Embed Size (px)
Citation preview
Plastic Deformation and Corrosion in
Austenitic Stainless Steels
Thesis
Proposed to be submitted in partial fulfillment of the requirements of
the degree of
Doctor of Philosophy
from
Indian Institute of Technology Bombay, India
&
Monash University, Australia
by
Srinivasan Narayanan
Supervisors:
Prof. Indradev Samajdar (IIT Bombay), Prof. Nick Birbilis (Monash University), Prof. Vivekanand Kain (BARC)
The course of study for this award was developed jointly by Monash University, Australia and the Indian
Institute of Technology Bombay and was given academic recognition by each of them. The programme
was administrated by The IITB-Monash Research Academy.
2016
Approval Sheet
The thesis entitled “Plastic Deformation and Corrosion in Austenitic Stainless Steels” by
Srinivasan Narayanan is approved for the degree of Doctor of Philosophy
ii
Declaration
I declare that this written submission represents my ideas in my own words and where others’
ideas or words have been included, I have adequately cited and referenced the original sources. I
also declare that I have adhered to all principles of academic honesty and integrity and have not
misrepresented or fabricated or falsified any idea/data/fact/source in my submission. I understand
that any violation of the above will be cause for disciplinary action by the Institute and can also
evoke penal action from the sources which have thus not been properly cited or from whom
proper permission has not been taken when needed.
Notice 1
Under the Copyright Act 1968, this thesis must be used only under the normal conditions of
scholarly fair dealing. In particular no results or conclusions should be extracted from it, nor
should it be copied or closely paraphrased in whole or in part without the written consent of the
author. Proper written acknowledgement should be made for any assistance obtained from this
thesis.
Notice 2
I certify that I have made all reasonable efforts to secure copyright permissions for third-party
content included in this thesis and have not knowingly added copyright content to my work
without the owner’s permission.
Student Name : Srinivasan Narayanan
IITB ID : 10411412
Monash ID : 27678700
iii
Acknowledgements
I would like to thank my thesis advisors at IIT Bombay, Monash University and Bhabha Atomic
Research Centre (BARC) for valuable guidance and support. I would also like to thank the
research progress committee members, Prof. A. Tewari and Prof. C. Davies for encouraging me
during annual progress seminar presentations. I thank Prof. V. S. Raja and Prof. K. Narasimhan
for motivating me at various stages of the doctoral degree.
The interactions with Dr. M.N. Gandhi, Dr. C. S. Harendranath, Mr. N. Marle, Ms. P. Kapre,
Mrs. P. Nikam from Centre for Research in Nanotechnology & Science (CRNTS) were very
much useful.
I am thankful to Dr. P.M. Ahmedabadi, Dr. S. Roychowdhury, Dr. G. J. Abraham, Dr. K.
Chandra, Mr. S. Kumar, Mr. K. Noduru, Mr. P. Singha, Mr. M. Patil, and Mr. A. Ajay of
Corrosion Science Section of BARC and Mr. Rajagopalan, Mr. Ayyapan, Mr. Hankare of BARC
for their help during the experimental work.
I sincerely thank Prof. S.S Joshi, Prof. R. Singh from Mechanical department of IIT Bombay for
granting permission to use the experimental facilities in their labs. I really enjoyed working with
them.
I would like to thank my friends at National facility of Texture and OIM at Department of
Metallurgical Engineering and Materials Science of IIT Bombay, Jain, Basu, Ajay, Satish, Raj,
Jaiveer, Abhishek, Gulshan, Ashish, Arijit, Durga, Jam, Partho, Minit, Sarkar, Manna, Parvej,
Kushal, Riya, Divya, Rakesh, Nachiket, Aditya, Hitesh, Irshad, Thiru, Suresh,
Many thanks are to Mr. Joshi, Mr. Prakash, Mr. Anil, Ms. Neelam, Ms. Sheha, of IIT Bombay
for their help during my experimental work and office staff of my department at IIT Bombay Mr.
Naresh for administrative help. Finally I thank IITB-Monash Research Academy, Board of
Research in Nuclear Science (BRNS), M/S Sandvik, for financial support and for giving me the
opportunity to carry out this research work.
Finally I thank my family members and my wife Lakshmi for constant support, patience and
encouraging me during PhD
iv
Abstract
This thesis contains study of localized corrosion behavior (sensitization and passivation) of cold-
worked austenitic stainless steel (SS). This has been covered in three parts: the first part deals
with in-grain misorientation and sensitization, second part deals with effects of deformed
microstructure on passivation, and the third part deals with study of Cr2O3 characterization at
machined sub-surfaces. Three different grades of austenitic SS grades (Sanicro 28
TM 1 hereinafter
called as alloy A, AISI (American Irons and Steel Institute) 316L and 304L) were selected in this
study. In the first part, AISI type 304L austenitic SS was cold rolled (25ºC) and warm rolled
(300ºC) followed by isothermal sensitization. Quantification of near boundary gradient zone was
done, partially automated, by appropriate computer algorithms. One-to-one microstructural
correlation was achieved by electron backscattered diffraction (EBSD) and white light
interferometry (WLI). Grains with visible fragmentation, or clear reductions in size, showed a
poor resistance to sensitization. However, non-fragmented deformed grains with clear presence
of near boundary orientation gradients provided an improved resistance.
For the second part, alloy A, 316L and 304L were subjected to anodic potentiodynamic
polarization test in 0.5M H2SO4 at room temperature after plane strain compression test.
Deformation microstructures developed in these grades, after plain-strain compression tests,
include strain-induced martensite. Alloy A showed the poor corrosion performance among three
alloys. Combination of microtexture measurements and Fourier transform infrared spectroscopy
(FTIR)-imaging revealed that the presence of strain-induced martensite promoted post-
passivation stability or retention of a protective Cr2O3 film.
In the third part, alloy A, 316L and 304L of austenitic SS were subjected to vertical milling.
These alloys exhibited difference in stacking fault energy and thermal conductivity. Anodic
potentiodynamic polarization tests did not reveal differences (between machined specimens) in
sub-surface machined layers. However, such differences were revealed in surface roughness,
sub-surface residual stresses, misorientations, and detection of subsurface Cr2O3 passive films. It
was shown, quantitatively, that higher machining speed reduced surface roughness & the
effective depths of the affected subsurface layers.
1 Sanicro 28 is an alloy marketed by Sandvik®. It is sold under the trademark Sanicro
28
TM
v
Contents
Acknowledgements iii
Abstract iv
List of Figures viii
List of Tables xv
Abbreviations xvi
Chapter 1 1
Introduction 1
References 2
Chapter 2 4
Literature Review 4
2.1.1 Introduction to Stainless Steels 4
2.1.2 Schaeffler Diagrams 5
2.1.3 Deformation-Induced Martensite 8
2.2 Deformed Microstructure: Focus Austenitic Stainless Steels 10
2.2.1 Introduction 10
2.2.2 Microstructure 10
2.2.3 Near Boundary Gradient Zone and Near Boundary Shear Strain 17
2.2.4 Strain Induced Martensite Transformation 18
2.2.5 Plastic Deformation Models 20
2.3 Localized Corrosion of Stainless Steels: Focus Sensitization 22
2.3.1 Introduction 22
2.3.2 Mechanism of Sensitization 24
2.3.3 Mitigation Measures 24
2.3.4 Evaluating Degree of Sensitization 26
vi
2.3.5 Effect of Cold Working on Sensitization of Stainless Steels 27
2.4 Passivation Behavior of Stainless Steels 31
2.4.1 Introduction 31
2.4.2 Effect of Plastic Strain on Anodic Polarization Behavior 33
2.4.3 Effect of Alloying Elements on Passivity 38
2.5 Introduction to Machining and Residual Stress: Focus Austenitic Stainless
Steel with Corrosion Perspective 41
2.5.1 Introduction to Machining 41
2.5.2 Residual Stress: Definition and Origin 43
2.5.3 Measurement Techniques 44
2.5.4 Effect of Residual Stress on Corrosion 46
References 46
Chapter 3
Near Boundary Gradient Zone and Sensitization Control in Austenitic
Stainless Steels 72
3.1 Introduction 72
3.2 Experimental Methods 75
3.3 Results 80
3.4 Discussion 93
3.5 Conclusions 95
References 96
Chapter 4
Plastic Deformation and Corrosion in Austenitic Stainless Steels: A
Novel Approach through Microtexture and Infrared Spectroscopy 105
4.1 Introduction 105
vii
4.2 Experimental Methods 106
4.3 Results 109
4.4 Discussion 122
4.5 Conclusion 125
References 126
Chapter 5
Defining the Post-Machined Sub-Surface Damage in Austenitic
Stainless Steels 135
5.1 Introduction 135
5.2 Experimental Methods 136
5.2.1 Materials 136
5.2.2 Machining 136
5.2.3 Surface Roughness Measurement 137
5.2.4 Sub-Surface Characterization 137
5.2.5 Thermal Conductivity Measurement 141
5.3 Results 141
5.4 Discussion 151
5.5 Conclusions 154
References 156
Chapter 6 160
Concluding Remarks 160
Reference 162
List of Publications 163
viii
List of Figures
Figure 2.1 (Schaeffler -diagrams for estimating constitutions of stainless steels Ni equivalent=
wt-% Ni + 30 wt-% C + 25 wt-% N + 0.5 wt-% Mn. Cr equivalent= wt-% Cr + wt-% Mo + 1.5
wt-% Si + 0.5 wt-% Nb + 1.5 wt-% Ti. α = Ferrite;α′ = martensite;γ = austenite [19]
Figure 2.2 Variation of critical stress required for transformations at different temperatures. The
regimes of stress assisted and strain induced transformations are indicated [33,41–43]
Figure 2.3 Schematic representation of crystallographic slip twinning [58]
Figure 2.4 Feasible microstructural features of deformed austenitic stainless steels. This
classification is based on equivalent stress-strain regions [17]
Figure 2.5 Configuration of dislocations through TEM. (a) The pile-ups of dislocations in
deformed austenitic stainless steels. (b) Formation of dislocation tangles [31] (c) Images of the
304 stainless steels deformed at very high strain rates 4. 8 x103s
-1 [60].
Figure 2.6 Generation of deformed microstructural features in FCC metals and alloys [67,68]
Figure 2.7 Plastic deformation generates different evolution of microstructural features [69–73]
Figure 2.8 Typical example of microbands and shear bands. (a) intersection of microbands at
twin bands [86]. (b)TEM structure of 80% cold rolled Fe revealing cells and microbands [31]. (c)
the pattern of shear bands [87]
Figure 2.9 Optical micrograph (a) and Electron backscattered diffraction (EBSD) (b-c) of
deformation induced shear bands of stainless steels [88]
Figure 2.10 Schematic representation of how grains of different orientation affects formation of
shear band [85]
ix
Figure 2.11 Representation of NBGZ (a) deviations from average grain orientation are in grey
scale. Black is no orientation deviation [98]. (b) The gradient zone is quantified by user defined
cur off quantities from drawing line profiles, grain center to grain boundary [96].
Figure 2.12 Representation of mesoscopic (a) shear strain and (b) in-grain misorientation after
progressive plane strain compression (PSC) tests [95]
Figure 2.13 (a) Presence of strain induced martensitic at the intersection of shearbands [36], (b)
EBSD phase map of strained specimen [107]
Figure 2.14 Vibrating sample magnetometer (VSM) estimated volume fraction of strain induced
martensite (SIM) of 304N and 304H austenitic SS [35].
Figure 2.15 Plastic deformation models: Sachs model (a-d) [125] and Taylor model (e-h)
[55,143]. Sachs model assumes single slip in each grain. Taylor model assumes many slip in
each grain.
Figure 2.16 The corrosion issues (various forms of corrosions) associated with AISI 304 and
316 SS [7]
Figure 2.17 (a) Schematic representation of grain boundary with a chromium depleted zone. (b)
chromium depletion profiles [164]
Figure 2.18 Electron backscattered scanning image shows different types of immunity of grain
boundaries to sensitization in austenitic stainless steels [164]
Figure 2.19 Schematic illustrating the procedure of single loop EPR test [198]
Figure 2.20 Schematic illustrating the procedure to calculate ratio of DoS from anodic and
reverse currents from double loop EPR test [195]
Figure 2.21 Time-Temperature curves of M23C6 precipitation behavior observed in 304 stainless
steels [205]
x
Figure 2.22 The effect of cold rolling on DoS. (a) after sensitization heat treatment for 1h and 5h
and (b) 1h [182].
Figure 2.23 Effect of EGBE on DoS of 316L(N) stainless steels with (a) 0.0829 and (b) 0.52 wt
% of Cu [206].
Figure 2.24 Typical anodic polarization curves indicating different anodic behavior of metallic
materials in aqueous solutions [252]
Figure 2.25 (a) Mott-Schottky plots [250] and (b) The dependence of semiconducting
parameters (ND and NA) on the film with strain [246]
Figure 2.26 Anodic potentiostatic anodic polarization curves of annealed and cold worked 430
SS [113]
Figure 2.27 Potentiostatic anodic polarization curves of cold worked at 27ºC and -196ºC on 304
stainless steels [113]
Figure 2.28 (a) Critical pitting potential values for cold rolled alloys, (b) Transmission electron
microscope (TEM) images revealing high density of narrow and sharper deformation bands. (c)
Scanning electron microscope (SEM) of 40% cold rolled specimen revealed high density of
deformation bands and (d) scarcely distributed bands [269].
Figure 2.29 Price variations of steel grades with respect to corrosion resistance [144]
Figure 2.30 Effect of alloying elements on anodic polarization curves in stainless steels [149]
Figure 2.31 Schematic of different types of residual stresses. The processes, origin (residual
stress arise from misfit) and residual stress patterns are included for each condition [327].
Figure 2.32 Classification of different residual stress measurement methods [328]
Figure 2.33 (a) strain free lattice (b) change in ‘d’ due to application of tensile stress
horizontally (c) position of Bragg peaks with and without application of tensile stress after
diffraction [336]
xi
Figure 3.1 Results of electrochemical tests on 304L stainless steel - (a) Electrochemical
polarization of as-received and cold rolled (room temperature) SS 304L in DL-EPR test
solution (0.5M H2SO4+ 0.01M KSCN) at room temperature at a scan rate of 100 mV/min., (b)
measured OCP vs. time graph of as-received and cold rolled specimens, (c) DL-EPR curves of
5 and 20% cold rolled specimens after sensitization at 675°C,6 h, (d) degree of sensitization
(DoS) as a function of prior rolling reductions. Rolled samples, cold (RT - room temperature)
and warm (300°C) rolled, were sensitized at 675°C,6 h and then the DoS values were
established by DL-EPR test. Data points with fragmented grains, as indicated in figure 3.1d, are
enveloped in a dotted line.
Figure 3.2 Electron backscattered diffraction (EBSD) image quality (IQ) maps of (a) 0%, (b)
5%,and (c) 20% cold rolled and then sensitized specimens. In (c) arrows are used to indicate
regions with visible grain fragmentation.(d) Quantification of grain fragmentation is presented as
number fraction of grains below 2 micron (as estimated from standard linear intercept method).
Figure 3.3 Scanning electron microscope (SEM) micrographs showing post DL-EPR surfaces of
(a) 0%, (b) 5% and (c) 20% cold rolled and then sensitized specimens. The images clearly
indicate regions of attack during DL-EPR test.
Figure 3.4 The percentage DoS versus (a) average grain size, (b) kernel average misorientation
(KAM), (c) grain orientation spread (GOS) and (d) grain average misorientation (GAM). Data
represents measurements from microstructures without visible grain fragmentation. Standard
deviations from multiple EBSD scans are used to provide the respective error bars. Measurement
uncertainties, or in-grain misorientations typically estimated in a fully recrystallized structure,
are shown as dotted lines in (b)-(d).
Figure 3.5 Percentage DoS versus estimated number fractions of (a) 1 and (b) 3 boundaries.
Data represents measurements from microstructures without visible grain fragmentation.
Standard deviations from multiple EBSD scans are used to provide the respective error bars.
Standard Brandon’s criteria ((Δθ= 15ºΣ-1/2
, where Δθ is angular deviation from exact CSL) [49]
was used for the identification of the CSL nature.
Figure 3.6 (a) Representing near boundary gradient zone (NBGZ) in two neighboring grains
after 5% cold deformation and subsequent sensitization. Grey scale indicates orientation
xii
gradient from the grain average (quaternion average) orientation. The geometric grain centers
were identified and profile vectors (till the grain boundaries) were drawn. (b) From 100 such
line vectors, misorientations (from the respective grain average orientations) versus normalized
distance (xi = ) were drawn. This was done through a custom computer program.
NBGZs were then the derivative of the slope of misorientation profile exceeding1°. Gradient
(Gi) and normalized distances ( Xi) of such NBGZs were estimated from equations (3.5) and
(3.6) respectively.
Figure 3.7 Percentage DoS versus average (a) gradient and (b) dimension of the gradient zone.
Datawere obtained from microstructure without visible grain fragmentation. Standard
deviations are represented as error bars.
Figure 3.8 Relating grain average depth of attack and NBGZ for the same region (a)
combining information from EBSD and WLI, (b) NBGZs, for 5% cold rolled specimens
Figure 3.9 Grain average depth of attack versus (a) average grain size, (b) kernel average
misorientation, (c) grain orientation spread and (d) grain average misorientation. Data were
obtained from 100 randomly selected grains from the 5% deformed plus sensitized sample.
Figure 4.1 (a) Schematic of a anodic potentiodynamic polarization curve showing Ecorr, iP, icrit
and Ecrit. Anodic potentiodynamic polarization curves after progressive plane strain compression
(true strains of 0.09,0.26,0.58) in (b) alloy A, (c) 316L and (d) alloy C.
Figure 4.2 (a) icrit and (b) ip (as in figure 4.1) for three different grades as a function of true
strain. In the respective figures, the extent of increase in icrit and ip are indicated for the alloys A,
316L and 304L.
Figure 4.3 (a) EBSD image quality (IQ) maps of the prior and post deformation specimens. (b)
Average grain sizes and (c) grain average misorientions were plotted as a function of true strain.
In (b) and (c) times decrease/increase in average grain size and grain average misorientation are
indicated for the respective grades. Error bars in (b) and (c) represent standard deviations from
multiple EBSD scans.
xiii
Figure 4.4 (a) Hardness and (b) percentage martensite versus true strain. Error bar in (a)
represents standard deviations from multiple measurements.
Figure 4.5 Chromium concentration (in wt%) versus depth. Data were obtained from the
respective post-passivation specimens of (a) Alloy A, (b) 316L and (c) 304L.
Figure 4.6 (a) FTIR-imaging estimated area under Cr2O3 peak as a function of true strain of
three grades of austenitic stainless steels. Multiple measurements were taken in the three grades
after progressive deformation. The data include ‘all’ measurement points and also their
respective average and standard deviation (as error bars). At least 100 measurement points were
taken in each case. (b) Two characteristic FTIR-imaging spectra (transmittance versus
wavenumber) are also included as reference.
Figure 4.7 (a) Direct observation on progressively plane strain compressed alloy A. This is
shown with EBSD IQ maps for true strains of 0, 0.04 and 0.09. (b) In the same samples, area
under Cr2O3 peaks were measured at different locations and are plotted as a function of kernel
average misorientation.
Figure 4.8 EBSD plus FTIR-imaging data in 316L after a true strain of 0.26. Area under Cr2O3
peak (and corresponding FTIR-imaging spectra) and EBSD estimated KAM values are shown at
three locations: (i) without strain localization (KAM = 0.45˚and FTIR = 0.05 cm-1
), (ii) with
strain localization (KAM = 0.70˚ and FTIR = 0.006 cm-1
) and (iii) with strain localization plus
SIMF (strain induced martensite formation) (KAM = 0.86˚ and FTIR 0.21cm-1
). SIMF is also
shown through EBSD phase map.
Figure 4.9 Average FTIR-imaging estimated area under Cr2O3 peak. This is given for different
microstructural features in the three alloys at different stages of plastic deformation. The error
bars represent standard deviations from multiple measurement points
Figure 5.1 Front view of the vertically milled specimens. This was valid for all three grades
(alloy A, 316L, 304L) of austenitic stainless steels.
Figure 5.2 (a) Schematic of grazing incidence X-ray diffraction (GIXRD) indicating angular
conventions for , and . The figure also includes standard representation of the residual stress
xiv
matrix:3 representing normal to the machining surface. (b) Multiple {hkl} GIXRD measurement:
showing different {hkl} peaks. They were then converted into a d-sin2
plot.
Figure 5.3 Measured surface roughness versus strain rates. Error bars represent standard
deviations from multiple measurements (two such representative measurements of surface
textures are included).
Figure 5.4 Anodic potentiodynamic polarization curves of the subsurface region marked in
figure 5.1. These are shown for all three grades: (a) alloy A, (b) 316L (b) and (c) 304L.
Figure 5.5 Multiple {hkl} GIXRD estimated τ 13 and σ11 (for stress conventions refer figure 2a)
versus depth of penetration for different grades of stainless steels. Also included are magnified
stress gradient profiles to establish the role of alloy chemistry and machining speed.
Figure 5.6 (a) EBSD IQ (Image quality) maps of as-received state and the sub-surface machined
region in all three grades of austenitic stainless steels machined at 2100, 1050, 105 s-1
strain
rates. (b) Magnified region was then used to map out KAM (kernel average misorientation) in
alloy A. This shows strong strain rate (or machining speed) dependence of KAM developments.
Figure 5.7 Kernel average misorientation (KAM) versus depth (from the top surface) for (a)
alloy A, (b) 316L and (c) 304L. Effective heights (h*) were estimated from the distance
corresponding to ½ (maximum + minimum) readings in y-axis.
Figure 5.8 (a-c) FTIR- imaging estimated area under Cr2O3 peak versus depth for: (a) alloy A,
(b) 316L and (c) 304L. The effective heights (or depths) were measured from as the distance
corresponding to ½ (maximum + minimum) readings in y-axis. (d) Two representative FTIR-
imaging spectra (transmittance vs wavenumber) are included as reference.
Figure 5.9 The effective heights (h* values) versus of three grades (alloy A, 316L, 304L) of
austenitic stainless steels. These are shown for all three strain rates.
xv
List of Tables
Table 2.1. Classification of stainless steel grades based on microstructure, chemistry and
applications [3,6,8–11,19,21]
Table 2.2 Typical IGC tests for austenitic stainless steels [149,193]
Table 3.1 The chemical composition (in weight % alloying elements) of the AISI304L
Table 3.2 Vickers hardness (microhardness with 300 g load) of the ‘cold rolled’ and ‘cold rolled
and sensitized’ specimens. The data were obtained from at least 10 random indentations.
Table 4.1 The chemical composition (in wt% alloying elements) of the three austenitic stainless
steel grades
Table 4.2 Change in anodic polarization parameters (ip and icrit) with strain. These are shown for
all three grades (alloy A, 316L and 304L ) and respective strain increments of 0-0.09, 0.09-0.26
and 0.26-0.58.
Table 4.3 Integration of chromium oxide (Cr2O3) signal intensity for cold rolled alloys.
Table 5.1 The chemical composition (in wt% alloying elements) of the three austenitic
stainless steel grades
Table 5.2 Calculated maximum τ 13 and σ11 for different strain rates of all grades of stainless
steels
Table 5.3 The stacking fault energy and thermal conductivity values of the three austenitic
stainless steels grades
xvi
Abbreviations
BCC Body Centered Cubic
CI Confidence Index
CSL Coincident Site Lattice
DoS Degree of Sensitization
EBSD Electron Backscattered Diffraction
FCC Face Centered Cubic
FEG Field Emission Gun
FTIR Fourier Transform Infrared Spectroscopy
GAM Grain Average Misorientation
GIXRD Grazing Incidence X-Ray Diffraction
GOS Grain Orientation Spread
GS Grain Size
HCP
IGSCC
IQ
Hexagonal Close Packed
Intergranular Stress Corrosion Cracking
Image Quality
KAM Kernel Average Misorientation
NBMS
NBGZ
OCP
Near Boundary Mesoscopic Shear
Near Boundary Gradient Zone
Open Circuit Potential
OIM
SCC
Orientation Imaging Microscopy
Stress Corrosion Cracking
SCE
SEM
Saturated Calomel Electrode
Scanning Electron Microscope
SS Stainless Steel
TEM Transmission Electron Microscope
ToF SIMS Time of Flight Secondary Ions Mass Spectroscopy
TSL Tex Sem Ltd
WLI
White Light Interferometry
1
CHAPTER 1
Introduction
Austenitic stainless steels (SS) offer a combination of good mechanical strength and excellent
uniform corrosion resistance [1–3]. The latter originates from the formation and retention of a
stable, thin and protective layer of chromium (Cr) rich oxide [4]. The local breakdown of the
protective film is of concern, as it causes localized corrosion - intense attack at localized sites [5–
7]. Mitigation of the localized corrosion may require tailoring the alloy chemistry and/or
controlled thermo-mechanical processing (TMP) [8,9]. A TMP may alter the substrate structure
and in turn affect local Cr-depletion or nature/stability of the protective film. However, any
correlation between the substrate microstructure and the protective film remains, at best,
empirical. This was the motivation behind the present thesis: Plastic Deformation and Localized
Corrosion in Austenitic Stainless Steel.
This study used three grades of stainless steels: Sanicro 28TM
(an alloy marketed by Sandvik®)
called as alloy A, commercial AISI (American Iron and Steel Institute) 316L and 304L SS. 304L
was used for sensitization studies in chapter 3, while all three grades were involved in chapter 4
and 5.
Two types of localized corrosion were considered – sensitization and general passivation. The
former involves grain boundary precipitation of Cr-rich carbides and a result Cr-depletion in the
immediate surroundings. If this Cr-depletion goes below 12-wt%, a local breakdown in
passivation is created. This is called sensitization. The sensitization is controlled through altering
the alloy chemistry, suitable solutionizing treatment and changing the grain boundary character
distribution [5,7]. This thesis presents a third, and novel, possibility of sensitization control
through localized plastic deformation. This has been presented in the Chapter 3: “Near boundary
gradient zone and sensitization control in austenitic stainless steel”. This chapter shows that
presence of near boundary gradient zone (NBGZ) [10], and corresponding diffusion short-cuts,
can provide a previously uncharted means for effective sensitization control in austenitic
stainless steels.
2
The other two thesis chapters cover the post-deformation general passivation. Effectiveness of
the Cr2O3 films with respect the substrate microstructure was evaluated through combined
measurements of microtexture and post-passivation FTIR (Fourier transformed infrared
spectroscopy)-imaging. Area under the characteristic Cr2O3 FTIR-imaging peak was used as a
relative measure of the Cr2O3 presence. It may be noted that this is the first such effort, as
recorded in the published literature: A relatively simple but quantitative validation for the local
stability/retention of Cr2O3 film. Once this technique was established, it was used for two
specific cases. Firstly, for establishing role of strain induced martensite formation (SIMF) on the
stability/retention of Cr2O3 film. Though conventional knowledge indicates that SIMF is bad for
corrosion performance, chapter 4 shows (through a combination of bulk electrochemical
measurements plus microtexture/FTIR-imaging) results in clear contradiction. Chapter 5, on the
other hand, explores the effects of alloy chemistry and machining speed on the sub-surface
damage. The damage was evaluated in terms of residual stress profiles, gradients in
misorientation and Cr2O3 presence (again through FTIR-imaging). Experimental observations
were rationalized in terms of stacking fault energy and temperature dependent thermal
conductivity of the respective grades.
In addition to chapters 3-5, the thesis also contains a chapter on the literature review (Chapter 2).
Chapter 2 contains exhaustive, recent and most cited research articles detailing the deformed
microstructure and its effects on electrochemical behavior of austenitic stainless steel. The last
chapter, Chapter 6: Concluding Remarks, summarizes the novelty of the thesis and also provides
a possible road-map for future research.
References
[1] P.Marshall, Austenitic Stainless Steels Microstructure and Mechanical Properties, first ed.,
Elsevier applied science publishers, England, 1984.
[2] M.G.Fontana, Corrosion Engineering, first ed., Tata Mc-Graw Hill Edition, New Delhi,
1986.
[3] A.J.Sedriks, Corrosion of Stainless Steels, second ed., A Wiley-Interscience Publication,
New York, 1996.
3
[4] B.Stellwag, The mechanism of oxide film formation on austenitic stainless steels in high
temperature water, Corros. Sci. 40 (1998) 337–370.
[5] H.J.Engell, Stability and breakdown phenomena of passivating films, Electrochim. Acta.
22 (1977) 987–993.
[6] N.Sato, The stability of localized corrosion, Corros. Sci. 37 (1995) 1947–1967.
[7] G.T.Burstein, C.Liu, R.M.Souto, S.P.Vines, Origins of pitting corrosion, Corros. Eng. Sci.
Technol. 39 (2004) 25–30.
[8] M. Kumar, A.J. Schwartz, W.E. King, Microstructural evolution during grain boundary
engineering of low to medium stacking fault energy fcc materials, Acta Mater. 50 (2002)
2599–2612.
[9] B.Verlinden, J.Driver, I.Samajdar, R.D.Doherty, Thermo Mechanical Processing of
Metallic Materials, first ed., Pergamon Materials Series, Great Briton, 2007.
[10] N.Srinivasan, V.Kain, N.Birbilis, K.V.Mani Krishna, S.Shekhawat, I.Samajdar, Near
boundary gradient zone and sensitization control in austenitic stainless steel, Corros. Sci.
100 (2015) 544–555.
4
CHAPTER 2
Literature review
2.1.1 Introduction to Stainless Steels
Stainless steels are alloys of iron (Fe) and chromium (Cr) [1]. Chromium enables formation of
thin, adherent, protective layer of Cr oxide making stainless steels (SS) resistant to uniform
corrosion, particularly rusting. Elements such as molybdenum (Mo), manganese (Mn), silicon
(Si), nickel (Ni), nitrogen (N), sulfur (S), titanium (Ti), carbon (C) may also be present [1–3].
They influence properties of SS: example, corrosion resistance, formability and machinability
[4]. In 1889, Glasgow found an improvement of tensile strength in mild steel by addition of Ni.
In 1905 Portevin found that steel containing 9% Cr were shown to be resistant to corrosion [2,5].
Between 1990 and 1915, the gradual developments in actual stainless steels had happened [6].
The potential of this new alloy was first recognized in 1821 by French metallurgist Pierre
Berthier [5]. Naturally, the alloy developments in SS have come a long way. A large number of
commercial grades [5, 6] are available today for a range of applications.
The SS grades are classified according to microstructures such as austenitic, ferritic, duplex,
martensitic and precipitation-hardening grades [1]. The nomenclatures of such grades are
provided by various standards. For example, American iron and steel institute (AISI) classifies
them by a three-digit code [3]. Some of these grades are listed in table 2.1. A combination of
microstructure and alloying elements in SS determines specific applications [3,5 7–10].
Austenitic Stainless Steels
In general, austenitic grades are classified into three groups (i) lean alloys (AISI 201, AISI 301,
AISI 304), (ii) Cr-Ni alloys (AISI 302, AISI 309, AISI 310, AISI 347), and (iii) Cr-Mo-Ni-N
alloys (316L, 317L) [6,8] . Austenitic SS are non-magnetic with face centered cubic crystal (fcc)
structure. This class of SS also transforms to strain-induced martensite [12–16]. Leaner the
austenitic grade, lower is the austenite stability [17]. The unstable austenite transforms into
martensite and thus provides transformation induced plasticity [18]. Though strain induced
martensite can have strong influence on the corrosion behavior (Chapter 4), it can enhance
5
ductility. For example, AISI 304 SS and its derivative are highly ductile and easily shaped, can
be easily deep drawn due to its lower austenitic stability.
Ferritic Stainless Steels
Ferritic SS can contain up to 30 wt% Cr, plus additional Mn and Si [10]. Based on chemical
compositions that dictate the general characteristics and corrosion resistance, this grade can be
divided into four groups, see Table 2.1. AISI 444 grades are used for environment that requires
higher corrosion resistance. AISI 409 is used in automobile industry [19]. AISI 430 and AISI
434 grades are used for household applications [9,10].
Duplex Stainless Steels
It can contain 18-29% Cr, 2.5-8.5% Ni, 1-4% Mo and up to 2.5% Mn, up to 2% Si, up to 0.35%
N [11]. Compared to austenitic grades, it posses improved yield strength and greater resistance to
localized corrosion [11,20]. Duplex SS are used as structural member in desalination plants, heat
exchangers, and to carry hot and dry gases/fluids in petrochemical industries [11].
Martensitic Stainless Steels
Martensitic SS are Cr containing steels without Ni [2,6]. Martensitic SS find its application in
steam and gas turbines. It can also be used as cutting utensils and fasteners [2,3,6,7].
Precipitation Hardened Stainless Steels
Precipitation hardened steels are austenitic or matensitic, or semi-austenitic crystal structures
depending upon the heat treatment [2]. Typical applications include spring holders and springs,
chains, valves, gears, pressure vessels [2,6,7].
2.1.2 Schaeffler Diagrams
The effect of alloying elements on microstructure of SS is detailed in Schaeffler diagram (figure
2.1). The diagram is based on the fact that the alloying elements can be divided into ferrite
stabilizers (promote formation of ferrite) and austenite-stabilizers (promote formation of
austenite). The chromium and nickel equivalents are defined as:
Chromium equivalent = %Cr + 1.5 x %Si + %Mo (2.1)
6
Nickel equivalent = %Ni + 30 x (%C + %N) + 0.5 x (%Mn + %Cu + %Co) (2.2)
Table 2.1 Classification of stainless steel grades based on microstructure,
chemistry and applications [3,6,8–11,19,21]
Classificat
ion
Constituent
Microstructure
Range of major alloying
elements composition wt %
Cr Ni Mo
Applications
AISI 200
series
Austenitic 16-19 3-6 -- Household, storage vessels, and
engineering applications [6,8]
AISI 300
series
Austenitic 16-26 8-37 2-4
400 series
AISI 409 Ferritic 10-12 ≤0.5 -- Railwagons, shipping containers,
automotive exhausts, bus and coach
frames, domestic appliances, indoor
panels, sinks, solar-water heaters,
[9,10,19,21]
AISI 430 Ferritic 16-18 ≤0.75 --
AISI 434 Ferritic 16-18 <1 1-2
AISI 444 Ferritic 17-20 ≤1 1-3
AISI 410 Martensitic 11-14 <1 -- Cutting utensils, fasteners, steam
and gas turbines [3]
AISI 431 Martensitic 15-17 1-3 --
Duplex series
7
AISI 329 Ferritic-
austenitic
23-28 2-5 -- Geothermal, nuclear, and solar
power, in pertrochemical industries
handling wet and dry gas [11]
Precipitation-hardening series
AISI 630 Martensitic 15-18 3-5 0.5 Pressure vessels, seals, aircraft
parts, chains, gears [3]
AISI 632 Semi-austenitic 14-16 6-8 2-3
Figure 2.1. Schaeffler -diagrams for estimating constitutions of stainless steels Ni equivalent=
wt-% Ni + 30 wt-% C + 25 wt-% N + 0.5 wt-% Mn. Cr equivalent= wt-% Cr + wt-% Mo + 1.5
wt-% Si + 0.5 wt-% Nb + 1.5 wt-% Ti. α = Ferrite; α′ = martensite; γ = austenite [19].
8
2.1.3 Deformation-Induced Martensite
During plastic deformation, metastable austenite transform into deformation induced martensite
transformation[12,22]. Two transformation mechanisms are involved. One of the transformations
is γ→ α’. Formation of α
’ is
from intermediate ε phase hexagonal close packed (hcp) [12,23–26].
This depends on stacking fault energy, which, in turn, depends on the chemical composition [27–
29].The chemical free energy difference decides deformation-induced martensite transformations
[29–32]. The transformation of martensite is diffusionless or displacive. Due to the relatively low
interstitial content, the crystal structure of α-martensite is bcc and not body-centered tetragonal
(bct) [30,31].
Thermodynamics of Martensite Formation
The thermodynamics of such transformation is represented in figure 2.2a. Spontaneous
transformations happen if difference between chemical free energies of both parent and product
reaches a critical value ∆GMs γ→ α’
, which occurs at Ms temperature. The transformation can also
occur at T1 (>Ms), if sufficient mechanical driving force U is available,
∆GT1 γ→ α’
+ U= ∆GM1 γ→ α’
(2.3)
The origination of mechanical driving force (U) is from imposed stress [32,33].
U’= so+ o= 0.5 So sin 2 0.5 o (1+cos 2 ) (2.4)
Figure 2.2a suggests that the chemical driving force of the martensitic transformation decreases
linearly with the increasing temperature. Thus, as indicated by equation 2.3 and 2.4, Below Msσ
temperature, the yielding can occur by means of the martensitic transformation, whereas at
higher temperatures the transformation can take place only after the plastic deformation of the
austenite phase.
The Md temperature defines the upper limit for the strain-induced transformation. In the case of
strain-induced transformation, the role of the mechanical driving force remains to be fully
charted. Several explanations, reported in the literature to explain mechanical driving force in
strain- induced transformation, are given below.
9
Plastic deformation helps to nucleate martensite particles by generating favorable
nucleation sites when stress is applied
Low SFE alloys such as Fe-Ni-Cr enables formation of strain-induced martensite at
higher temperature.
For nucleation of strain induced martensite, internal stress due to dislocation pile up
produces mechanical driving force. The temperature at which 50% transformation of
martensite at true strain of 30% was calculated using [12,34] the equation 2.5
Md30 = 413-462 (C+N)-9.2(Si)-8.1 (Mn)-13.7(Cr)-9.5(Ni)-18.5(Mo) (2.5)
The volume fraction of strain-induced martensite transformation, depends on alloy chemistry
[35], austenitic grain size [15], and thermo-mechanical treatment [12,32]. Strain-induced
martensite influence mechanical properties (flow stress, work hardening rates) [16,36] and
corrosion properties (sensitization, pitting corrosion) [34,37–40]. This topic is of relevance to the
thesis discussed in (Chapter 4).
(a) (b)
Figure 2.2 Variation of critical stress required for transformations at different temperatures. The
regimes of stress assisted and strain induced transformations are indicated [33,41–43]
10
2.2 Deformed Microstructure: Focus Austenitic Stainless Steels
2.2.1 Introduction
Plastic deformation in austenitic stainless steels can occur either by slip or by twinning [30]. The
{111} octahedral planes and <110> directions constitute slip systems (total 12) for austenitic SS
[30]. A minimum of stress required for slip to occur is known as critical resolve shear stress.
Like slip, twinning also occurs in a definite direction on a specific crystallographic plane - the
twinning system for austenitic SS is {111} <112> [44,45]. A schematic representation of slip
and twinning is shown in figure 2.3. Twinning occurs when the slip systems are restricted or
something increases critical resolve shear stress so that twinning stress is lower than the stress
for slip. For example, twinning is preferred mechanism of plastic deformation in nitrogen alloyed
austenitic SS [46,47]. Twinning is affected by crystal structure [48], stacking fault energy (SFE)
[49,50], orientation [51,52], grain size [53,54] and strain rate [55–57].
Figure 2.3 Schematic representation of crystallographic slip twinning [58]
2.2.2 Microstructure
Microstructure is defined as examination of distinct structural features, visible, if examined with
a microscope [31]. Microstructures constitute one or more phases, point defects (vacancies and
interstitials), line defects (dislocations), and volumetric defects (grain boundaries, voids) [30].
Phases and defects determine properties of materials. Phase is defined as with clear distinct
crystal structure and/or chemical composition, separated by boundaries [49,52,31,59]. Defects
are discontinuity in perfect periodicity of crystal structure.
11
Different types of deformed microstructures of austenitic SS in the stress-strain regime is shown
in figure 2.4 [17]. Deformed microstructure of austenitic SS up to 400 MPa, dislocation tangles
are dominant. Stacking faults can form for the stress range 400-600 MPa and larger stacking
faults can be formed beyond 400-600 MPa. Stacking fault energy dictates types of dislocations
arrangements [30,31]. Dislocation structure is different at different strain regime and is shown in
figure 2.5.
Figure 2.4 Feasible microstructural features of deformed austenitic stainless steels. This
classification is based on equivalent stress-strain regions [17].
(a) (b) (c)
Figure 2.5 Configuration of dislocations through TEM. (a) The pile-ups of dislocations in
deformed austenitic stainless steels. (b) Formation of dislocation tangles [31] (c) Images of the
304 stainless steels deformed at very high strain rates 4. 8 x103s
-1 [60].
12
Substructures Evolution
Substructure is defined as distribution of second phases, grain boundaries, and twin boundaries
[61,62]. Commonly observed microstructural features by optical microscopy are grain
boundaries and twin boundaries. Second phase in microstructure can be examined using electron
microscopy techniques. Fragmentation of grains by deformation induced dislocation boundaries
are classified into (i) geometrically necessary boundaries (GNB) [63–66] and (ii) incidental
dislocation boundaries (IDB) [63–66]. The GNB separate crystallites by activating different slip
systems and/or strain amplitudes. The formation of IDB takes place by trapping of glide
dislocations. During plastic deformation, single crystals subdivide into many crystallites of
different crystal orientation. This is the signature of inhomogeneous plastic flow and is shown in
figures 2.6-2.7.
Figure 2.6 Generation of deformed microstructural features in FCC metals and alloys
[67,68]
13
Figure 2.7 Plastic deformation generates different evolution of microstructural features
[69–73]
Dislocation Substructures
With increasing strain, the misorientation angle across the GNB and IDB increases and the
spacing between boundaries decreases [63–67,70,71,74,75]. At low to medium strain, the
following features, cell blocks (CB), deformation bands, and Taylor lattices are evident [25, 26] .
Taylor lattice are observed at the onset of plastic deformation and consists of parallel
dislocations of alternating sign [63–66,72]. Microbands appear thin plate within a grain [63–
66,71,72]. Shear bands appear at larger plastic strains and are not parallel to slip planes. Shear
bands form at certain specific angles [76–79].
Strain Heterogeneities in Stainless Steels
Plastic deformation is usually inhomogeneous in nature. Two types of inhomogeneties, exists
viz.(i) heterogeneities within grain [80,81] and (ii) heterogeneities involving several grains
14
[82,83]. In-grain heterogeneities require characterization at different length scales [80] and are
influenced by strain, strain path, and SFE. Shear bands are an example of heterogeneities
involving several grains. The size and volume fraction of shear bands depend on SFE [81].
Transmission electron microscopy (TEM) has been used to explore microbands and shear bands.
Microbands are defined as thin-plate region that appear at higher strains ≥ 1 during rolling and
extrusion processes [31] and shear band occur due to localized shears cutting across several
grains [31,84]. Multiple microbands intersecting twin bands are shown in figure 2.8a. At higher
strains, grains tend to form bands of different orientations. Microbands with uniform thickness is
shown in figure 2.8b, revealed bands, separated by transition zones and grain boundaries.
Fluctuations in shear bands thickness can vary 5-50 μm (figure 2.8c). When slip and twinning
cannot accommodate the deformation, differential response, in development of shear bands is
evident. Inclined nature of shear bands (figure 2.9a) are characterized by electron backscattered
diffraction (EBSD). A typical EBSD map is shown in figure 2.9a-b. EBSD scans of such regions
are indicative of severe plastic deformation and grains are fragmented into several parts with the
same color (figure 2.9c). Effect of favorable (low Taylor factor) and unfavorable (high Taylor
factor) oriented grains influence the misorientation development adjacent to shear band [85].
Figure 2.10 shows effect of different orientation affects formation of shear bands.
15
(a) (b)
(c)
Figure 2.8 Typical example of microbands and shear bands. (a) intersection of
microbands at twin bands [86]. (b)TEM structure of 80% cold rolled Fe revealing cells and
microbands [31]. (c) the pattern of shear bands [87].
16
(b)
(a) (c)
Figure 2.9 Optical micrograph (a) and Electron backscattered diffraction (EBSD) (b-c) of
deformation induced shear bands of stainless steels [88]
(a) (b)
Figure 2.10 Schematic representation of how grains of different orientation affects
formation of shear band [85]
17
2.2.3 Near Boundary Gradient Zone & Near Boundary Mesoscopic Shear
Strain
Plastic deformation leads to change in orientation of grains and development of deformation
texture [89]. Within a grain, gradients of orientation/misorientation often develops. Such
gradients may lead to creation of new lattice curvature and grain subdivision [90–92]. It is
normally stipulated that incompatibilities between relative rotation of individual crystallites lead
to near boundary mesoscopic shear (NBMS). The NBMS leads to near boundary gradients of
orientation/misorientation [93]. Orientation gradients depend on various factors such as strain
path [94,95], neighbor grains [96–99] etc. Orientation gradients also depend on microstructural
parameters and macroscopic variables [91,99]. Orientation gradients form gradually at lower
strains and build up further during deformation [89,90,100]. Buildup of plastic deformation near
grain boundary creates gradient of misorientation and termed as near boundary gradient zone
(NBGZ) [89,91,101–104], as shown in figure 2.11a-b. NBGZ can be rationalized by dislocation
theories [68,98,105] or crystal plasticity [106,107]. Misorientation developments are largely
restricted to regions around NBGZ [102,103]. Kamaya et al (2012) [102] has reported
distribution of large local misorientation in grain boundary due to impeded slip steps using
deformed 316 SS specimen. In an another study, Keskar et al (2014) [93] have established direct
correlation between mesoscopic shear strain and in-grain misorientation and grain fragmentation
for the same grain as shown in figure 2.12 a-b.
(a) (b)
Figure 2.11 Representation of NBGZ (a) deviations from average grain orientation are in
grey scale. Black is no orientation deviation [99]. (b) The gradient zone is quantified by user
defined cur off quantities from drawing line profiles, grain center to grain boundary [95].
18
(a) (b)
Figure 2.12 Representation of mesoscopic (a) shear strain and (b) in-grain misorientation after
progressive plane strain compression (PSC) tests [93].
2.2.4 Strain Induced Martensite Transformation
It was experimentally shown that nucleation of strain-induced martensite occurred at intersection
of shear bands (figure 2.13a) [108–110]. The other researchers argued that presence of ά
martensite is at single shear bands [111,112]. The effects of strain-induced martensite, on
stability passive films in cold rolled austenitic stainless steels were discussed (Chapter 4).
Disagreements exist on the exact role of strain-induced martensite on corrosion properties.
Further, its effect depends on size, distribution, nature, grain size. Elayaperumal et al (1972)
[113] have shown that passivity of cold rolled 430 stainless steels was better than cold rolled 304
steels. In another study, formation of the thicker passive film is reported in 66% cold worked 304
steels compared to solution annealed state [114]. This finding was attributed to higher Cr:Fe ratio
in cold worked specimen [114]. Electron backscattered diffraction (EBSD) [115] has also been
used to indicate presence of strain induced martensite as shown in figure 2.13b [116].
19
(a) (b)
Figure 2.13 (a) Presence of strain induced martensitic at the intersection of shearbands
[36] and (b) EBSD phase map of strained specimen [116].
According to Olson and Cohen [112,117], metastable austenitic SS form stress-assisted and
strain-induced martensite. The former forms by pre-existing nuclei and the later forms by new
nuclei. Lee et al (2000) [112] have conducted higher deformation-impact induced martensite
transformation by split-Hopkinson bar technique and found two types of martensite formation.
It was shown that the austenitic grain size [118,119] and dislocation density [27] have influenced
the martensite transformation. In situ high energy XRD is used to study lattice strain and
resultant strain induced martensite transformation in austenitic steels [120,121]. This study
concluded that, formation of strain induced martensite depend on strain rate, and the α’martensite
phase carries more stress than austenite [120,121]. The peak broadening in XRD data for
austenitic phase is related to stepwise transformation events. The vibrating sample magnetometer
(VSM) has been used to quantify strain induced martensite in 304 and 316 types stainless steels
[122–124]. Gilpa et al (2015) [35] have reported volumetric fraction of strain induced martensite
in AISI 304 steels with different Cu (called as 304H, 304N ) wt % as shown in figure 2.14. For
the same equivalent strain, 304N is stable and 304 N has Cu 1. 56 wt % and formed more strain
induced martensite (figure 2.14) [35].
20
Figure 2.14 Vibrating sample magnetometer (VSM) estimated volume fraction of strain-induced
martensite (SIM) of 304N and 304H austenitic stainless steels [35].
2.2.5 Plastic Deformation Models
Plastic deformations in metallic materials proceed by slip and twinning [30,31]. It can be viewed
from crystal plasticity theory [125–128] and microstructural developments [68,98,129,130].
Crystal plasticity focuses on stress equilibrium and strain compatibility. Microstructural
developments involve studying substructures and dislocation theories [68,98,105,131–133].
Sachs model was one of earliest model and it is based on single slip (identical stress state in each
grain) as shown in figure 2.15 a-d. Strain incompatibility at grain boundaries can’t be explained
by this model. Sachs model is also known as lower-bound model [134] .
Taylor model, overcomes this difficulty. It assumes strain homogeneity. It proposes, in
polycrystalline aggregate grains experience iso- strain (same strain state). Polycrystals requires
multiple slip, commonly referred as Taylor model (variable stress state in each grain) as shown
in figure 2.15 e-h. Though Taylor model assumes iso-strain, microstructural studies have proved
presence of heterogeneities [31,68,98,105]. Different grains, experience heterogeneities, and
within grains also [68,135–138].
Taylor model necessitates each grain accommodates an imposed deformation based on
independent slip system. The full-constraint (FC) Taylor model proposed plastic strain of a grain
21
is equal to macroscopic plastic strain of specimen. Bishop and Hill have proposed stress- based
procedure to find active slip system based on assumption of iso-strain.
Deformation texture prediction based on above said Taylor model agrees well with the
experiment. However, the Taylor hypothesis violates stress equilibrium at grain boundaries.
Hence relaxed constraint (RC) Taylor models were proposed.
The classical Taylor models (FC or RC models) treat grains separately and interactions between
grainis not considered. The Lamel model [106,139] and advanced Lamel (Alamel) [106,107]
model consider two grains sharing common boundary. Lamel and Alamel models assume grain
boundaries parallel with rolling plane. Hence Lamel model can be applied for simulating rolling
deformation.
Grain interaction (GIA) model is based on cluster of grains arranged in a brick shaped volume.
Like Lamel model, GIA is designed for rolling simulations and not for general deformations
[106]
FE method is used to solve boundary value problems in continua. In FEM model grains
interactions was considered by employing constitutive equations in FEM code. Crystal plasticity
finite element method (CPFEM) considers short and long range grain interactions. CPFEM
tackles anisotropic micromechanical problems and it can combine variety of mechanical effects
[140]. Plastic deformation mechanism such as slip, twinning and phase transformation and non-
crystallographic banding can be incorporated in CPFEM [141]. CPFEM is time demanding.
Fast Fourier transformation based crystal plasticity (CPFFT) [142] was introduced as an
alternative to FE methods. CPFFT is a spectral method operates in Fourier space, considered to
be very efficient compared to FE methods due to repetitive use of fast Fourier transform (FET).
Compared with CPFEM, CPFFT methods is less popular due to requirement of periodic micro
structural aspects. Proper use of application/selection of deformation texture model is essential.
It is reported that lower magnitude of NBGZ (specimen deformed at uniaxial strain) all models
were predicted well [95]. Alamel and CPFEM models predicted well for higher NBGZ
(specimens deformed at plane strain and biaxial strain) [95].
22
(a) (b) (c) (d)
(e) (f) (g) (h)
Figure 2.15 Plastic deformation models: Sachs model (a-d) [125] and Taylor model (e-h)
[55,143]. Sachs model assumes single slip in each grain. Taylor model assumes many slip in
each grain.
2.3. Localized Corrosion of Stainless Steels: Focus Sensitization
2.3.1 Introduction
The major corrosion issues, associated with standard grades of austenitic SS are shown in figure
2.16. SCC, pitting, and general corrosion are the types of corrosion attack encountered by grades
such as AISI 304 and AISI 316 SS [7,144,145].
23
Sensitization in SS refers to formation of chromium depletion zones adjacent to grain boundaries
due to precipitation of M23C6 carbides [1,146–150]. Formation of chromium depleted zones leads
to loss of passivity at grain boundaries [148,149,151–162]. Precipitation of M23C6 occurs when
SS are exposed in the temperature range of 500 to 800°C [34].
Sensitized austenite SS are susceptible to IGC on subsequent exposure to corrosive environment
[1,2,148,149,152,163]. A schematic representation of grain boundary with a chromium depleted
zone (figure 2.17a) and chromium depletion profiles is shown in figure 2.17b.
Figure 2.16 The corrosion issues (various forms of corrosions) associated with AISI 304 and
316 SS [7]
24
(a) (b)
Figure 2.17 (a) Schematic representation of grain boundary with a chromium depleted zone. (b)
chromium depletion profiles [164]
2.3.2 Mechanism of Sensitization
The mechanism of sensitization can be explained by chromium depletion theory [148], In 1930’s
chromium depletion theory was introduced by Strauss et al (1930) [165] and furthered by Bain
et al.(1933) [166]. Hence the process of carbide precipitation (M23C6 type carbides) at the
interfaces is to be avoided [163,167,168]. Chromium depletion theory is based on formation of
M23C6 rich precipitates that form at interfaces and resultant chromium depletion. This causes Cr
level below 12 wt %, large potential difference exists between interfaces that lowers the stability
of passive film at/around depleted regions [149].Three parameters that define degree of
sensitization (DoS) are length, width and depth of chromium depletion zones [169].
2.3.3 Mitigation Measures
Sensitization can be mitigated by lowering carbon content [1,149,170,171], adding stabilizer
(titanium, niobium) [172], and by solution-annealing treatement [173]. It has been reported that
25
Cerium addition upto 0.01 wt % showed resistance to sensitization [174]. Effect of grain size on
controlling sensitization has also been established [171,175].
Grain boundary engineering (GBE) [176–187] is a process of increasing special boundaries by
series of thermo-mechanical treatment. Metallurgical reactions such as precipitation and
segregation at grain boundaries depends on energy /types of grain boundaries. Grain boundaries
can be classified as low and high angle boundaries, based upon misorientation [31,180]. It is
reported that, and widely accepted that, low angle boundaries (with misorientation less than 15º)
are comparatively more resistant to segregation and precipitation [31,180]. Figure 2.18 shows
that grain boundary network consists of twin boundaries, and low energy grain boundary
segments. High angle grain boundaries further, classified special and random grain boundaries.
Geometric models are used to characterize grain boundary structures.
Figure 2.18 Electron backscattered scanning image shows different types of immunity
of grain boundaries to sensitization in austenitic SS [164]
Special boundaries can be considered as coincident site lattice (CSL) boundaries, defined as two
grains share a common lattice points. It is denoted by Σ, refers to reciprocal density of common
lattice points, e.g. Σ3 special boundary has 1 in 3 atoms share common lattice site, within a
stipulated deviation angle (Brandon’s criterion) [31,188]. In GBE, the materials property have
been reported to be improved by manipulating CSL boundaries [176,182,185,187,189–192].
26
2.3.4 Evaluating Degree of Sensitization
Sensitization is normally assessed, qualitatively, by ASTM A262 Practice A. It involves electro-
etching of specimen in 10% oxalic acid. The etched-microstructure can be classified as ‘step’
(absence of attack at grain boundaries), dual (no single grain is completely attacked), ditch (at
least one grain is attacked) [193]. Attacked regions at grain boundaries appear darker than
matrix. For ‘ditch’ structure, further evaluation is essential as per other tests mentioned in ASTM
A262 (table 2.2). Electrochemical potentiokinetic reactivation (EPR) test quantifies the extent of
sensitization in SS. The extent of sensitization is usually termed as the degree of sensitization
(DoS) [194–197]. The EPR test can be done in either Single loop [198] or double loop [195]
mode. In single loop EPR tests, first the specimen is passivated at +0.2 V first as shown in figure
2.19 after attainment of stable Open circuit potential (OCP). After holding at constant
passivation potential (+0.2 V), potential is scanned back to at the scan rate of 6 V/h. Double loop
EPR generates an anodic loop and reactivation loop as shown in figure 2.20 the current values at
each loop (anodic scan and reverse scan) DoS. Further, it is reported recently that thermoelectric
power (TEP) technique has been successfully applied to measure degree of sensitization [199].
Figure 2.19 Schematic illustrating the procedure of single loop EPR test [198]
27
Figure 2.20 Schematic illustrating the procedure to calculate ratio of DoS from anodic
and reverse currents from double loop EPR test [195]
2.3.5 Effect of Cold Working on Sensitization of Stainless Steels
Cold-work introduces dislocations and strain-induced martensite [30]. The presence of such
microstructural features affect susceptibility to sensitization [151,200]. At low degree of cold
work, carbides start to nucleate at grain boundary and at higher degree of cold work, nucleation
of carbides occurs at grain interior [151,200]. Further cold working increase the dislocation
density in the matrix, hence, precipitation can takes place within the matrix. Some researchers
have experimentally shown that beneficial effect of low/threshold level of cold work improved
the resistance to sensitization [182]. The deformation prior to sensitization, increases the chance
for carbide nucleation [200].
Contradictions exists regarding the exact role of deformation in affecting sensitization [201].
Mode and types of deformation such as uniaxial tensile, compressive loading, cross rolling, and
unidirectional rolling influence sensitization. Several reports that indicates, lower degree of
deformation of SS has deteriorated resistance to sensitization and higher deformation of SS has
improved resistance to sensitization. Hence there is disagreements among the researchers about
exact role of deformation on sensitization [202]. Precipitation of M23C6 do not occur at coherent
twin boundaries [186,203,204]. Time-temperature precipitation diagram suggests delayed M23C6
precipitation at twin boundaries as shown in figure 2.21 in 304 stainless steels [205].
28
Table 2.2 Typical IGC tests for austenitic stainless steels [149,193]
Name of ASTM
standard tests
Test solution Exposure Evaluation
technique
Species
attacked
A393 Strauss 15.7%
H2SO4+5.7%CuSO4
boiling ambience
72 h
exposure
is needed
Examined
after
bending
Chromium
depletion
A262 Practice A
(Oxalic acid etch )
10% H2C2O4 room
temperature
1.5 min Type of
attack (step,
dual, ditch)
Chromium
depletion
A262 Practice B 50% H2SO4+2.5%
Fe2(SO4)3 boiling
ambience
120 h Weight loss
per unit area
Sigma
phase and
chromium
depleted
area
A262 Practice C
(Huey)
65% HNO3 boiling
ambience
48 h Average
weight loss
per unit area
Sigma
phase and
chromium
depleted
area
A262 Practice D 10% HNO3+3%HF,
70ºC
2 h Weight loss
per unit area
Sigma
phase and
chromium
depleted
area
A262 Practice E
(Copper accelerated
Strauss)
15.7% H2SO4 +
5.7%CuSO4, contact
with copper boiling
ambience
24 h Appearance
after
bending
Chromium
depletion
at carbides
A262 Practice F H2SO4+CuSO4 24 h Weight loss Carbides
29
Grain boundary connectivity [206–210] determines Cr flux and hence affect the extent of
sensitization [182–184,210,211]. Thus presence and continuity of special boundaries affect
DoS.Kim and his co-workers (2011) have experimentally proved that absence of chromium
depleted zone by segregation of un-reacted Cr atoms [212]. Another investigation addressed
effects of pre-strain annealing on grain boundary character distribution (GBCD) [182]. This
study reported slight-pre strain annealing due to optimized GBCD enhanced IGC resistance. The
effects of cold-rolling (upto 60%) on DoS were reported and shown that improvement in
resistance to IGC in 5% cold rolled specimens followed by strain-annealing that increased the
CSL frequency (figure 2.22) [182]. The concept of effective grain boundary energy (EGBE)
have emerged in 2002 [183]. Its influence on DoS was reported for austenitic SS [183] and
established the chemistry dependence of EGBE. 0.521 wt % of copper have been reported to be
improved resistance to DoS as shown in figure 2.23 [206]. Parvathavarthimi et al (2009) [206]
have experimentally proved the relationship between the various microstructural parameter
(grain size, grain boundary nature, EGBE, and DoS (figure 2.23).
Figure 2.21 Time-temperature curves of M23C6 precipitation behavior observed in 304 SS
[205]
30
(a) (b)
Figure 2.22 The effect of cold rolling on DoS. (a) after sensitization heat treatment for 1h and 5h
and (b) 1h [182]
(a) (b)
Figure 2.23 Effect of EGBE on DoS of 316L(N) stainless steels with (a) 0.0829 and (b) 0.52 wt
% of Cu [206]
Effect of Strain-Induced Martensite on Sensitization
It is known that plastic deformation of austenitic SS produce strain induced martensite that
affects kinetics of sensitization [213]. Diffusion of carbon and chromium is much faster in strain-
induced martensite than austenite [37,214]. It has been reported that, specimens deformed by
31
cold rolling process, sensitize faster than by tensile testing process [215,216]. Cold rolled steels
with martensite content caused rapid sensitization at temperature below 600°C and produced
rapid healing [34,37,214]. Rapid healing is desensitization-kinetics due to presence of strain-
induced martensite. It is further reported that rapid healing is not possible without the presence of
martensite [37]. It has been reported that, strain-induced martensite does not recover at 575ºC for
specimens with 30% and 40% pre-strain [216].
Takahashi et al (2001) reported [217] full recovery of strain-induced martensite at 425ºC in 304
stainless steels. At lower temperatures, it has been reported that presence of strain-induced
martensite lead to rapid sensitization [34,218]. Further, presence of strain-induced martensite is
responsible for transgranular stress corrosion cracking [202], and hydrogen assisted cracking
[218].
Ma et al (2005) [219] have reported that complete recovery of strain-induced martensite at 75%
cold rolling was annealing at 640°C for 10 min. It has been shown that retained martensite
affects DoS and passive films [219] .
It is possible to differentiate from DL-EPR curves to distinguish classical and martensite induced
sensitization [34,197]. It has been shown that the presence of martensite in deformed austenitic
SS can lead to precipitation on martensitic regions within the matrix [34,197]. Sensitization of
martensite phase can be detected by hump in the DL-EPR curves [34,197]. Kain et al (2005)
[197] have indicated presence of intragranular martensite induced sensitization.
2.4. Passivation Behavior of Stainless Steels
2.4.1 Introduction
Austenitic SS form thin, adherent, and a few nanometer thick Cr2O3-rich passive film [153].
Austenitic SS are susceptible to localized corrosion, e.g. pitting corrosion, due to breakdown of
passive film in localized regions [220,221]. The presence of aggressive anions, typically halide
ions, aggravate localized attack on passive film on austenitic SS [221,222]. The integrity of
passive film is also affected by microstructural inhomogeneity [153,223,224]. The characteristics
of passive film is largely governed by ionic and electronic transport processes [225–228].
32
The passivity is affected by parameters such as chemical composition of the material, potential
developed in a given environment, and service temperature [225,229–233]. Passive film
formation, stability, thickness, stoichiometry, microstructure, and electronic properties have been
widely investigated [230–232]. Pitting corrosion is stochastic in nature. It includes various stages
such as breakdown of passive film, growth of metastable and stable pits [221,222]. Pitting
corrosion can be studied using anodic potentiodynamic polarization test [234–239]. Typical
anodic potentiodynamic polarization curve consist of active, passive, and transpassive regions as
shown in figure 2.24. The current density is generally low in passive state. As shown in figure
2.24, passive film can breakdown at potential called pitting potential (Epit), when there is no
repassivation above Epass. Above Epit, breakdown of passivity leads to pitting.
Characterization of Passive Films
Two different approaches to study and characterize passive films are conventional
electrochemical tests [198,239] and analytical spectroscopy techniques [240–243]. The
semiconducting nature of film can be evaluated by Mott-Schottky analysis [216,244–247]. The
semiconducting nature of passive films are usually studied by employing point defect model
(PDM) in different test solution [248,249]. PDM assumes that passive film contains oxygen and
metal cation vacancies. Growth and breakdown passive film depends on migration of vacancies.
Donor density and diffusivity are key parameters that can be determined by employing Mott-
Schottky analysis along with PDM. Typical Mott-Schottky plot for passive films developed at
H2SO4 solution is shown in figure 2.25a [250]. Donor and acceptor density values of passive
films formed in borate buffer solution on 304 austenitic SS at different strains is shown in figure
2.25b [246]. Such densities values were reported to be solution dependent [246,248–250]. In
addition to Mott-Schottky analysis, Taguchi method [251] has been used for studying fracture
load of passive films. Analytical techniques to study passive film characteristics are auger
electron spectroscopy (AES) [240,241,253], secondary ion mass spectroscopy (SIMS) [254–257]
electron spectroscopy for chemical analysis (ESCA) [258–261], and Raman spectroscopy
[242,243,262–264] .
33
Figure 2.24 Typical anodic potentiodynamic polarization curves indicating different anodic
behavior of metallic materials in aqueous solutions [252]
2.4.2 Effect of Plastic Strain on Anodic Polarization Behavior
Anodic potentiodynamic polarization behavior is affected by microstructural changes due to
cold/warm working [113,265,266]. Elayaperumal et al (1972) [113] have studied passive
behaviour in cold rolled 304 and 430 SS in 1N H2SO4. Cold rolled specimens generally shifts
open circuit potential (OCP) more active and increases icrit [113]. icrit is defined as critical current
density to induce passivity. OCP is corrosion potential at which sum of cathodic and anodic
current is zero. Higher values of icrit implies difficulty in achieving passivity [113]. OCP was
shifted to -0.420 VSCE in 68% cold rolled specimens compared to annealed (-0.330 VSCE)
specimens. Anodic potentiostatic polarization curves of cold worked 430 SS (figure 2.26) and
304 SS (figure 2.27) indicated that influence of plastic strain on anodic polarization curves.
It was also reported that formation of passivity is difficult in cold rolled specimens, this is
evident particularly in 50%, and 68% specimens. The values of icrit, to achieve passivity for
annealed and 68% cold rolled specimens are 25 x10-5
A/cm2 and 15 x10
-3 A/cm
2 respectively.
34
(a) (b)
Figure 2.25 (a) Mott-Schottky plots [250] and (b) The dependence of semiconducting
parameters (ND and NA) on the film with strain [246]
Figure 2.26 Anodic potentiostatic polarization curves of annealed and cold worked 430 SS
[113]
35
A thicker passive film was reported in 66% cold worked 304 steels compared to solution
annealed (1100°C for 0.5h followed by water quenching) in 3.5 % NaCl test solutions [114]. It
was attributed to higher Cr:Fe ratio in cold worked specimen. Epit values of 66% cold worked
and solution annealed specimens are 0.25 VSCE and 0.06 VSCE respectively [114]. Mudali et al
(1999) [267] had studied the effect of nitrogen additions on 316L SS in various test solutions. It
is reported that resistance to pitting corrosion has improved when nitrogen content is increased
from 0.015 to 0.56 wt% in 1N H2SO4, 0.5M NaCl, and 1N H2SO4+0.5M NaCl; nitrogen addition
had increased the value of Epit. As the temperature increases, the Epit value decreased in these SS
[267]. Pitting potential, Epit, was determined in 304 and 317 SS having varying amount of
hydrogen in another research work [268]. In general, the addition of nitrogen improved the
pitting corrosion resistance in 0.5M NaCl + 0.5M H2SO4. Pitting potentials of 304 SS with 860
ppm nitrogen was higher than with 180 ppm nitrogen.
Figure 2.27 Anodic potentiostatic polarization curves of cold worked at 27ºC and -196ºC on 304
stainless steels [113]
The improvement in pitting corrosion resistance were reported in 316 and 317 SS and attributed
to synergetic effect of molybdenum and nitrogen additions. Thus changes of Epit values with
nitrogen content is found by nitrogen equivalent for molybdenum. The preferred site for pitting
attack was observed at triple points, grain boundaries, inclusions, and inclusion/matrix interface
36
[268] . Another study had reported nitrogen additions upto 20% is beneficial [269]. Beyond 20%
cold rolled, addition of nitrogen was not beneficial in improving resistance to pitting corrosion
[269]. Figure 2.28a shows critical pitting potential values for cold rolled 316 SS, and figure
2.28b-d revealed TEM and SEM images of high density of deformation bands.
It is worth noting that, values of Epit is influenced by scan rate during anodic potentiodynamic
polarization test. To overcome this, Yi et al. (2013) [239] have proposed a new parameter called
‘cumulative electric charge density’ indicating pitting resistance during anodic potentiodynamic
polarization test.
Kumar et al (2007) [270] have studied the effect of cold rolling on anodic potentiodynamic
polarization behavior in 304L SS with interpass cooling, without interpass cooling, and subzero
temperatures on anodic potentiodynamic polarization test in 1N H2SO4. The OCP became more
active with increasing cold rolled in both interpass colling and without interpass cooling. Epp
(primary passive potential) have remained same for cold rolled specimens irrespective of
interpass cooling and without interpass cooling. The values of ip (passive current)is increasing up
to 50% cold rolled this indicated, with increasing deformation, tendency for passive film
formation is difficult. This is in agreement with previous studies [113]. An improvement in
pitting resistance is reported at 70% and 90% cold rolled specimens in 1N H2SO4 in both
interpass colling and without interpass cooling. In general, lower values of anodic
potentiodynamic polarization parameter (Epp, ip) exhibits quicker passive film.
37
(a) (b)
(c) (d)
Figure 2.28 (a) Critical pitting potential values for cold rolled alloys, (b) TEM images revealing
high density of narrow and sharper deformation bands. (c) SEM of 40% cold rolled specimen
revealed high density of deformation bands and (d) scarcely distributed bands [269].
formation. Epit was determined in another work on laboratory grade 304 SS as a function of cold
work in the test solution of 0.5 M NaCl having pH value of 6.6 at 23°C temperature [271,272].
38
Effect of Strain-Induced Martensite on Anodic Polarization Behavior
Plastic deformation of austenitic SS leads to formation of strain-induced martensite
[27,31,33,41,60,117,273] and it affects electrochemical behavior [40,113,274–279]. It is reported
that, passive film is weakened [266,276,280] and unaffected [281] and strengthened [114,282]
due to cold working.
It is also reported that, there is no change of active dissolution behavior in 50% cold rolled
specimens of 430 ferritic SS in 1N H2SO4 test solution (figure 2.26), due to absence of strain-
induced martensite [113]. Anodic potentiodynamic polarization curves of annealed and 50% cold
rolled ferritic SS have exhibited similar trend. The strain-induced martensite formed due to cold
work in 304 steels influence the anodic polarization curves (figure 2.27) [113]. In contrast, in
another study on deformed 430 ferritic SS, metastable pits were observed [271,272].
There have been numerous studies that suggested poor corrosion performance due to strain-
induced martensite [113,271,272,283,284]. Electrochemical measurements, have indicated that
deformation leading to strain induced martensite reduce corrosion performance due to selective
dissolution of martensite [40,113,285]. In contrast, it is reported that absolute amount of strain-
induced martensite has no influence and sophisticated smaller scale analysis is needed to study
effect of strain induced martensite on passive film stability [271]. Further, recent studies have
suggested that, corrosion performance depend on grain size, and distribution of strain induced
martensite [40]. The beneficial effect of strain-induced martensite was realized with sub-micron
grain size [283]. Piling up of dislocations and strain-induced martensite affect pitting corrosion
[271,272].
2.4.3 Effect of Alloying Elements on Passivity
Alloying additions to SS such as Cr, Mo enhances passivation behavior [149]. The cost is
important in materials selection and alloying addition [144,145]. The plot of material cost and
corrosion resistance suggests, for aggressive environments higher alloying additions such as
Sanicro 28 (27% Cr, 31% Ni, 3.5% Mo) is preferred because of superior corrosion performance
(figure.2.29)
39
The effect of alloying elements on anodic potentiodynamic polarization curve is shown in figure
2.30. The most alloying elements affecting passivity are chromium, molybdenum, nitrogen, also,
the synergetic effect of alloying additions/ sulphide inclusions have been detailed [286,287].
Role of nitrogen, copper, molybdenum have attracted special attention and there has been plenty
of discussion on their beneficial effect in the literature [288–292]. Alloying Ni, Mo, and N to
high Cr (more than 18 wt %) containing steels can make it resistant for pitting corrosion.
However, there has been many instances even these steels are susceptible to pitting corrosion in
strong acidic test solution at elevated temperatures [293,294].
Figure 2.29 Price variations of steel grades with respect to corrosion resistance [144]
Manganese sulfide (MnS) inclusions often initiate pitting in SS [295]. In this study [295], to
establish MnS behavior on pitting corrosion two steels were selected, high purity 316 SS and
commercial 316 SS. Anodic potentiodynamic polarization test performed on as-polished SS
specimens, metastable pitting event is observed in commercial 316 SS and no such current spikes
is observed in high purity steels, this clearly indicates formation of passivation [295].
40
Figure 2.30 Effect of alloying elements on anodic potentiodynamic polarization curves
in stainless steels [149]
SEM and energy dispersive X-ray spectrometer (EDS) images revealed 5-10 microns round
shaped inclusions of CaO, SiO2, Al2O3 in as-polished commercial SS. Such inclusion is not
found on the surface of high purity SS. Beneficial effects on addition of Mo due to formation of
improved oxide films bonds [39] in (54Fe-21.7Cr-17.3Ni3.6Mo&65Fe-18.7Cr-11.2Ni-1.7Mo)
SS. In another work by Hashimoto et al (1979) is due to Molybdates formation that removes the
active sites [258] . Further, Sugimoto and Sawada (1977) [288] have showed direct correlation of
improvement in passive film thickness with increase in Mo content. The appearance of second
anodic peaks in stainless steels (particularly in H2SO4) has been studied by different parameters
[286,287]. These parameters are immersion time before anodic potentiodynamic polarization
experiment, acidity of test solution, cathodic pre polarization in anodic potentiodynamic
polarization test. The second anodic peak was attributed to nickel content [296].
41
2.5 Introduction to Machining and Residual Stress: Focus Austenitic
Stainless Steels with Corrosion Perspective
2.5.1 Introduction to Machining
The susceptibility of austenitic SS to localized corrosion such as passivity breakdown, pitting
corrosion, and SCC. The susceptibility of austenitic SS depends on, among other things, surface
conditions that include surface roughness, residual stress, and sub-surface microstructure.
[297,298]. Hence, surface modifications due to machining play a major role on breakdown of
passive films thus increases susceptibility to pitting and SCC [299–302]. Sub-surface
microstructural developments also affects nature and stability of the chromium oxide film in
austenitic SS [297,303].
Mechanical working (turning, grinding, superfinishing, drilling, tapping, sawing) of any metallic
materials increases in surface roughness [304,305], defect density [306], development of residual
stresses/strains[307,308] and phase transformations [308,309]. This affects localized corrosion
behavior, particularly, SCC [298,300,301,304,310]. Austenitic SS components during fabrication
undergo machining. This can be achieved by conventional techniques and modern high speed
machines.
The major drawback of conventional machining is that magnitude of localized overheating at
shear zones and residual stresses developments during machining operations. This can be better
controlled by high speed machining (HSM) [311–313] and electrochemical machining (ECM)
[314–317]. HSM enables cutting of metals and alloys at higher cutting speeds and feeds and
recently, there has been lot of interest in machining at very high speeds. High speed steel cutters
with or without carbide inserts are used in milling of SS. Generally higher cutting speed,
smoother the finish [318].
Effect of Machining on Corrosion
Surface machining of austenitic SS has resulted in grain refinement [301], strain-induced
martensite [301,319] and introduction of residual stress [320] that influence corrosive attack
[298,300,321]. Presence of strain- induced martensite has increased the susceptibility of
42
corrosive attack [301] and increase work hardening [322] and formation of hydrogen induced
cracks [319] in austenitic SS.
Ghosh et al (2010) [301] have reported presence of strain-induced martensite in specimens of
304L SS near machined surfaces. It was also reported that, its presence has increased the
susceptibility to SCC. In an another study by Turnbull et al (2011)[300], SCC and pitting
corrosion was also reported in ground and milled specimens of 304 specimens, and the presence
of strain induced martensite was not studied/reported [300]. Hence combined effect of heavy
plastic deformation and generation of residual stress in machined layer is detrimental for SCC.
In general, higher surface roughness reduce the incidence of pitting, due to higher number of
availability of vulnerable sites [297,304,323] and interestingly, it is reported that pits are readily
occur at smoother surface in fine ground 316L SS [310]. The metastable pitting behavior in 316L
SS having different surface roughness has been explored [304]. Faller et al (2005) have reported
difference in electrochemical behavior depends on surface finish [324]. Rhouma et al (2001)
have showed beneficial aspect of surfaces having compressive residual stress [325].
EBSD has been used to characterize machined layer (near surface microstructure) [300,301].This
layer consist of severely distorted grains and/or nanocrystalline structure. Transgranular SCC has
been reported in machined 304 SS specimens after boiling MgCl2 test [301]. Atomic force
microscopy (AFM) and depth profile analysis have revealed SCC path in direction of slip and
cracks were deeper than slip bands respectively [298].
Lyon et al (2015) has studied influence of milling on SCC in 316Ti SS [302]. In this study [302]
primary and secondary cracks were reported due to stress corrosion. Primary cracks were aligned
with milling direction and secondary cracks were orthogonal to primary cracks. Zhang et al
(2016) studied machining induced residual stress on initiation of SCC in boiling MgCl2 test
[320]. Presence of tensile residual stress can result in initiation of SCC micro-cracks and depends
on critical value of tensile residual stress. 190MPa of tensile residual stress was reported for 316
austenitic SS [320].
43
2.5.2 Residual Stress: Definition and Origin
Introduction
Residual stress is an unrecovered stress that remains in body after the removal of external
loading during fabrication of materials [326]. It is rarely studied through typical microstructural
approach [31]. Failures in materials (ductile and brittle fractures, fatigue failures and creep) can
be significantly influenced by residual stress [327,328]. It is important to know its origin and
state in predicting the performance of many engineering components [326]. The origin of
residual stress can be explained by ‘misfit’ [31,326,329]. Misfits can be introduced during
engineering process as shown in figure 2.31.
Classification
Residual stress is classified broadly into macro and micro stress [31,326]. Further, it can also be
differentiated based on nature in which they arise [326], scale [330], behavior [331]. Type I or
macro residual stress shows large variation in the body of the component than the grain size
Figure 2.31 Schematic of different types of residual stresses. The processes, origin (residual
stress arise from misfit) and residual stress patterns are included for each condition [327].
44
of the system and type II and type III are micro residual stress, different individual grains exhibit
different value, and type III are due to presence of dislocations and other crystal defects. Type III
residual stress is at atomic level. Different types of macro and micro residual stress in each
process also included schematically in left, the misfits for each process on centre and final
residual stress pattern on right as shown in figure 2.31.
2.5.3 Measurement Techniques
Different methods (destructive, semi destructive and non-destructive) are adopted for quantifying
residual stress as shown in figure 2.32 [328]. Destructive and semi destructive are called
mechanical methods inferring origin of residual stress from complete or partial displacement
[332]. Non-destructive makes use of x-ray or neutron diffraction methods and ultrasonic methods
[333,334].
Figure 2.32 Classification of different residual stress measurement methods [328]
45
The measurement of residual stress, depend on the interaction between x-ray beam and crystal
lattice, change in lattice spacing is calculated and converted to stress. Measurement of change in
interplanar spacing (d) is shown in figure 2.33. When tensile stress/strain is applied, the shift in
diffraction is recorded (figure 2.33c). Diffraction occurs when Bragg’s law is satisfied. Spacing
between planes of atom (d) is calculated by using Bragg’s law (equation 2.5). The Bragg’s law
details XRD residual stress measurements, changes in interplananr spacing ‘d’ due to stress or
other process/treatments, for detecting strain ε [329,330,332,334–336] (equation 2.6) .
(2.5)
ε (2.6)
Hooke’s law states that, (equation 2.7)
σij= Eijkl εkl (2.7)
where λ,θ,σij,Eijkl,εkl d1,d0 are radiation wave length, half the Bragg angle, elastic stress, elastic
modulus of materials property, strain and interplanar spacing of stressed and unstressed
specimens respectively. If elastic modulus of materials property (Eijkl) is known, the stress (σij)
can be determined
(a) (b) (c)
Figure 2.33 (a) strain free lattice (b) change in ‘d’ due to application of tensile stress
horizontally (c) position of Bragg peaks with and without application of tensile stress after
diffraction [336]
46
2.5.4 Effect of Residual Stress on Corrosion
Residual stresses can be generated by machining of SS. Nature of residual stress are depend on
hardness of materials. Tensile and compressive residual stresses develop for softer materials and
harder materials [302,337] There is a limited number of studies reported on the role of residual
stress on passivation behavior of SS [320,338,339]. Nature (tensile or compressive) of residual
stress, magnitude and surface conditions have reported to affect passive films [338]. Residual
stress affect localized corrosion due to introduction of active anodic sites [216,340]. Elemental
Auger depth profiles was employed in this to arrive at inference that the tensile stressed surface
was richer in oxygen [338]. Thicker passive layer was observed in specimens surface after
tensile testing in 316 SS [339]. The chemical composition of passive film was studied in an
another study [341]. Passivity breakdown was studied in 316 SS [342]. In this study, residual
tensile stress has generated vacancies into the passive film [342].
Lyon et al (2015) [302] has studied effect of surface finishing on development of residual stress
and SCC in stabilized grades of 316 SS. Milling of stabilized 316 SS had resulted biaxial tensile
stress and formation of primary and secondary SCC depends on machining direction [302].
Pitting has occurred in specimens having lower surface roughness due to presence of higher
tensile residual stresses [300]. In a recent study Turnbull et al (2011) [300] showed introduction
of residual stress depends on orientation.
References
[1] P.Marshall, Austenitic Stainless Steels Microstructure and Mechanical Properties, first ed.,
Elsevier applied science publishers, England, 1984.
[2] G.George, H.Shaikh, Introduction to austenitic stainless steels, in: H.S. Khatak, B. Raj
(Eds.), Corros. Austenitic Stainl. Steels Mech. Mitig. Monit., Woodhead Publishing
limited, India, 2002: pp. 1–36.
[3] A.K.Sinha, C.Wu, G.Liu, Steel nomenclature, in: G.E.Totten (Eds.) Steel Heat Treatment:
Metallurgy and Technologies, second ed., CRC press, 2007: pp. 1–90.
[4] E.Trent, P. Wright, Metal cutting, fourth ed., Butterworth Heinemann, USA, 2000.
[5] H.M.Cobb, The history of stainless steel, first ed., ASM International, USA, 2010.
47
[6] J.R.Davies, eds., ASM Speciality Handbook Stainless Steels, first ed., ASM International,
USA,1994.
[7] B.Larsson, U.Lundell, S.Bukovinsky, Special stainless steels for the process industry,
Mater. Des. 6 (1985) 306–312.
[8] ASM International, Chapter 6: Austenitic Stainless Steels, Stainl. Steels Des. Eng. (2008)
69–78.
[9] P.J.Ennis, 7 Ferritic and martensitic steels for power plants, in: A. Shirzadi, S. Jackson
(Eds.), Structural Alloys for Power Plants, Woodhead Publishing limited, 2014: pp. 188–
220.
[10] M.Cortie, Ferritic Stainless Steels, Encyclopedia of Materials: Science and Technology
(2001) 1–3.
[11] H.D.Solomon, Stainless Steels: Duplex, Encyclopedia of Materials: Science and
Technology (2001) 1–3.
[12] T.Angel, Formation of martensite in austenitic stainless steels: effects of deformation,
temparature, and composition, J. Iron Steel Inst. 177 (1954) 165–174.
[13] G.B.Olson, M.Cohen, A general mechanism of martensitic nucleation: Part II. FCC →
BCC and other martensitic transformations, Metall. Trans. A. 7 (1976) 1905–1914.
[14] D.C.Cook, Strain induced martensite formation in stainless steel, Metall. Trans. A. 18
(1987) 201–210.
[15] V.Shrinivas, S.K.Varma, L.E.Murr, Deformation-induced martensitic characteristics in
304 and 316 stainless steels during room-temperature rolling, Metall. Mater. Trans. A. 26
(1995) 661–671.
[16] J.Talonen, H.Hänninen, Formation of shear bands and strain-induced martensite during
plastic deformation of metastable austenitic stainless steels, Acta Mater. 55 (2007) 6108–
6118.
[17] T.S.Byun, On the stress dependence of partial dislocation separation and deformation
microstructure in austenitic stainless steels, Acta Mater. 51 (2003) 3063–3071.
[18] X.F.Fang, W.Dahl, Strain hardening and transformation mechanism of deformation
induced martensite transformation in metastable austenitic stainless steels, Mat.
Sci.Eng.A. 141 (1991) 189–198.
[19] D.Talbot, J.Talbot, Chapter 8 Stainless steels, first ed., Corrosion Science and
Technology, CRC press, USA 1998
48
[20] J.O.Nilsson, Super duplex stainless steels, Mater. Sci. Technol. 8 (1992) 685–700.
[21] Ferritic Stainless Steels Sheet, Coil & Plate Providing Solutions in Specialty Metals,
(n.d.).
[22] J.Dash, H.M.Otte, The martensite transformation in stainless steel, Acta Metall. 11 (1963)
1169–1178.
[23] J.S.Bowles, J.K.Mackenzie, The crystallography of martensite transformations, Acta
Metall. 2 (1954) 129–137.
[24] C.M.Wayman, Crystallographic theories of martensitic transformations, J. Less Common
Met. 28 (1972) 97–105.
[25] Q.X.Dai, X.N.Cheng, Y.T.Zhao, X.M.Luo, Z.Z.Yuan, Design of martensite
transformation temperature by calculation for austenitic steels, Mater. Charact. 52
(2004) 349–354.
[26] L.Bracke, L.Kestens, J.Penning, Transformation mechanism of alpha martensite in an
austenitic Fe-Mn-C-N alloy, Scr. Mater. 57 (2007) 385–388.
[27] K.Spencer, J.D.Embury, K.T.Conlon, M.Véron, Y.Bréchet, Strengthening via the
formation of strain-induced martensite in stainless steels, Mat. Sci.Eng.A. 387-389 (2004)
873–881.
[28] R.E.Schramm, R.P.Reed, Stacking fault energies of seven commercial austenitic stainless
steels, Metall. Trans. A. 6 (1975) 1345–1351.
[29] C.G.Rhodes, A.W.Thompson, The composition dependence of stacking fault energy in
austenitic stainless steels, Metall. Trans. A. 8 (1977) 1901–1906.
[30] G.E.Dieter, Metallurgical Metallurgy, first ed., McGraw Hill Book Company, USA,1961.
[31] B.Verlinden, J.Driver, I.Samajdar, R.D.Doherty, Thermo Mechanical Processing of
Metallic Materials, first ed., Pergamon Materials Series, Great Briton, 2007.
[32] V.Seetharaman, R.Krishnan, Influence of the martensitic transformation on the
deformation behaviour of an AISI 316 stainless steel at low temperatures, J. Mater. Sci. 16
(1981) 523–530.
[33] V.Seetharaman, Deformation and martensitic transformation, Bull. Mater. Sci. 6 (1984)
703–716.
[34] V.Kain, K.Chandra, K.N.Adhe, P.K.De, Effect of cold work on low-temperature
sensitization behaviour of austenitic stainless steels, J.Nucl.Mater. 334 (2004) 115–132.
49
[35] L.C.M. Gilapa, C.A.S.de Oliveira, M.R.da Silva, Effect of copper on the formation of
strain-induced martensite in two austenitic stainless steels AISI 304, Mater. Sci. Eng. A.
622 (2015) 212–218.
[36] J.Talonen, P.Nenonen, G.Pape, H.Hänninen, Effect of strain rate on the strain-induced
austenite-martensite transformation and mechanical properties of austenitic stainless
steels, Metall. Mater. Trans. A. 36 (2005) 421–432.
[37] C.L.Briant, A.M.Ritter, The effects of deformation induced martensite on the sensitization
of austenitic stainless steels, Metall. Trans. A. 11 (1980) 2009–2017.
[38] E.P.Butler, M.G.Burke, Chromium depletion and martensite formation at grain boundaries
in sensitised austenitic stainless steels, Acta Metall. 34 (1986) 557–570.
[39] C.Alvarez, E.Almanza, L.Murr, Evaluation of the sensitization process in 304 stainless
steel strained 50% by cold-rolling, J. Mater. Sci. 40 (2005) 2965–2969.
[40] S.M.Alvarez, A. Bautista, F. Velasco, Influence of strain-induced martensite in the anodic
dissolution of austenitic stainless steels in acid medium, Corros. Sci. 69 (2013) 130–138.
[41] G.B.Olson, M.Cohen, A mechanism for the strain-induced nucleation of martensitic
transformations, J. Less Common Met. 28 (1972) 107–118.
[42] G.F.Bolling, R.H.Richman, The influence of stress on martensite-start temperatures in Fe-
Ni-C alloys, Scr. Metall. 4 (1970) 539–543.
[43] G.F.Bolling, R.H.Richman, The plastic deformation-transformation of paramagnetic f.c.c.
Fe-Ni-C alloys, Acta Metall. 18 (1970) 673–681.
[44] W.Callister, D.Rethwisch, Materials science and engineering: an introduction, 2007.
[45] I.J.Beyerlein, X.Zhang, A.Misra, Growth Twins and Deformation Twins in Metals, Annu.
Rev. Mater. Res. 44 (2014) 329–363.
[46] J.W.Simmons, Over view: High nitrogen alloying of stainless steels, Mater. Sci. Eng. A.
207 (1996).
[47] P.Müllner, C. Solenthaler, P. Uggowitzer, M.O. Speidel, On the effect of nitrogen on the
dislocation structure of austenitic stainless steel, Mater. Sci. Eng. A. 164 (1993) 164–169.
[48] J.A.Venables, Deformation twinning in face-centred cubic metals, Philos. Mag. 6 (1961)
379–396.
[49] R.E.Reed-Hill, R. Abbaschian, Physical metallurgy principles, PWS Publishing company,
Boston, 1991.
50
[50] T.H.Courtney, Mechanical behavior of materials, Mc Graw Hill, Boston, 2000.
[51] C.N. Reid, W.S. Owen, Deformation geometry for materials scientists, Pergamon Press,
Hungary, 1973.
[52] W.F.Hosford, Physical Metallurgy, in: CRC press, 2010.
[53] M.J.Marcinkowski, H.A.Lipsitt, The plastic deformation of chromium at low
temperatures, Acta Metall. 10 (1962) 95–111.
[54] M.A.Meyers, O.Vöhringer, V.A.Lubarda, The onset of twinning in metals: A constitutive
description, Acta Mater. 49 (2001) 4025–4039.
[55] G.I. Taylor, Plastic strain in metals, Inst. Met. (1938) 307–325.
[56] G.T.Gray, Deformation twinning in Al-4.8 wt% Mg, Acta Metall. 36 (1988) 1745–1754.
[57] S.Mahajan, D.F.Williams, Deformation Twinning in Metals and Alloys, Int. Metall. Rev.
18 (1973) 43–61.
[58] F.D.Fischer, T.Schaden, F.Appel, H. Clemens, Mechanical twins, their development and
growth, Eur. J. Mech. A/Solids. 22 (2003) 709–726.
[59] D.A.Porter, E.A.Easterling, M.A. Sherif, Phase Transformations in Metals and Alloys,
third ed., CRC press, Noida, 2014.
[60] W.S.Lee, C.F.Lin, Impact properties and microstructure evolution of 304L stainless steel,
Mat.Sci.Eng.A. 308 (2001) 124–135.
[61] J.G.Sevillano, P.Van Houtte, E. Aernoudt, Large strain work hardening and textures, Prog.
Mater. Sci. 25 (1980) 69–134.
[62] A.A.Luo, Recent magnesium alloy development for elevated temperature applications, Int.
Mater. Rev. 49 (2004) 13–30.
[63] D.Kuhlmann-Wilsdorf, N.Hansen, Geometrically necessary, incidental and subgrain
boundaries, Scr. Metall. Mater. 25 (1991) 1557–1562.
[64] N.Hansen, D.J.Jensen, Flow stress anisotropy caused by geometrically necessary
boundaries, Acta Metall. Mater. 40 (1992) 3265–3275.
[65] B.Bay, N.Hansen, D.Kuhlmann-Wilsdorf, Deformation structures in lightly rolled pure
aluminium, Mater. Sci. Eng. A. 113 (1989) 385–397.
[66] N.Hansen, D.Kuhlmann-Wilsdorf, Low energy dislocation structures due to unidirectional
deformation at low temperatures, Mater. Sci. Eng. 81 (1986) 141–161.
51
[67] D.Kuhlmann-Wilsdorf, Theory of plastic deformation:-properties of low energy
dislocation structures, Mat. Sci.Eng.A. 113 (1989) 1–41.
[68] B.Bay, N.Hansen, D.A.Hughes, D.Kuhlmann-Wilsdorf, Evolution of f.c.c. deformation
structures in polyslip, Acta.Metall.Mater. 40 (1992) 205–219.
[69] W.Pantleon, Resolving the geometrically necessary dislocation content by conventional
electron backscattering diffraction, Scr. Mater. 58 (2008) 994–997.
[70] C.T.Young, T.J. Headley, J.L. Lytton, Dislocation substructures formed during the flow
stress recovery of high purity aluminum, Mater. Sci. Eng. 81 (1986) 391–407.
[71] F.Basson, J.H. Driver, Modelling the evolution of geometrically necessary boundaries at
large plastic strains, Mater. Sci. Eng. A. 256 (1998) 243–255.
[72] H.J.Mcqueen, E. Evangelista, M. Cabibbo, G. Avramovic-Cingara, Unified Terminology
for Strain Induced Boundaries, Can. Metall. Quar. 47 (2008) 71–82.
[73] H.J.McQueen, Deformation band formation, characteristics, history, J. Phys. Conf. Ser.
240 (2010) 1–4.
[74] D.A.Hughes, N.Hansen, D.J.Bammann, Geometrically necessary boundaries, incidental
dislocation boundaries and geometrically necessary dislocations, Scr. Mater. 48 (2003)
147–153.
[75] W.Pantleon, On the distribution function of disorientations in dislocation cell structures,
Scr. Mater. 35 (1996) 511–515.
[76] M.E.Gurtin, A gradient theory of single-crystal viscoplasticity that accounts for
geometrically necessary dislocations, J. Mech. Phys. Solids. 50 (2002) 5–32.
[77] H.H.M. Cleveringa, E. Van Der Giessen, A. Needleman, Discrete dislocation analysis of
bending, Int. J. Plast. 15 (1999) 837–868.
[78] M Hirabayashi, S. Weissmann, Study of CuAu I by transmission electron microscopy,
Acta Metall. 10 (1962) 25–36.
[79] G.F.Bolling, R.H. Richman, Continual mechanical twinning: Part I: Formal description,
Acta Metall. 13 (1965) 709–722.
[80] D.G.Brandon, J.Nutting, The metallography of deformed iron, Acta Metall. 7 (1959) 101–
110.
[81] M.Hatherly, A.S.Malin, Deformation of copper and low stacking-fault energy, copper
base alloys, Met. Technol. 6 (1979) 308–319.
52
[82] P.R.Carreker, W.R.Hibbard, J.Metals. 9 (1957) 1157.
[83] W.Boas, G.J.Ogilvie, The plastic deformation of a crystal in a polycrystalline aggregate,
Acta Metall. 2 (1954) 655–659.
[84] M.Hatherly, A.S.Malin, Shear bands in deformed metals, Scripta. Metall. 18 (1984) 449–
454.
[85] Q.Xue, J.F.Bingert, B.L.Henrie, G.T.Gray III, EBSD characterization of dynamic shear
band regions in pre-shocked and as-received 304 stainless steels, Mater. Sci. Eng. A. 473
(2008) 279–289.
[86] Q.Xue, E.K.Cerreta, G.T.Gray, Microstructural characteristics of post-shear localization in
cold-rolled 316L stainless steel, Acta Mater. 55 (2007) 691–704.
[87] M.A.Meyers, Y.B.Xu, Q.Xue, M.T.Pérez-Prado, T.R.McNelley, Microstructural evolution
in adiabatic shear localization in stainless steel, Acta Mater. 51 (2003) 1307–1325.
[88] B.F.Wang, Z.L.Liu, X.Y.Wang, Z.Z. Li, An EBSD investigation on deformation-induced
shear bands in a low nickel austenitic stainless steel under controlled shock-loading
conditions, Mater. Sci. Eng. A. 610 (2014) 301–308.
[89] C.S.Barret, L.H.Levenson, Trans Met. Soc AIME1. 137 (1940) 112.
[90] R.Ørsund, J.Hjelen, E.Nes, Local lattice curvature and deformation heterogeneities in
heavily deformed aluminium, Scr. Metall. 23 (1989) 1193–1197.
[91] D.Raabe, Z.Zhao, S.J.Park, F.Roters, Theory of orientation gradients in plastically
strained crystals, Acta. Mater. 50 (2002) 421–440.
[92] D.P.Field, P.B.Trivedi, S.I.Wright, M.Kumar, Analysis of local orientation gradients in
deformed single crystals, Ultramicroscopy. 103 (2005) 33–39.
[93] N.Keskar, S.Mukherjee, K.V.M.Krishna, D.Srivastava, G.K.Dey, P.Pant, R.D.Doherty,
I.Samajdar, Quantifying the mesoscopic shear strains in plane strain compressed
polycrystalline zirconium, Acta. Mater. 69 (2014) 265–274.
[94] I.L.Dillamore, H.Katoh, A Comparison of the Observed and Predicted Deformation
Textures in Cubic Metals, Met. Sci. 8 (1974) 21–27.
[95] S.Raveendra, A.K.Kanjarala, H.Paranjape, S.K.Mishra, S.Mishra, L.Delannay, I.Samajdar
Strain mode dependence of deformation texture developments:microstructural origin,
Metall. Mater. Transcations A. 42A (2011) 2011–2113.
[96] S.P.R.Becher, Effects of grain interactions on deformation and local texture in
polycrystals, Acta.Metall.Mater. 43 (1995) 2701–2719.
53
[97] D.A.Hughes, N.Hansen, High angle boundaries formed by grain subdivision mechanisms,
Acta. Mater. 45 (1997) 3871–3886.
[98] F.Roters, D.Raabe, G.Gottstein, Work hardening in heterogeneous alloys—a
microstructural approach based on three internal state variables, Acta Mater. 48 (2000)
4181–4189.
[99] S.K.Mishra, P.Pant, K.Narasimhan, A.D.Rollet, I. Samajdar, On the widths of orientation
gradient zones adjacent to grain boundaries, Scripta. Mater. 61 (2009) 273–276.
[100] D.Raabe, Simulation and Experimental Examination of the Evolution of Orientation
Gradients in Single Grains During Rolling of Body-Centered-Cubic Polycrystals, Phys.
Stat.Sol.B. 181 (1994) 291–299.
[101] O.Diard, S.Leclercq, G.Rousselier, G.Cailletaud, Evaluation of finite element based
analysis of 3D multicrystalline aggregates plasticity Application to crystal plasticity model
identification and the study of stress and strain fields near grain boundaries, Int. J. Plast.
21 (2005) 691–722.
[102] M.Kamaya, Assessment of local deformation using EBSD: Quantification of local damage
at grain boundaries, Mater. Charact. 66 (2012) 56–67.
[103] W.C. Liu, P.P. Zhai, C.S. Man, Estimating local dislocation content near a grain boundary
in hot deformed AA 3104 aluminum alloy, Mater. Sci. Eng. A. 531 (2012) 178–181.
[104] Y.L.Shen, W.Li, D.L.Sulsky, H.L.Schreyer, Localization of plastic deformation along
grain boundaries in a hardening material, Int. J. Mech. Sci. 42 (2000) 2167–2189.
[105] D.Peirce, R.J.Asaro, A.Needleman, An analysis of nonuniform and localized deformation
in ductile single crystals, Acta Metall. 30 (1982) 1087–1119.
[106] P.Van Houtte, L.Delannay, S.R.Kalidindi, Comparison of two grain interaction models for
polycrystal plasticity and deformation texture prediction, Int. J. Plast. 18 (2002) 359–377.
[107] P.Van Houtte, S.Li, M.Seefeldt, L.Delannay, Deformation texture prediction: from the
taylor model to the advanced Lamel model, Int. J. Plast. 21 (2005) 589–624.
[108] R.Lagneborgj, The martensite transformation in 18% Cr-8% Ni steels, Acta Metall. 12
(1964) 823–843.
[109] L.E.Murr, K.P.Staudhammer, S.S. Hecker, Effects of Strain State and Strain Rate on
Deformation-Induced Transformation in 304 Stainless Steel: Part II. Microstructural
Study, Metall. Trans. A. 13 (1982) 627–635.
[110] A.J.Goldman, C.N.J.Wagner, Faulting in deformed austenite and martensite, Acta Metall.
11 (1963) 405–413.
54
[111] N.Gey, B.Petit, M.Humbert, Electron backscattered diffraction study of ε/α′ martensitic
variants induced by plastic deformation in 304 stainless steel, Metall. Mater. Trans. A. 36
(2005) 3291–3299.
[112] W.S.Lee, C.F.Lin, Morphologies and characteristics of impact-induced martensite in 304L
stainless steel, Scr. Mater. 43 (2000) 777–782.
[113] K.Elayaperumal, P.K.De, J.Balachandra, Passivity of type 304 stainless steel–effect of
plastic deformation, Corrosion. 28 (1972) 269–273.
[114] S.V.Phadnis, A.K.Satpati, K.P.Muthe, J.C.Vyas, R.I.Sundaresan, Comparison of rolled
and heat treated SS304 in chloride solution using electrochemical and XPS techniques,
Corros. Sci. 45 (2003) 2467–2483.
[115] R.A.Schwarzer, D.P.Field, B.L.Adams, M.Kumar, A.J. Schwartz, Present state of electron
backscatter diffraction and prospective developments, in: A.J. Schwartz, M. Kumar, B.L.
Adams, D.P. Field (Eds.), Electron Backscatter Diffr. Mater. Sci., Springer Science +
Business media, New York, 2009: pp. 1–20.
[116] S.Hong, M.Kim, D.Min, K.Lee, J.Shim, D.Kim, J.Suh, W.Sung, I.Choi, Unraveling the
origin of strain-induced precipitation of M23C6 in the plastically deformed 347 Austenite
stainless steel, Mater. Charact. 94 (2014) 7–13.
[117] G.B.Olson, M.Cohen, Kinetics of strain-induced martensitic nucleation, Metall. Trans. A.
6 (1975) 791–795.
[118] J.R.C.Guimarães, J.C.Gomes, A metallographic study of the influence of the austenite
grain size on martensite kinetics, Acta Metall. 26 (1978) 1591–1596.
[119] J.R.C.Guimarães, Excess driving force to initiate martensite transformation in fine-grained
austenite, Scr. Mater. 57 (2007) 237–239.
[120] P.Hedström, U.Lienert, J.Almer, M.Odén, Stepwise transformation behavior of the strain-
induced martensitic transformation in a metastable stainless steel, Scr. Mater. 56 (2007)
213–216.
[121] P.Hedström, L.E.Lindgren, J.Almer, U.Lienert, J.Bernier, M.Terner, M.Oden, Load
Partitioning and Strain-Induced Martensite Formation during Tensile Loading of a
Metastable Austenitic Stainless Steel, Metall. Mater. Trans. A. 40 (2009) 1039–1048.
[122] D.N.Wasnik, I.K.Gopalakrishnan, J.V.Yakhmi, V.Kain, I.Samajdar, Cold rolled texture
and microstructure in types 304 and 316L austenitic stainless steels, ISIJ Int. 43 (2003)
1581–1589.
55
[123] K.Mumtaz, S.Takahashi, J.Echigoya, Y.Kamada, L.F.Zhang, H.Kikuchi,K.Ara, M.Sato
Magnetic measurements of martensitic transformation in austenitic stainless steel after
room temperature rolling, J. Mater. Sci. 39 (2004) 85–97.
[124] K.Mumtaz, S.Takahashi, J.Echigoya, Y. Kamada, L.F. Zhang, H. Kikuchi, K.Ara, M.Sato,
Magnetic measurements of the reverse martensite to austenite transformation in a rolled
austenitic stainless steel, J. Mater. Sci. 39 (2004) 1997–2010.
[125] O.Hoffman, G.Sachs, Introduction to theroy of plasticity for engineers, Mc Graw Hill,
New York, 1953.
[126] N.A.Fleck, J.W.Hutchinson, Strain Gradient Plasticity, in: W.H. John, Y.W. Theodore
(Eds.), Adv. Appl. Mech., Elsevier, 1997: pp. 295–361.
[127] R.G.Stringfellow, D.M.Parks, G.B.Olson, A constitutive model for transformation
plasticity accompanying strain-induced martensitic transformations in metastable
austenitic steels, Acta Metall. Mater. 40 (1992) 1703–1716.
[128] N.A.Fleck, G.M.Muller, M.F.Ashby, J.W. Hutchinson, Strain gradient plasticity: Theory
and experiment, Acta Metall. Mater. 42 (1994) 475–487.
[129] D.Raabe, M.Sachtleber, Z.Zhao, F.Roters, S.Zaefferer,Micromechanical and
macromechanical effects in grain scale polycrystal plasticity experimentation and
simulation, Acta. Mater. 49 (2001) 3433–3441.
[130] X.Liang, J.R.McDermid, O.Bouaziz, X.Wang, J.D.Embury, H.S.Zurob, Microstructural
evolution and strain hardening of Fe-24Mn and Fe-30Mn alloys during tensile
deformation, Acta Mater. 57 (2009) 3978–3988.
[131] D.Hull, D.J.Bacon, Chapter 8 Origin and multiplication of dislocations, in: Introduction.
to Dislocations, fifth Ed., Butterworth-Heinemann, Oxford, 2011: pp. 157–169.
[132] D.Hull, D.J.Bacon, Chapter 3 Movement of dislocations, in: Introduction. to Dislocations,
fifth ed., Butterworth-Heinemann, Oxford, 2011: pp. 43–62.
[133] J.Kacher, B.P.Eftink, B.Cui, I.M.Robertson, Dislocation interactions with grain
boundaries, Curr. Opin. Solid State Mater. Sci. 18 (2014) 227–243.
[134] K.Zhang, Multi-level Modelling of Plastic Anisotropy of Aluminium Alloys Using Crystal
Plasticity Models and Advanced Yield Functions, 2014.
[135] N.Clement, D.Caillard, J.L.Martin, Heterogeneous deformation of concentrated NiCr
F.C.C. alloys: Macroscopic and microscopic behaviour, Acta Metall. 32 (1984) 961–975.
[136] M.Sachtleber, Z.Zhao, D. Raabe, Experimental investigation of plastic grain interaction,
Mater. Sci. Eng. A. 336 (2002) 81–87.
56
[137] T.R.Bieler, S.L.Semiatin, The origins of heterogeneous deformation during primary hot
working of Ti-6Al-4V, Int. J. Plast. 18 (2002) 1165–1189.
[138] N.Allain-Bonasso, F.Wagner, S.Berbenni, D.P.Field, A study of the heterogeneity of
plastic deformation in IF steel by EBSD, Mater. Sci. Eng. A. 548 (2012) 56–63.
[139] P.VanHoutte, L.Delannay, I. Samajdar, Quantitative Prediction of Cold Rolling Textures
in Low-Carbon Steel by Means of the Lamel Model, Textures Microstruct. 31 (1999)
109–149.
[140] F.Roters, P.Eisenlohr, T.R.Bieler, D.Raabe, Introduction to crystalline anisotropy and the
crystal plasticity finite element method in: The Crystal Plasticity Finite Element Method
as a Multiphysics Framework, Wiley (2010) 1–6.
[141] F.Roters, P.Eisenlohr, L.Hantcherli, D.D.Tjahjanto, T.R.Bieler, D.Raabe, Overview of
constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity
finite-element modeling: Theory, experiments, applications, Acta Mater. 58 (2010) 1152–
1211.
[142] H.Moulinec, P.Suquet, A numerical method for computing the overall response of
nonlinear composites with complex microstructure, Comput. Methods Appl. Mech. Eng.
157 (1998) 69–94.
[143] G.I.Taylor, The mechanism of plastic deformation of crystals, P. R. Soc.London. 145
(1934) 362–387.
[144] S.Bernhardsson, P.Norberg, H.Eriksson, O.Forssell, A.B.S.Steel, Selection of stainless
steels for refineries and the petrochemical industry, (1986).
[145] S.Bernhardsson, Corrosion performance of a high-nickel alloy, Mater. Des. 10 (1989)
186–196.
[146] C.L.Briant, R.A.Mulford, E.L.Hall, Sensitization of Austenitic Stainless Steels, I.
Controlled Purity Alloys, Corrosion. 38 (1982) 468–477.
[147] T.M.Devine, Kinetics of sensitization and de-sensitization of duplex 308 stainless steel,
Acta Metall. 36 (1988) 1491–1501.
[148] T.M.Devine, The mechanism of sensitization of austenitic stainless steel, Corros.Sci. 30
(1990) 135–151.
[149] A.J.Sedriks, Corrosion of Stainless Steels, second ed., A Wiley-Interscience Publication,
New York, 1996.
57
[150] H.Kim, S.Jeon, S.Kim, I.Lee, Y.Park, K.Kim, Y.Kim, Investigation of the sensitization
and intergranular corrosion of tube-to-tubesheet welds of hyper duplex stainless steel
using an electrochemical reactivation method, Corros. Sci. 87 (2014) 60–70.
[151] C.S.Tedmon, D.A.Vermilyea, J.H.Rosolowski, Intergranular corrosion of austenitic
stainless steel, J.Electrochemical.Soc. 118 (1971) 192–202.
[152] V.Cihal, Intergranular Corrosion of Steels and Alloys, first ed., Elsevier Applied Science
Publishers, New York, 1984.
[153] M.G.Fontana, Corrosion Engineering, first ed., Tata Mc-Graw Hill Edition, New Delhi,
1986.
[154] R.W.Revie, H.H.Uhlig, Corrosion and Corrosion Control: An introduction to Corrosion
Science and Engineering, fourth ed., Wiley Interscience, New Jersey, 2008.
[155] P.J.Gellings, M.A.de Jongh, Grain boundary oxidation and the chromium depletion theory
of intercrystalline corrosion of austenitic stainless steels, Corros.Sci. 7 (1967) 413–421.
[156] R.L. Fullman, A thermodynamic model of the effects of composition on the susceptibility
of austenitic stainless steels to intergranular stress corrosion cracking, Acta.Metall.Mater.
30 (1982) 1407–1415.
[157] E.Hall, C.Briant, Chromium depletion in the vicinity of carbides in sensitized austenitic
stainless steels, Metall. Trans. A. 15 (1984) 793–811.
[158] S.M.Bruemmer, L.A.Charlot, Development of grain boundary chromium depletion in type
304 and 316 stainless steels, Scripta.Metall.Mater. 20 (1986) 1019–1024.
[159] C.Stawstrom, M.Hillert, An improved depleted-zone theory of intergranular corrosion of
18-8 stainless steel , J.Iron.Steel.I. 207 (1969) 77–85.
[160] G.S.Was, R.M.Kruger, A thermodynamic and kinetic basis for understanding chromium
depletion in Ni-Cr-Fe alloys, Acta.Metall.Mater. 33 (1985) 841–854.
[161] S.M.Bruemmer, B.W.Arey, L.A.Charlot, Influence of chromium depletion on
intergranular stress corrosion cracking of 304 stainless steel, Corrosion. 48 (1992) 42–49.
[162] M.A.Gaudett, J.R.Scully, Distributions of Cr depletion levels in sensitized AISI 304
stainless steel and its implications concerning intergranular corrosion phenomena,
J.Electrochem.Soc. 140 (1993) 3425–3435.
[163] M.H.Lewis, B.Hattersley, Precipitation ofM23C6 in austenitic steels, Acta.Metall.Mater.
13 (1965) 1159–1168.
58
[164] D.L.Engelberg, 2.06 Intergranular Corrosion, in: J.A.R. Tony (Ed.), Shreir’s Corros.,
Elsevier, Oxford, 2010: pp. 810–827.
[165] B.Strauss, H.Schottky, J.Hinnuber, The carbide precipitation during annealing of stainless
non-magnetic stainless steel, J. Inorg. Gen. Chem. 188 (1930) 309–324.
[166] E.C.Bain, R.H.Aborn, J.J.B.Rutherford, The nature and prevention of intergranular
corrosion in austenitic stainless steels, Transcation Am. Soc. Steel Treat. 21 (1933) 481–
509.
[167] T.A.Mozhi, M.C.Juhas, B.E.Wilde, Modeling low temperature sensitization of austenitic
stainless steels, Scripta.Metall.Mater. 21 (1987) 1547–1552.
[168] P. De.Tiedra, Ó. Martín, M. López, M. San-Juan, Use of EPR test to study the degree of
sensitization in resistance spot welding joints of AISI 304 austenitic stainless steel,
Corros. Sci. 53 (2011) 1563–1570.
[169] V.Kain, R.C.Prasad, P.K.De, Testing sensitization and predicting susceptibility to
intergranular corrosion and intergranular stress corrosion cracking in austenitic stainless
steels, Corrosion. 58 (2002) 15–37.
[170] R.J.Bendure, L.C.Ikenberry, J.H.Waxweiler, Quantity and form of carbides in austenitic
and precipitation hardening stainless steels, T.Metall.Soc.AIME. 221 (1961) 1032–1039.
[171] R.Pascali, A.Benvenuti, D.Wenger, Carbon content and grain size effects on the
sensitization of AISI type 304 stainless steels, Corrosion. 40 (1984) 21–32.
[172] A.I.Z. Farahat, T.A. El-Bitar, Effect of Nb, Ti and cold deformation on microstructure and
mechanical properties of austenitic stainless steels, Mat.Sci.Eng.A. 527 (2010) 3662–
3669.
[173] A.H.Advani, D.G.Atteridge, L.E.Murr, Solution annealing effects on sensitization of 316
stainless steels, Scripta.Metallurgica Mater. 25 (1991) 2221–2226.
[174] Y.Watanabe, V.Kain, T.Tonozuka, T.Shoji, T.Kondo, F.Masuyama, Effect of Ce addition
on the sensitization properties of stainless steels, Scripta.Mater. 42 (2000) 307–312.
[175] R.Singh, S.Chowdhury, I.Chattoraj, Modification of sensitization resistance of AISI 304L
stainless steel through changes in grain size and grain boundary character distributions,
Metall. Mater. Trans. A. 39 (2008) 2504–2512.
[176] T.Watanabe, Approach to grain boundary design for strong and ductile polycrystals, Res.
Mech. 11 (1984) 47–84.
[177] G.Palumbo, K.T.Aust, Localized corrosion at grain boundary intersections in high purity
nickel, Scripta.Metall.Mater. 22 (1988) 847–852.
59
[178] K.T.Aust, U.Erb, G.Palumbo, Interface control for resistance to intergranular cracking,
Mat.Sci.Eng.A. 176 (1994) 329–334.
[179] P.Lin, G.Palumbo, U.Erb, K.T.Aust, Influence of grain boundary character distribution on
sensitization and Intergranular corrosion of alloy 600, Scripta.Metall.Mater. 33 (1995)
1387–1392.
[180] V.Randle, The Role of Coincident Site Lattice in Grain Boundary Engineering, first ed.,
Ashgate Publishing, Cambridge, United Kingdom, 1996.
[181] V.Y.Gertsman, S.M.Bruemmer, Study of grain boundary character along intergranular
stress corrosion crack paths in austenitic alloys, Acta. Mater. 49 (2001) 1589–1598.
[182] M.Shimada, H.Kokawa, Z.J.Wang, Y.S.Sato, I. Karibe, Optimization of grain boundary
character distribution for intergranular corrosion resistant 304 stainless steel by twin-
induced grain boundary engineering, Acta. Mater. 50 (2002) 2331–2341.
[183] D.N.Wasnik, V.Kain, I.Samajdar, B.Verlinden, P.K.De, Resistance to sensitization and
intergranular corrosion through extreme randomization of grain boundaries, Acta. Mater.
50 (2002) 4587–4601.
[184] H.Kokawa, M.Shimada, M.Michiuchi, Z.J.Wang, Y.S.Sato, Arrest of weld-decay in 304
austenitic stainless steel by twin-induced grain boundary engineering, Acta. Mater. 55
(2007) 5401–5407.
[185] R.Jones, V.Randle, Sensitisation behaviour of grain boundary engineered austenitic
stainless steel, Mat. Sci.Eng.A. 527 (2010) 4275–4280.
[186] C.Hu, S.Xia, H.Li, T.Liu, B.Zhou, W.Chen, N.Wang, Improving the intergranular
corrosion resistance of 304 stainless steel by grain boundary network control, Corros. Sci.
53 (2011) 1880–1886.
[187] V.Randle, Grain boundary engineering: an overview after 25 years, Mater. Sci. Technol.
26 (2010) 253–261.
[188] D.G.Brandon, The structure of high-angle grain boundaries, Acta.Metall.Mater. 14 (1966)
1479–1484.
[189] V.Randle, Grain Boundary Engineering, in: K.H.J.B. Editors-in-Chief:, W.C. Robert, C.F.
Merton, I. Bernard, J.K. Edward, M. Subhash, et al. (Eds.), Encycl. Mater. Sci. Technol.
(Second Ed., Elsevier, Oxford, 2005: pp. 1–8.
[190] A.J.Schwartz, W.E.King, M.Kumar, Influence of processing method on the network of
grain boundaries, Scr. Mater. 54 (2006) 963–968.
60
[191] M.Michiuchi, H.Kokawa, Z.J.Wang, Y.S.Sato, K.Sakai, Twin-induced grain boundary
engineering for 316 austenitic stainless steel, Acta Mater. 54. (2006).
[192] B.Sunil Kumar, B.S.Prasad, V.Kain, J.Reddy, Methods for making alloy 600 resistant to
sensitization and intergranular corrosion, Corros. Sci. 70 (2013) 55–61.
[193] Standard practices for detecting susceptibility to intergranular attack in austenitic stainless
steels, ASTM Int. A262-10 (2010) 1–16.
[194] V.Cihal, R.Stefec, T.Shoji, T.Watanabe, V.Kain, Electrochemical potentiodynamic
reactivation: development and applications of the EPR test, Key. Engg.Mat. 261-263
(2004) 855–864.
[195] A.P.Majidi, M.A.Streicher, The double loop reactivation method for detecting
sensitization in AISI 304 stainless steels, Corrosion. 40 (1984) 584–593.
[196] Corrosion of metals and alloys- Electrochemcial potentiokinetic reactivation measurement
using the double loop method (based on Cihal’s method), BS ISO 127 (2006).
[197] V.Kain, K.Chandra, K.N.Adhe, P.K.De, Detecting classical and martensite-induced
sensitization using the electrochemical potentiokinetic reactivation test, Corrosion. 61
(2005) 587–593.
[198] A.P.Majidi, M.A.Streicher, Potentiodynamic reactivation method for detecting
sensitization in AISI 304 and 304L stainless steels, Corrosion. 40 (1984) 393–408.
[199] N.Ortiz, F.F.Curiel, V.H.López, A.Ruiz, Evaluation of the intergranular corrosion
susceptibility of UNS S31803 duplex stainless steel with thermoelectric power
measurements, Corros. Sci. 69 (2013) 236–244.
[200] C.S.Tedmon, D.A.Vermilyea, D.E.Broecker, Effect of cold work on intergranular
corrosion of sensitized stainless steel, Corrosion. 27 (1971) 104–106.
[201] R.Singh, I.Chattoraj, A.Kumar, B.Ravikumar, P.Dey, The effects of cold working on
sensitization and intergranular corrosion behavior of AISI 304 stainless steel, Metall.
Mater. Trans. A. 34 (2003) 2441–2447.
[202] C.Garcia, F.Martin, P.De.Tiedra, J.A. Heredero, M.L. Aparicio, Effect of prior cold work
on intergranular and transgranular corrosion in type 304 stainless steels: quantitative
discrimination by image analysis, Corrosion. 56 (2000) 243–255.
[203] T.Thorvaldsson, G.Dunlop, Grain boundary Cr-depleted zones in Ti and Nb stabilized
austenitic stainless steels, J.Mater. Sci. 18 (1983) 793–803.
61
[204] E.A.Trillo, L.E.Murr, Effects of carbon content, deformation, and interfacial energetics on
carbide precipitation and corrosion sensitization in 304 stainless steel, Acta. Mater. 47
(1998) 235–245.
[205] S.M.Bruemmer, Grain Boundary Chemistry and Intergranular Failure of Austenitic
Stainless Steels, Mater. Sci. Forum. 46 (1989) 309–334.
[206] N.Parvathavarthini, S.Mulki, R.K.Dayal, I.Samajdar, K.V.Mani, B.Raj, Sensitization
control in AISI 316L(N) austenitic stainless steel: defining the role of the nature of grain
boundary, Corros. Sci. 51 (2009) 2144–2150.
[207] V.Randle, Refined approaches to the use of the coincidence site lattice,
JOM.J.Min.Met.Mat.S. 50 (1998) 56–58.
[208] D.B.Wells, J.Stewart, A.W.Herbert, P.M.Scott, D.E.Williams, The use of percolation
theory to predict the probability of failure of sensitized, austenitic stainless steels by
intergranular stress corrosion cracking, Corrosion. 45 (1989) 649–660.
[209] M.A.Gaudett, J.R.Scully, Applicability of bond percolation theory to intergranular stress-
corrosion cracking of sensitized AlSl 304 stainless steel, Metall.Mater.Trans.A. 25 (1994)
775–787.
[210] S.Tsurekawa, S.Nakamichi, T.Watanabe, Correlation of grain boundary connectivity with
grain boundary character distribution in austenitic stainless steel, Acta. Mater. 54 (2006)
3617–3626.
[211] D.L.Engelberg, R.C.Newman, T.J.Marrow, Effect of thermomechanical process history on
grain boundary control in an austenitic stainless steel, Scripta. Mater. 59 (2008) 554–557.
[212] J.K.Kim, Y.H.Kim, B.H.Lee, K.Y.Kim, New findings on intergranular corrosion
mechanism of stabilized stainless steels, Electrochim. Acta. 56 (2011) 1701–1710.
[213] M.Stalder, S.Vogel, M.A.M.Bourke, J.G.Maldonado, D.J.Thoma, V.W.Yuan,
Retransformation (alpha to gamma) kinetics of strain induced martensite in 304 stainless
steel, Mater. Sci. Eng. A280.(2000) 270–281.
[214] C.L.Briant, A.M.Ritter, The effect of martensite on the sensitization of low carbon 304
stainless steel, Metall. Trans. A. 12 (1981) 910–913.
[215] E.Almanza, L.E.Murr, A comparison of sensitization kinetics in 304 and 316 stainless
steels, J. Mater. Sci. 35 (2000) 3181–3188.
[216] L.V.Jinlong, L. Hongyun, Influence of tensile pre-strain and sensitization on passive films
in AISI 304 austenitic stainless steel, Mater. Chem. Phys. 135 (2012) 973–978.
62
[217] S.Takahashi, J.Echigoya, T.Ueda, Martensitic transformation due to plastic deformation
and magnetic properties in SUS 304 stainless steel, J. Mater. Process. Technol. 108 (2001)
213–216.
[218] C.L.Briant, Technical Note: Sensitization of Partially Martensitic Stainless Steels at Very
Low Temperatures, Corrosion. 38 (1982) 596–597.
[219] Y.Ma, J.E.Jin, Y.K.Lee, A repetitive thermomechanical process to produce nano-
crystalline in a metastable austenitic steel, Scr. Mater. 52 (2005) 1311–1315.
[220] G.G.Long, J.Kruger, M. Kuriyama, Passivity of Metals and Semiconductors, Passiv. Met.
Semicond. (1983) 139–143.
[221] G.S.Frankel, Pitting Corrosion, ASM International, Volume13 (2003) 236–241.
[222] G.S.Frankel, Pitting corrosion of metals: A review of the critical factors, J. Electrochem.
Soc. 145 (1998) 2186–2198.
[223] T.P.Hoar, The production and breakdown of the passivity of metals, Corros. Sci. 7 (1967)
341–355.
[224] C.J.Semino, J.R.Galvele, Passivity breakdown of high purity iron and AISI 4340 steel in
0.5M NaCl solution, Corros. Sci. 16 (1976) 297–306.
[225] C.M.Rangel, T.M.Silva, M.da.C.Belo, Semiconductor electrochemistry approach to
passivity and stress corrosion cracking susceptibility of stainless steels, Electrochim. Acta.
50 (2005) 5076–5082.
[226] N.Sato, Anodic breakdown of passive films on metals, J. Electrochem. Soc. 129 (1982)
255–260.
[227] G.T. Burstein, Passivity and localised corrosion, in: L.L.Shreir, R.A.Jarman, G.T.Burstein
(Eds.), Corros. Vol. 1 Met. React., Butterworth Heinemann, Great Briton, 1994: pp. 118–
150.
[228] T.L.S.L.Wijesinghe, D.J.Blackwood, Characterisation of passive films on 300 series
stainless steels, Appl. Surf. Sci. 253 (2006) 1006–1009.
[229] S.J.Doh, J.H.Je, J.S.Kim, K.Y.Kim, H.S.Kim, Y.D.Lee, J.M.Lee, Y.Hwu, Influence of Cr
and Mo on the passivation of stainless steel 430 (18Cr) and 444 (18Cr–2Mo): In situ
XANES study, Nucl. Instruments Methods Phys. Res. Sect. B. 199 (2003) 211–215.
[230] M.H.Dean, U.Stimming, The electronic properties of disordered passive films, Corros.
Sci. 29 (1989) 199–211.
63
[231] J.W.Schultze, M.M.Lohrengel, Stability, reactivity and breakdown of passive films.
problems of recent and future research, Electrochim. Acta. 45 (2000) 2499–2513.
[232] N.E.Hakiki, M.F.Montemor, M.G.S.Ferreira, M.da.C.Belo, Semiconducting properties of
thermally grown oxide films on AISI 304 stainless steel, Corros. Sci. 42 (2000) 687–702.
[233] S.Lozano-Perez, T.Yamada, T.Terachi, M.Schröder, C.A.English, G.D.W. Smith,
C.R.M.Grovenor, B.L.Eyre, Multi-scale characterization of stress corrosion cracking of
cold-worked stainless steels and the influence of Cr content, Acta. Mater. 57 (2009) 5361–
5381.
[234] J.D.Sudbury, O.L.Riggs, D.A.Shock, Anodic passivation studies, Corrosion. 16 (1960)
47t–54t.
[235] W.A.Mueller, The polarization curve and anodic protection, Corrosion. 18 (1962) 359t–
367t.
[236] K.Osozawa, H.J.Engell, The anodic polarization curves of iron-nickel-chromium alloys,
Corros. Sci. 6 (1966) 389–393.
[237] H.C.Man, D.R.Gabe, A study of pitting potentials for some austenitic stainless steels using
a potentiodynamic technique, Corros. Sci. 21 (1981) 713–721.
[238] V.S. Rao, V.S. Raja, Anodic polarization and surface composition of Fe-16Al-0.14C alloy
in 0.25 M sulfuric acid, Corrosion. 59 (2003) 575–583.
[239] Y.Yi, P.Cho, A.Al Zaabi, Y.Addad, C.Jang, Potentiodynamic polarization behaviour of
AISI type 316 stainless steel in NaCl solution, Corros. Sci. 74 (2013) 92–97.
[240] J.E.Castle, R.Ke, Studies by augur spectroscopy of pit initiation at the site of inclusions in
stainless steel, Corros. Sci. 30 (1990) 409–428.
[241] V.Shankar Rao, M.Norell, V.S.Raja, Scanning auger electron spectroscopy study of the
oxide film formed on dendritic and interdendritic regions of C containing Fe3Al
intermetallic, Corros. Sci. 45 (2003) 2717–2728.
[242] D.L.A.de Faria, S.V.Silva, M.T.de.Oliveira, Raman microspectroscopy of some iron
oxides and oxyhydroxides, J. Raman Spectrosc. 28 (1997) 873–878.
[243] S. Ramya, T. Anita, H. Shaikh, R.K. Dayal, Laser Raman microscopic studies of passive
films formed on type 316LN stainless steels during pitting in chloride solution, Corros.
Sci. 52 (2010) 2114–2121.
[244] L.V.Taveira, M.F.Montemor, M. Da Cunha Belo, M.G. Ferreira, L.F.P. Dick, Influence of
incorporated Mo and Nb on the Mott-Schottky behaviour of anodic films formed on AISI
304L, Corros. Sci. 52 (2010) 2813–2818.
64
[245] Z.Feng, X.Cheng, C.Dong, L.Xu, X.Li, Passivity of 316L stainless steel in borate buffer
solution studied by Mott–Schottky analysis, atomic absorption spectrometry and X-ray
photoelectron spectroscopy, Corros. Sci. 52 (2010) 3646–3653.
[246] L.Jinlong, L.Hongyun, Electrochemical investigation of passive film in pre-deformation
AISI 304 stainless steels, Appl. Surf. Sci. 263 (2012) 29–37.
[247] M.BenSalah, R.Sabot, E.Triki, L.Dhouibi, P.Refait, M.Jeannin, Passivity of Sanicro28
(UNS N-08028) stainless steel in polluted phosphoric acid at different temperatures
studied by electrochemical impedance spectroscopy and Mott–Schottky analysis, Corros.
Sci. 86 (2014) 61–70.
[248] R.Babic, Semiconducting properties of passive films on AISI 304 and 316 stainless steels,
J. Electroanal. Chem. 358 (1993) 143–160.
[249] A.Fattah-alhosseini, M.A.Golozar, A.Saatchi, K.Raeissi, Effect of solution concentration
on semiconducting properties of passive films formed on austenitic stainless steels,
Corros. Sci. 52 (2010) 205–209.
[250] S.Fujimoto, H.Tsuchiya, Semiconductor Property of Passive Films and Corrosion
Behavior of Fe-Cr Alloys, Charact. Corros. Prod. Steel Surfaces. (n.d.).
[251] A.Alamr, D.F.Bahr, M.Jacroux, Effects of alloy and solution chemistry on the fracture of
passive films on austenitic stainless steel, Corros. Sci. 48 (2006) 925–936.
[252] S.Antonio, Corrosion fundamentals and characterization techniques, in: 2008: pp. 6–45.
[253] M.Odziemkowski, Spectroscopic studies and reactions of corrosion products at surfaces
and electrodes, in: S.D. Jack Yarwood, Richard Douthwaite (Ed.), Spectrscopic Prop.
Inorg. Organomet. Compd., 2009: pp. 385–449.
[254] I.Olefjord, L.Wegrelius, Surface analysis of passive state, Corros. Sci. 31 (1990) 89–98.
[255] S.Mischler, A.Vogel, H.J.Mathieu, D.Landolt, The chemical composition of the passive
film on Fe-24Cr and Fe-24Cr-11Mo studied by AES, XPS and SIMS, Corros. Sci. 32
(1991) 925–944.
[256] A.Seyeux, M.Liu, P.Schmutz, G.Song, A.Atrens, P.Marcus, ToF-SIMS depth profile of
the surface film on pure magnesium formed by immersion in pure water and the
identification of magnesium hydride, Corros. Sci. 51 (2009) 1883–1886.
[257] M.Salasi, G.B.Stachowiak, G.W. Stachowiak, M.R.Kilburn, NanoSIMS investigation of
passive oxide films on high-Cr cast iron, Corros. Sci. 67 (2013) 298–303.
65
[258] K.Hashimoto, K.Asami, K.Teramoto, An X-ray photo-electron spectroscopic study on the
role of molybdenum in increasing the corrosion resistance of ferritic stainless steels in
HCl, Corros. Sci. 19 (1979) 3–14.
[259] J.M.Bastidas, M.F.López, A.Gutierrez, C.L.Torres, Chemical analysis of passive films on
type AISI 304 stainless steel using soft X-ray absorption spectroscopy, Corros. Sci. 40
(1998) 431–438.
[260] A.A.Hermas, XPS analysis of the passive film formed on austenitic stainless steel coated
with conductive polymer, Corros. Sci. 50 (2008) 2498–2505.
[261] R.Steinberger, J.Duchoslav, T.Greunz, M.Arndt, D.Stifter, Investigation of the chemical
stability of different Cr (VI) based compounds during regular X-ray photoelectron
spectroscopy measurements, Corros. Sci. 90 (2015) 562–571.
[262] K.F.McCarty, D.R.Boehme, A Raman study of the systems Fe3−xCrxO4 and Fe2−xCrxO3, J.
Solid State Chem. 79 (1989) 19–27.
[263] N.Boucherit, A.H.L.Goff, S.Joiret, Influence of Ni, Mo, and Cr on pitting corrosion of
steels studied by Raman spectroscopy, Corrosion. 48 (1992) 569–579.
[264] L.J.Oblonsky, T.M.Devine, A surface enhanced Raman spectroscopic study of the passive
films formed in borate buffer on iron, nickel, chromium and stainless steel, Corros. Sci. 37
(1995) 17–41.
[265] Y.Fu, X.Wu, E.Han, W.Ke, K.Yang, Z.Jiang, Influence of cold work on pitting corrosion
behavior of a high nitrogen stainless steel, J. Electrochem. Soc. 155 (2008) C455–C463.
[266] A.Barbucci, G.Cerisola, P.L.Cabot, Effect of cold-working in the passive behavior of 304
stainless steel in sulfate media, J. Electrochem. Soc. 149 (2002) B534–B542.
[267] U.K.Mudali, S.Ningshen, A.K.Tyagi, R.K.Dayal, Influence of Metallurgical and Chemical
Variables on the Pitting Corrosion Behaviour of Nitrogen-Bearing Austenitic Stainless
Steels, Mater. Sci. Forum. 318-320 (1999) 495–502.
[268] U.K.Mudali, R.K.Dayal, J.B.Gnanamoorthy, P.Rodriguez, Pitting corrosion studies on
nitrogen-bearing austenitic stainless steels, Mater. Transcations JIM. 37 (1996) 1568–
1573.
[269] U.K.Mudali, P.Shankar, S.Ningshen, R.K.Dayal, H.S.Khatak, B.Raj, On the pitting
corrosion resistance of nitrogen alloyed cold worked austenitic stainless steels, Corros.
Sci. 44 (2002) 2183–2198.
[270] B.R.Kumar, B.Mahato, R. Singh, Influence of Cold-Worked Structure on Electrochemical
Properties of Austenitic Stainless Steels, Metall. Mater. Trans. A. 38 (2007) 2085–2094.
66
[271] L.Peguet, B.Malki, B.Baroux, Influence of cold working on the pitting corrosion
resistance of stainless steels, Corros. Sci. 49 (2007) 1933–1948.
[272] L.Peguet, B.Malki, B.Baroux, Effect of austenite stability on the pitting corrosion
resistance of cold worked stainless steels, Corros. Sci. 51 (2009) 493–498.
[273] A.Das, P.C.Chakraborti, S.Tarafder, H.K.D.H.Bhadeshia, Analysis of deformation
induced martensitic transformation in stainless steels, Mater. Sci. Technol. 27 (2011) 366–
370.
[274] G.C.Palit, V.Kain, H.S.Gadiyar, Electrochemical investigations of pitting corrosion in
nitrogen-bearing type 316LN stainless steel, Corrosion. 49 (1993) 977–991.
[275] B.Mazza, P.Pedeferri, D.Sinigaglia, A.Cigada, L.Lazzari, G.Re, D.Wenger, Relationship
between the electrochemical and corrosion behavior and the structure of stainless steels
subjected to cold plastic deformation, J. Electrochem. Soc. 123 (1976) 1157–1163.
[276] B.Mazza, P.Pedeferri, D.Sinigaglia, A.Cigada, G.Fumagalli, G.Re, Electrochemical and
corrosion behaviour of work-hardened commercial austenitic stainless steels in acid
solutions, Corros. Sci. 19 (1979) 907–921.
[277] T.J.Mesquita, E.Chauveau, M.Mantel, N.Bouvier, D.Koschel, Corrosion and metallurgical
investigation of two supermartensitic stainless steels for oil and gas environments, Corros.
Sci. 81 (2014) 152–161.
[278] M.Zamanzade, A.Barnoush, Effect of chromium on the electrochemical properties of iron
aluminide intermetallics, Corros. Sci. 78 (2014) 223–232.
[279] C.Örnek, D.L.Engelberg, SKPFM measured volta potential correlated with strain
localisation in microstructure to understand corrosion susceptibility of cold-rolled grade
2205 duplex stainless steel, Corros. Sci. (2015) 4–11.
[280] C.J.Semino, P.Pedeferri, G.T.Burstein, T.P.Hoar, The localized corrosion of resistant
alloys in chloride solutions, Corros. Sci. 19 (1979) 1069–1078.
[281] R.Štefec, F.Franz, A study of the pitting corrosion of cold-worked stainless steel, Corros.
Sci. 18 (1978) 161–168.
[282] V.A.C.Haanappel, M.F.Stroosnijder, Influence of mechanical deformation on the
corrosion behavior of AISI 304 stainless steel obtained from cooking utensils, Corrosion.
57 (2001) 557–565.
[283] A.S.Hamada, L.P.Karjalainen, M.C. Somani, Electrochemical corrosion behaviour of a
novel submicron-grained austenitic stainless steel in an acidic NaCl solution, Mat.Sci.Eng
A. 431 (2006) 211–217.
67
[284] R.D. Moser, P.M. Singh, L.F. Kahn, K.E. Kurtis, Chloride-induced corrosion resistance of
high-strength stainless steels in simulated alkaline and carbonated concrete pore solutions,
Corros. Sci. 57 (2012) 241–253.
[285] A.Randak, F.W.Trautes, Influence of austenite stability of 18-8 Cr-Ni-steels on the cold
working and corrosion properties of these steels, Mater. Corros. 21 (1970) 97–109.
[286] J.Stewart, D.E.E.Williams, The initiation of pitting corrosion on austenitic stainless steel:
on the role and importance of sulphide inclusions, Corros. Sci. 33 (1992) 457–474.
[287] G.P.Halada, D.Kim, C.R.Clayton, Influence of nitrogen on electrochemical passivation of
high-nickel stainless steels and thin molybdenum-nickel films, Corrosion. 52 (1996) 36.
[288] K.Sugimoto, Y.Sawada, The role of molybdenum additions to austenitic stainless steels in
the inhibition of pitting in acid chloride solutions, Corros. Sci. 17 (1977) 425–445.
[289] R.C.Newman, T.Shahrabi, The effect of alloyed nitrogen or dissolved nitrate ions on the
anodic behaviour of austenitic stainless steel in hydrochloric acid, Corros. Sci. 27 (1987)
827–838.
[290] Y.X.Qiao, Y.G.Zheng, W.Ke, P.C.Okafor, Electrochemical behaviour of high nitrogen
stainless steel in acidic solutions, Corros. Sci. 51 (2009) 979–986.
[291] R.Qvarfort, Some observations regarding the influence of molybdenum on the pitting
corrosion resistance of stainless steels, Corros. Sci. 40 (1998) 215–223.
[292] T.Sourisseau, E.Chauveau, B.Baroux, Mechanism of copper action on pitting phenomena
observed on stainless steels in chloride media, Corros. Sci. 47 (2005) 1097–1117.
[293] L.Wegrelius, F.Falkenberg, I.Olefjord, Passivation of Stainless Steels in Hydrochloric
Acid, J. Electrochem. Soc. 146 (1999) 1397–1406.
[294] I.Olefjord, B.O.Elfstrom, The composition of the surface during passivation of stainless
steels, Corrosion. 38 (1982) 46–52.
[295] K.H. N.Hara Y.Sugawara, I.Muto, Improvement of pitting corrosion resistance of type
316L stainless steel by potentiostatic removal of surface MnS inclusions, Int. J. Corros.
2012 (2012) 1–6.
[296] L.Felloni, S.S.Traverso, G.L.Zucchini, G.P.Cammarota, Investigation on the second
anodic current maximum on the polarization curves of commercial stainless steels in
sulphuric acid, 13 (1973) 773–789.
[297] G.T.Burstein, P.C.Pistorius, Surface roughness and the metastable pitting of stainless steel
in chloride solutions, Corrosion. 51 (1995) 380–385.
68
[298] S.Ghosh, V.Kain, Effect of surface machining and cold working on the ambient
temperature chloride stress corrosion cracking susceptibility of AISI 304L stainless steel,
Mater. Sci. Eng. A. 527 (2010) 679–683.
[299] K.E.Heusler, Growth and dissolution of passivating films, Corros. Sci. 31 (1990) 597–
606.
[300] A.Turnbull, K.Mingard, J.D.Lord, B.Roebuck, D.R.Tice, K.J.Mottershead,
N.D.Fairweather, A.K.Bradbury, Sensitivity of stress corrosion cracking of stainless steel
to surface machining and grinding procedure, Corros. Sci. 53 (2011) 3398–3415.
[301] S.Ghosh, V.Kain, Microstructural changes in AISI 304L stainless steel due to surface
machining: Effect on its susceptibility to chloride stress corrosion cracking, J. Nucl.
Mater. 403 (2010) 62–67.
[302] K.N.Lyon, T.J.Marrow, S.B.Lyon, Influence of milling on the development of stress
corrosion cracks in austenitic stainless steel, J. Mater. Process. Technol. 218 (2015) 32–
37.
[303] P.E.Manning, D.J.Duquette, W.F.Savage, The effect of test method and surface condition
on pitting potential of single and duplex phase 304L stainless steel, (1979) 151–157.
[304] Y.Zuo, H.Wang, J.Xiong, The aspect ratio of surface grooves and metastable pitting of
stainless steel, Corros. Sci. 44 (2002) 25–35.
[305] S.E. Ziemniak, M. Hanson, P.C. Sander, Electropolishing effects on corrosion behavior of
304 stainless steel in high temperature, hydrogenated water, Corros. Sci. 50 (2008) 2465–
2477.
[306] C.Wlesner, Residual stresses after orthogonal machining of AISI 304: numerical
calculation of the thermal component and comparison with experimental results, Metall.
Trans. A. 23A (1992) 989–996.
[307] R.B.Cruise, L.Gardner, Residual stress analysis of structural stainless steel sections, J.
Constr. Steel Res. 64 (2008) 352–366.
[308] S.Papula, J.Talonen, O.Todoshchenko, H. Hänninen, Effect of residual stress and strain
induced alpha martensite on delayed cracking of metastable austenitic stainless steels,
Metall. Mater. Trans. A. 45 (2014) 5270–5279.
[309] R.P.Reed, The spontaneous martensitic transformations in 18% Cr, 8% Ni steels, Acta
Metall. 10 (1962) 865–877.
[310] G.Hinds, L.Wickström, K.Mingard, A.Turnbull, Impact of surface condition on sulphide
stress corrosion cracking of 316L stainless steel, Corros. Sci. 71 (2013) 43–52.
69
[311] H.Schulz, T.Moriwaki, High-speed Machining, CIRP Ann. - Manuf. Technol. 41 (1992)
637–643.
[312] Z.Wang, M.Rahman, High speed machining, in: M.S.J. Hashmi (Ed.), Compr. Mater.
Process., Elsevier, Ireland, 2014: pp. 221–253.
[313] K.A. Al-Ghamdi, A. Iqbal, A sustainability comparison between conventional and high-
speed machining, J. Clean. Prod. 108 (2015) 192–206.
[314] P.Novak, I.Rousar, R.Stefec, V.Cihal, Intergranular corrosion in electrochemical
machining, Mater. Chem. Phys. 10 (1984) 155–161.
[315] M.Datta, D.Harris, Electrochemical micromachining: An environmentally friendly, high
speed processing technology, Electrochim. Acta. 42 (1997) 3007–3013.
[316] M.Datta, D.Landolt, Fundamental aspects and applications of electrochemical
microfabrication, Electrochim. Acta. 45 (2000) 2535–2558.
[317] R.Sueptitz, P.Dunne, K.Tschulik, M.Uhlemann, J.Eckert, A.Gebert, Electrochimica Acta
Electrochemical micromachining of passive electrodes, Electrochim. Acta. 109 (2013)
562–569.
[318] Asm, Vol 16 - Machining Processes, ASM Handb. (1990) 944.
[319] M.Martin, S.Weber, C.Izawa, S.Wagner, A.Pundt, W.Theisen, Influence of machining-
induced martensite on hydrogen-assisted fracture of AISI type 304 austenitic stainless
steel, Int. J. Hydrogen Energy. 36 (2011) 11195–11206.
[320] W.Zhang, K.Fang, Y.Hu, S.Wang, X.Wang, Effect of machining-induced surface residual
stress on initiation of stress corrosion cracking in 316 austenitic stainless steel, Elsevier
Ltd, 2016.
[321] L.Gurvich, L.I.Shubadeeva, Effect of machining on corrosion resistance in stainless steels,
Fiz. Mekhanica Mater. 7 (1971) 23–27.
[322] D.O’Sullivan, M.Cotterell, Machinability of austenitic stainless steel SS303, J. Mater.
Process. Technol. 124 (2002) 153–159.
[323] T.Hong, M.Nagumo, Effect of surface roughness on early stages of pitting corrosion of
Type 301 stainless steel, Corros. Sci. 39 (1997) 1665–1672.
[324] M.Faller, S.Buzzi, O.V.Trzebiatowski, Corrosion behaviour of glass-bead blasted stainless
steel sheets and other sheets with dull surface finish in a chloride solution, Mater. Corros.
56 (2005) 373–378.
70
[325] A.Ben Rhouma, C.Braham, M.E.Fitzpatrick, J.Leidion, H.Sidhom, Effects of Surface
Preparation on Pitting Resistance, Residual Stress, and Stress Corrosion Cracking in
Austenitic Stainless Steels, J. Mater. Eng. Perform. 10 (2001) 507–514.
[326] P.J.Withers, H.K.D.H. Bhadeshia, Residual stress. Part 2 – Nature and origins, Mater. Sci.
Technol. 17 (2001) 366–375.
[327] P.J.Withers, Residual stress and its role in failure, Reports Prog. Phys. 70 (2007) 2211–
2264.
[328] N.S.Rossini, M.Dassisti, K.Y.Benyounis, A.G.Olabi, Methods of measuring residual
stresses in components, Mater. Des. 35 (2012) 572–588.
[329] P.J.J. Withers, H.K.D.H. Bhadeshia, Residual stress Part 1 – Measurement techniques,
Mater. Sci. Technol. 17 (2001) 355–365.
[330] I.C. Noyan, Effect of gradients in multi-axial stress states on residual stress measurements
with x-rays, Metall. Trans. A. 14 (1983) 249–258.
[331] P.J.Bouchard, P.J.Withers, Identification of residual stress length scales in welds for
fracture assessment, Proc. a Spec. Symp. Held within 16th Eur. Conf. Fract. - ECF16
Residual Stress Its Eff. Fatigue Fract. Part 4 (2006) 163–176.
[332] P.J.Withers, H.K.D.H.Bhadeshia, Residual stress part 1 - Measurement techniques, Mater.
Sci. Technol. 17 (2001) 355–365.
[333] P.J.Withers, Residual Stresses: Measurement by Diffraction, Encycl. Mater. Sci. Technol.
(2001) 8158–8169.
[334] P.Vanhoutte, L.De.buyser, The influence of crystallographic texture on diffraction
measurements of residual stress, Acta.Metall.Mater. 41 (1999) 323–336.
[335] G.S.Schajer, C.O.Ruud, Overview of residual stresses and thier measurement, in:
G.S.Schajer (Eds), Practical Residual Stress Measurement Methods, John Wiley &Sons
2013 pp. 1–27.
[336] T.R.Watkins,G.S.Schajer,M.J.Lance 1.07 Residual stress measurements in comprehensive
Materials Processing Volume 1, Elsevier, 2012, 113-134
[337] D.Y.Jang, T.R.Watkins, K.J.Kozaczek, C.R.Hubbard, O.B.Cavin, Surface residual stresses
in machined austenitic stainless steel, Wear. 194 (1996) 168–173.
[338] F.Navaï, Effects of tensile and compressive stresses on the passive layers formed on a type
302 stainless steel in a normal sulphuric acid bath, J. Mater. Sci. 30 (1995) 1166–1172.
71
[339] F.Navaï, O.Debbouz, AES study of passive films formed on a type 316 austenitic
stainless-steels in a stress field, J. Mater. Sci. 34 (1999) 1073–1079.
[340] A.S.Hamdy, E. El.Shenawy, T.El.Bitar, The corrosion behavior of niobium bearing cold
deformed austenitic stainless steels in 3.5% NaCl solution, Mater. Lett. 61 (2007) 2827–
2832.
[341] V.Vignal, O.Delrue, O.Heintz, J.Peultier, Influence of the passive film properties and
residual stresses on the micro-electrochemical behavior of duplex stainless steels,
Electrochim. Acta. 55 (2010) 7118–7125.
[342] V.Vignal, C.Valot, R.Oltra, M.Verneau, L.Coudreuse, Analogy between the effects of a
mechanical and chemical perturbation on the conductivity of passive films, Corros. Sci. 44
(2002) 1477–1496.
72
CHAPTER 3
Near Boundary Gradient Zone and Sensitization Control in
Austenitic Stainless Steels
3.1 Introduction
Austenitic stainless steels have excellent resistance to uniform corrosion in most environments.
However, austenitic stainless steels can be prone to localized forms of corrosion depending on
their composition and thermal history [1–7], including intergranular corrosion (IGC), pitting
corrosion, crevice corrosion and stress corrosion cracking. This study focuses on sensitization,
which is known to lead to IGC and intergranular stress corrosion cracking (IGSCC).
Sensitization can occur, normally inadvertently, during welding or improper heat treatment;
resulting in precipitation of chromium (Cr) carbides at grain boundaries, with adjacent regions
developing a Cr depletion. If the Cr content of the depleted zone falls below ~12 weight percent,
the passive film that forms over such Cr depleted regions is less protective and susceptible to
corrosion. A microstructure containing Cr-carbides and regions of Cr depletion is termed
sensitized [2,4–16].
The sensitization of austenitic stainless steels is nominally assessed in a qualitative manner by
practice A of ASTM-A262. This involves electro-etching the specimen in a 10% solution of
oxalic acid at a current density of 1A/cm2. The developed microstructure is classified as either a
“step”(no chromium carbide/Cr depleted region), “dual” (no grain completely surrounded by
attacked chromium carbide/Cr depletion regions)or “ditch” (at least one grain totally surrounded
by attacked chromium carbides/Cr depletion regions). A test method that provides quantification
of degree of sensitization (DoS) is the electrochemical potentiokinetic reactivation (EPR) test.
The double loop -electrochemical potentiokinetic reactivation (DL-EPR) test is a rapid and
convenient test and using suitable experimental set up is amenable to be used for field testing.
Results of EPR tests have been correlated to IGC and IGSCC by numerous researchers [17,18].
The EPR test is primarily used to detect chromium depletion and in specially designed studies
73
has also been used to evaluate effects of thermal ageing, sigma phase and impurity segregation
[19–21].
Traditional techniques to mitigate sensitization include:(i) lowering the carbon content [3–
6,22,23],which is the reason for development of low-carbon stainless steels and is used in
particular for welded applications, (ii) solution annealing [3–6,24], by dissolving pre-existing
carbides,(iii) adding over-size solute atoms(example; cerium) that build-up stressed regions in
the matrix affecting diffusion of chromium [25], and (iv) adding stabilizing elements (titanium or
niobium) to stainless steels to precipitate carbon to avoid formation chromium carbide (M23C6).
M23C6containing chromium, iron and molybdenum form usually in the absence of stabilizing
elements[3–6,26]. The DL-EPR technique was shown to be effective to study the influence of
delta ferrite on degree of sensitization [27]. Effect of grain size on IGC also has been studied
extensively to improve sensitization resistance [23,28]. The DoS was shown to decrease with
increasing grain size in type 316L stainless steel [29]. In addition to the above, thermoelectric
power (TEP) technique has been shown to be effective to measure DoS for a duplex stainless
steel [30].
Mitigation of sensitization has also been proposed in the form of grain boundary engineering
(GBE) [28,31–43]. Grain boundaries can be distinguished based on their misorientations: low
and high angle boundaries [44,45]. A further classification [44–48]of the high angle boundaries
generalizes them as random and special. In general, the low angle and the special boundaries are
expected to have lower energies than the so-called random boundaries. The first attempt to
describe a special boundary is to define its coincidence site lattice (CSL) nature[44–49]. A CSL
number represents inverse of the common lattice points between two grains. For example, if all
lattice points are common (within a stipulated deviation angle: for example Brandon’s criterion
[49]): then it is called 1, the low angle boundary. If one in 3 points is common, the 3 is
constituted. It is important to point out at this stage that a typical axis-angle misorientation
information, as obtained from microtexture measurements, contains only three parameter [50].
The complete description of the grain boundary also requires information on the boundary plane,
and a total of five parameters [44,45,50]. The grain boundary definition from the CSL notation
alone thus remains incomplete. For example, 3 (60° <111>) tilt and twist boundaries were
reported to have significant differences in nature and energy [37,39,44]. In spite of such
74
limitations, CSL nature of the grain boundaries were used extensively to enforce sensitization
control [28,31–42,51,52].
It has been reported [41,53,54] that coherent twin boundaries do not form Cr-carbides, and also
been stipulated [39,55–58] that grain boundary Cr-flux may depend on the boundary
connectivity. Thus a combination of the relative presence and continuity of special boundaries,
where such boundaries are defined as grains having sharing lattice points, were shown [33–
38,41,55–58] to affect the degree of sensitization. More specifically, microstructures with very
high or very low concentrations of special boundaries constitute the so-called grain boundary
engineered austenitic stainless steels that provide resistance to sensitization[37,38]. There are
two possible routes to enforce such grain boundary engineering in austenitic stainless steels.
Extensive cold work followed by full annealing leads to high concentration of random
boundaries [37]. On the other hand, relatively light cold work followed by annealing at a
relatively low temperature provides a high fraction of special boundaries[34,36,37,51]. However,
studies on the second route are not definitive in regards to the possible role of ‘remnant’ cold
work on the sensitization behavior.
The time temperature sensitization (TTS) or isothermal transformation diagram is typically used
to demarcate the regions of sensitized and non-sensitized i.e. ‘step’, ‘dual’ and ‘ditch’
microstructure. The severity of sensitization is depends on temperature and holding time.
Various researchers have reported TTS diagrams for stainless steels including for SS 304L [59–
63]. From these TTS diagrams for a typical SS304L, it is clear that at 675º C, it would take 3 h to
20 h to obtain start of a ‘ditch’ structure, and the duration depends on the specific chemical
composition of the alloy [61]. This guided us to explore and establish the duration of heat
treatment at 675 ºC to obtain “medium” level of sensitization (‘dual’ microstructure).
Indeed, cold work is expected to affect sensitization [64–69], and it was identified, even in the
early ‘60s [22] that (i) carbide precipitation may be enhanced by cold work and (ii) the extent of
carbide precipitation may also be influenced by cold work. However, past empirical research
[64–67] appears to contain incomplete and often contradictory results. More importantly, efforts
were not specifically made to obtain direct correlations between signatures of cold work and
sensitization. Often, solution annealing is essential for some austenitic stainless steels products
and it introduces distortion. To control distortion, straightening (either skin pass rolling or stretch
75
straightening) is done. Straightening will allow remnant cold work to be present in as-supplied
austenitic stainless steels products. The understanding developed so far on the effect of prior cold
working affecting sensitization is that there is an increase in degree of sensitization and hence
IGC rates- with an increase in the degree of cold working. The cold work introduces
dislocations, initially more so near the grain boundaries. The increase in dislocation density at
grain boundaries causes easier precipitation of chromium carbides and/or may provide higher
diffusivities. Further cold work increases the dislocation density even in the matrix and it causes
precipitation to occur even intragranularly. The carbides start to nucleate in grain boundary if
degree of cold working is low and the carbides start to nucleate in grain interior as well during
higher degree of cold working [70–72]. It is well known that lowering carbon content (L grades)
is a way of avoiding/reducing sensitization, however, the present study deals with sensitization
behavior of cold (room temperature - RT) and warm rolled AISI 304L. The use of 304L in this
study allowed development of medium DoS facilitating establishment of grain boundary effects
of cold working after a controlled sensitization heat treatment. The bulk electrochemical
measurements and microtexture experiments are a way of linking local depth of attack with
orientation developments. It was felt that a combination of microtexture measurements and
subsequent post-corrosion surface profilometry (revealing local depths of attack) might provide
such a linkage. This was the motivation behind the study.
3.2 Experimental Methods
AISI 304L austenitic SS was used in this study. The Chemical composition of the alloy is listed
in Table 3.1. The 304L was obtained as an industrially hot rolled plate, solution annealed at 1050
°C for 1 h. As-received plates of 3 mm thickness were cold and warm rolled in a laboratory
rolling mill. Cold rolling was done at room temperature and for warm rolling a working
temperature of 300 ± 25 °C was maintained through inter-pass annealing. The following rolling
reductions were used: 5, 10, 20, 30, 40, 50 and 60% reduction in thickness. Rolled specimens
were then sensitized at 675 °C for 6 h. The sensitization heat treatment was selected to produce a
‘medium’ level of sensitization i.e. ‘dual’ microstructure/degree of sensitization less than 5% for
the as-received (0% rolled) plate. This allowed establishment of the effects of working on
sensitization.
76
The microhardness of the as-received, cold and warm rolled specimen was measured using a
Vickers indenter with a load of 300g. An average of 10 values was taken and reported. Vickers
microhardness was also measured after rolling and sensitization heat treatment.
Table 3.1 The chemical composition (in weight % alloying elements) of the AISI 304L
The double loop electrochemical potentiodynamic reactivation (DL-EPR) test, described in detail
elsewhere [19–21,73]. Polished specimens with a surface finish of 1 m were subjected to DL-
EPR tests in a deaerated solution of 0.5 M H2SO4 + 0.01 M KSCN at room temperature.
Deaeration was carried out 45 minutes prior to the commencement of the test, as well as during
the test by bubbling argon in the electrolyte. Prior to the DL-EPR tests, the surface specimens
were cathodically cleaned at a potential of -1000 mVSCE (millivolt with respect to saturated
calomel electrode) for 2 minutes in the deaerated test solution of 0.5 M H2SO4 + 0.01 M KSCN.
The potential was allowed to stabilize and it typically took 15 minutes. Care was taken to remove
all the bubbles on the specimen surface before staring the potential scanning. The forward scan
was started from a potential value of -450mVSCEto +300 mVSCE. The potential was immediately
reversed at + 300 mVSCE and the reverse scan were taken up to -450mVSCE. All the
potentiodynamic scans were carried out using a scan rate of 6 V/h. The DoS is calculated as per
equation 3.1
100 (3.1)
where Ir is the maximum current density during the backward (reactivation) scan, Ia is the
maximum current density during the forward (activation) scan. The DoS value measured for the
material with grain ASTM grain size number m is corrected for the DoS for the material with
ASTM grain size number using equation 3.2
(3.2)
C S P Mn Si Cr Ni N
304 L 0.029 0.010 0.025 1.78 0.20 18.01 8.21 0.037
77
where DoSm is the measured DoS for the material with ASTM grain size number m and DoSn is
the converted DoS for the material with ASTM grain size number n [17,25,74–76].
Specimens of as-received and cold rolled were also subjected to anodic polarization experiment
in the test solution of 0.5M H2SO4 +0.01M KSCN at scan rate of 6V/h. The anodic polarization
experiment was carried out for illustrating the region of passivity obtained in the DL-EPR test
solution. The anodic polarization test has been performed in the deaerated test solution of 0.5M
H2SO4+0.01M KSCN at a scan rate of 6V/h by using three-electrode setup (reference, auxiliary
and working electrode). The saturated calomel electrode (SCE) was used as reference electrode,
platinum electrode was used as auxiliary electrode and the test specimen as the working
electrode. Deaeration was carried out at least 45 minutes prior to the experiment and deaeration
was continued during the anodic polarization scan also. Before starting the experiment, a
cathodic potential of -1000 mVSCE was applied to the specimen for 2 minute. After this, it was
ensure that there were no bubbles on the test specimen surface and the specimen was allowed to
equilibrate in the test solution and the open circuit potential (OCP) was established and
monitored for 10 minutes before the start of anodic polarization test. The potential was scanned
from -500 mVSCE to 1200 mVSCE.
The hydrogen charging on the surface by applying cathodic potential and the fact that it may
alter the potential-current density response during the upward scan has now been mentioned in
the discussion part. Cathodic charging did enable attainment of Ecorr of -400 to -420 mVSCE that
is expected for austenitic stainless steels in the DL-EPR test solution. Charging at -1000 mVSCE
(i.e. a cathodic potential) would introduce hydrogen onto the surface of the austenitic stainless
steel. As the potential is subsequently swept towards anodic potentials, the hydrogen in the
material would take up electron and get oxidized and escape out. This extraneous reaction does
introduce some error in the current being reported at potentials around the Ecorr. However, the
error is too small and is insignificant once potentials move away from Ecorr into anodic direction.
Samples for electron backscattered diffraction (EBSD) were electropolished in an electrolyte of
80:20 methanol (CH4O) and perchloric acid (HClO4). A commercial StruersTM
Tenupol-5
electropolisher was used at 15 volts dc and at -20°C. EBSD measurements were made on a
78
FEITM
Quanta-3DFEG - scanning electron microscope. A TSL-OIMTM
EBSD system was used.
An area of approximately 2× 2 mm2 was covered, in each sample, by multiple EBSD scans.
Beam, video and step size (0.3 m) were kept identical between the scans. EBSD data above 0.1
confidence index (CI) was used for subsequent analysis. CI is a statistical measure of automated
indexing [77] and CI > 0.1 indicates more than 95% accuracy. The EBSD data were used for
obtaining standard image quality (IQ) maps [77]. IQ represented the number of detected Kikuchi
bands in the automated Hough transform [77]. Regions containing grain boundaries and high
dislocation density naturally had lower IQ values.
The grain boundaries with misorientation that falls between 1˚ and 10˚ classified as low angle
grain boundaries (LAGB) and more than 10˚ misorientations termed as random high angle grain
boundaries (HAGB). Grain boundaries with Σ ≤ 29 are defined as low energy boundaries known
as special boundaries. The angular resolution of EBSD 0.5-1˚ for classifying LAGB. For
identification of the special boundaries, the Brandon’s criteria (Δθ= 15ºΣ-1/2, where Δθ is
angular deviation from exact CSL) [49] was used.
EBSD data was used to obtain grain size. A grain was defined as a region bound by more than 5°
boundaries. From the area of such grains, and assuming circular geometry, average grain sizes
were obtained. A grain was defined by the continuous presence of >5° boundaries. Use of a
higher misorientation angle has a potential problem. Some of the prior deformation grain
boundaries are within 5°, and a higher grain definition angle often considers a grain cluster for
size/misorientation calculations.
In-grain misorientations were estimated as Kernel average misorientation (KAM), grain
orientation spread (GOS) and grain average misorientation (GAM).
KAM (i) = (3.3)
79
where i is an EBSD data point with x (6 in case of the hexagonal grid used in this study)
neighbors. ij is the misorientations, provided it did not exceed 5°, between points i and any of
its six neighbor j.
GOS = (3.4)
where gav is the quaternion average of a grain orientation. The grain contains N data points of gi
(i = 1 to N) orientations.
GAM= (3.5)
where i-j represents pairs of data points within a grain, nn number of nearest neighbor data points
and gi -gj are the corresponding orientations.
Misorientation developments were often used to define the developments in deformed
microstructures [78–89]. This study used three different parameters: KAM (equation 3.3), GOS
(equation 3.4) and GAM (equation 3.5). KAM represents average misorientation of defined set
of pixels [82,84,85,88–90]. It has been used effectively to represent local lattice distortions,
stored energy of cold work and relative presence of geometrically necessary dislocations[86,88].
GAM, average misorientation of all the data points in a grain, can be adopted [88] to reveal
possible differences in effective plastic strain between the grains. GOS quantifies the orientation
spread and has been used [87,88] to identify developments in orientation gradients and long
range misorientations in a deformed crystallite.
Further analysis of EBSD data is discussed later in the results. A white light interferometry
(WLI) based non-contact profilometer (VeecoTM
NT-9100) was used to measure depth of attack
on the test specimen after the DL-EPR test. As the EPR test is known to cause attack up to a
maximum of 3-4 m on austenitic stainless steel, the WLI, with its accuracy of measurement of a
few nm is a suitable technique to correlate with the results of DL-EPR test. The WLI signals
were collected, from the same area, before and after the DL-EPR tests. Depth/height information
was extracted and then exported to the EBSD data-set. In this process, there are two difficulties:
possible (i) shifts between the two scan areas and (ii) differences in step size and scan grids. To
80
solve this a custom program was made and then implemented successfully. The algorithm of this
program is included in the appendix 3.1.
3.3 Results
Figure.3.1a collates the data of anodic polarization. The increase in icrit values of cold rolled
specimens (30% &50%) compared to as-received indicates difficulty in achieving passivity-state.
icrit is defined as maximum current needed to achieve passivity during anodic polarization
experiment and icrit values for as-received and 30% and 50% cold rolled are 35.8 mA/cm2, 89.6
mA/cm2 and 108.5 mA/cm
2 respectively. The OCP vs. time graph is shown in figure 3.1b and
clearly indicates a shift in the OCP towards noble direction for the cold rolled specimens
compared to the as-received specimen. The OCP for the as-received specimen stabilized at -466
mVSCE and for 30% cold rolled and 50% cold rolled specimens at -436 mVSCE and -425 mVSCE
respectively. Figure.3.1c represents respective DL-EPR curves of 5% and 20% cold rolled plus
sensitized specimens and the measured DoS values are plotted in figure 3.1d. As shown in figure
3.1d, both high and low DoS values were noted. More specifically, high DoS values were noted
in the as-received specimen (DoS=4.78) and microstructures with fragmented grains (DoS
>10.25). However, deformed specimens without visible grain fragmentation showed low DoS
values (<0.20). The observation on grain fragmentation is summarized in figure.3.2. In the EBSD
image quality (IQ) maps, the structures without (figure 3.2a and figure 3.2b) and with (figure
3.2c) grain fragmentation are distinguishable. In particular, figure 3.2c showed local drops in IQ
and creation of new lattice curvatures. It needs to be noted that presence of dislocations and
corresponding inelastic scattering is expected to degrade IQ [77], while dislocation accumulation
is known [91] to cause grain fragmentation. The signatures of grain fragmentation were captured
from clear refinement in grain size. This is shown in figure 3.2d. As shown in the figure 3.2d, till
10% cold work number fraction of grains below 2 m (as estimated from standard linear
intercept method) was similar. After 20% cold rolling, however, there was a significant increase
(0.38 to 0.61 in the estimated number fraction). This was taken as a clear signature of grain
fragmentation. Such grain fragmentations were observed ≥ 20% and 50% reductions through
room temperature (RT) and 300°C rolling respectively. Post DL-EPR test, the surfaces are
shown in figure 3.3.
81
(a) (b)
(c) (d)
Figure 3.1 Results of electrochemical tests on 304L stainless steel - (a) Electrochemical
polarization of as-received and cold rolled (room temperature) SS 304L in DL-EPR test
solution (0.5M H2SO4+ 0.01M KSCN) at room temperature at a scan rate of 100 mV/min. (b)
measured OCP vs. time graph of as-received and cold rolled specimens, (c) DL-EPR curves of
5 and 20% cold rolled specimens after sensitization at 675°C,6 h, (d) degree of sensitization
(DoS) as a function of prior rolling reductions. Rolled samples, cold (RT - room temperature)
and warm (300°C) rolled, were sensitized at 675°C,6 h and then the DoS values were
established by DL-EPR test. Data points with fragmented grains, as indicated in figure 3.1d, are
enveloped in a dotted line.
82
(a) (b) (c)
(d)
Figure 3.2 Electron backscattered diffraction (EBSD)imagequality (IQ) maps of (a) 0%, (b)
5%,and (c) 20% cold rolled and then sensitized specimens. In (c) arrows are used to indicate
regions with visible grain fragmentation.(d) Quantification of grain fragmentation is presented as
number fraction of grains below 2 micron (as estimated from standard linear intercept method).
83
(a) (b) (c)
Figure 3.3 Scanning electron microscope (SEM) micrographs showing post DL-EPR surfaces of
(a) 0%, (b) 5% and (c) 20% cold rolled and then sensitized specimens. The images clearly
indicate regions of attack during DL-EPR test.
The figure 3.3 indicates severity and locations of the attacked regions in DL-EPR tests. In the
undeformed sample, figure 3.3a, the attack was mostly on the grain boundaries. Slight cold
working (5% reduction in thickness: figure 3.3b) clearly enforced a resistance to sensitization,
while 20% deformation enhanced the sensitization and corresponding severity of the attack
(figure.3.3c).
Cold rolled austenitic stainless steels partially transform to strain induced martensite (SIM) at
room temperature [92–94]. The monotonic increment of Vickers hardness value (see table 3.2 for
the ‘rolled’ material) indicates formation of the SIM. However, sensitization was reported [95]
to revert the martensite even after 350-500˚C annealing. Saturation magnetization values, as
estimated from VSM (vibrating sample magnetometer), confirmed this reversal in the present
study. In other words, the samples after the sensitization treatment did not contain SIM.
The difference in sensitization, in structures without visible grain fragmentation, was explored
further. As shown in figure 3.4, differences in DoS cannot be explained from the EBSD
estimated values of average grain size (figure 3.4a) and in-grain misorientations (figure 3.4b-d).
84
Table 3.2 Vickers hardness (microhardness with 300 g load) of the ‘cold rolled’ and ‘cold rolled
and sensitized’ specimens. The data were obtained from at least 10 random indentations.
The latter was generalized as KAM (figure 3.4b), GOS (figure 3.4c) and GAM (figure 3.4d).
None of these microstructural parameters had a monotonic correlation with the DoS values. The
nature of grain boundaries influence DoS [28,31,32,35–41,45,49,53–58,96], percentage DoS was
also plotted as a function of Σ1 and Σ3 boundary fraction. DoS did not have a direct correlation
with Σ1 (figure 3.5a), while the high DoS specimen clearly had the higher Σ3 fraction (figure
3.5b).
Higher Σ3fraction specimen exhibiting higher DoS is contrary to the conventional wisdom,
stronger presence of 60°<111> boundaries are expected [28,31,32,35–37,39,40,54] to provide
less chromium carbide precipitation and correspondingly lower sensitization.
Rolling reduction
percentage (%)
Vickers microhardness (HV)
Cold rolled Cold rolled and
Sensitized
0 241 201
5 280 210
10 312 257
20 347 289
30 374 291
40 406 310
50 423 326
60 436 354
85
(a) (b)
(c) (d)
Figure 3.4 The percentage DoS versus (a) average grain size, (b) kernel average
misorientation (KAM), (c) grain orientation spread (GOS) and (d) grain average
misorientation (GAM).Data represents measurements from microstructures without visible
grain fragmentation. Standard deviations from multiple EBSD scans are used to provide the
respective error bars. Measurement uncertainties, or in-grain misorientations typically
estimated in a fully recrystallized structure, are shown as dotted lines in (b)-(d).
86
It has been reported that chromium carbide precipitation at grain boundaries plays a major role in
increasing DoS for type 347 stainless steel [97]. As the grain boundary nature may also affect
DoS [28,31,32,35–41,45,49,53–58,96], the latter was compared to the estimated fractions of 1
and 3. As shown in figure 3.5a, 1 fraction did not appear to have a correlation with DoS. The
single data point of high 3 concentration was the undeformed sample. Deformation reduced the
3 fraction. This is expected. Plastic deformation is known [98] to reduce the relative presence
of twin boundaries. This brings in an interesting paradox.
(a) (b)
Figure 3.5 Percentage DoS versus estimated number fractions of (a) 1 and (b) 3 boundaries.
Data represents measurements from microstructures without visible grain fragmentation.
Standard deviations from multiple EBSD scans are used to provide the respective error bars.
Standard Brandon’s criteria ((Δθ= 15ºΣ-1/2
, where Δθ is angular deviation from exact CSL) [49]
was used for the identification of the CSL nature.
The only sample with high DoS was the one with noticeably higher 3 concentration (0.56±0.04
versus 0.42±0.04 to 0.31±0.04). Deformation imposed misorientation developments, thus
violating twin orientation relationships locally [98]. The specimens with reduced 3
concentration, but in the presence of in-grain misorientations, however, showed clear
improvements in sensitization control or lower DoS values.
87
Plastic deformation is expected to create a near boundary gradient of orientation and
misorientation [85,91,99,100]. This has been termed, earlier [85,100], as near boundary gradient
zone (NBGZ). An example of such NBGZ in a two-grain ensemble is shown in figure 3.6a. From
an identified grain center, profile vectors can be drawn to the grain boundaries (figure 3.6a).
From 100 of such vectors, made through an appropriate computer program, misorientation (
versus normalised distance (Xi: distance normalized by grain radius) plots were obtained, as
shown in figure 3.6b. The average gradient (Gi) and the normalized dimension ( Xi) of the grain
specific NBGZs were calculated as,
(3.6)
Xi= (3.7)
For each grain under consideration, 100 line vectors were used to estimate the NBGZ using the
algorithm described. The misorientation results presented in the work employed the point-to-
point misorientation along the given line vector. Employing these many line vectors ensured
sufficient statistical averaging of minor un-correlated fluctuations (potentially due to the creation
of geometrical as well as incidental dislocation boundaries) and brings out the clear patterns of
NBGZ formation. This process was repeated for at least 100 grains in each specimen. It needs to
be noted that for normalization (Xi/di) lengths of individual line vectors (and not the average
grain size was used.
The parameters ( 1, 2, X2 and X1) were estimated from the misorientation versus Xi plots
(see figure 3.6b) for the respective grains. Though no correlation was noted between DOS versus
Gi (figure 3.7a), Xi > 0.08 clearly provided significant resistance to sensitization or low DOS
values.
88
.
(a) (b)
Figure 3.6 (a) Representing near boundary gradient zone (NBGZ) in two neighboring grains
after 5% cold deformation and subsequent sensitization. Grey scale indicates orientation
gradient from the grain average (quaternion average) orientation. The geometric grain centers
were identified and profile vectors (till the grain boundaries) were drawn. (b) From 100 such
line vectors, misorientations (from the respective grain average orientations) versus
normalizeddistance (Xi = ) were drawn. This was done through a custom computer
program. NBGZs were then the derivative of the slope of misorientation profile exceeding1°.
Gradient (Gi) and normalized distances ( Xi) of such NBGZs were estimated from equations
(3.6) and (3.7) respectively.
89
(a) (b)
Figure 3.7 Percentage DoS versus average (a) gradient and (b) dimension of the gradient zone.
Data were obtained from microstructure without visible grain fragmentation. Standard
deviations are represented as error bars.
The macroscopic data from DL-EPR and WLI + EBSD tests indicate a possible correlation
between DoS and relative dimensions of NBGZ. Such data, though statistical, remain ‘limited’ at
best. It was decided to extend this data by taking local information into account. A scheme of
incorporating depth of attack during DL-EPR test (estimated by WLI) information into the
EBSD data set was adopted: a point discussed further in the appendix 3.1. The EBSD graphics,
and analysis, can thus be used to plot a typical grain structure with WLI estimated depth of attack
(figure 3.8a), and also to represent in the same grains the respective NBGZ (figure 3.8b)
information. Figure 3.8a contains information of depth of attack and grain morphology. The
depth of attack is measured from WLI after DL-EPR experiment in the same microstructural
locations. The distribution of near boundary gradient can be quantitatively related for one-to-one
correlation to grain average depth of attack. Grain average depth of attack as shown in figure
3.8a varies from 0 to 400 nm. Higher grain average depth of attack was found to be associated
with the regions characterized by lower extent of NBGZ (figure 3.8b).
90
(a) (b)
Figure 3.8 Relating grain average depth of attack and NBGZ for the same region (a)
Combining information from EBSD and WLI, (b) NBGZs, for 5% cold rolled specimens
In both solution-annealed and solution-annealed plus sensitized specimens, post-EPR depth
variations were noted between the grains and also within the same grain. It may be noted that
solutionizing did not fully eliminate signatures of the cold work or in-grain misorientations.
Naturally, all other microstructural parameters (e.g. in-grain misorientations) can also be
evaluated against the WLI data. As the WLI resolution was about 1 nm (in the z-direction) and 1
m (in x and y direction), a combined WLI+EBSD data can easily be used to bring out effects of
grain size (figure 3.9a), KAM (figure 3.9b), GOS (figure 3.9c) and GAM (figure 3.9d) on the
grain average depth of attack ( ). was estimated as,
(3.8)
91
(a) (b)
(c) (d)
Figure 3.9 Grain average depth of attack versus (a) average grain size, (b) kernel average
misorientation, (c) grain orientation spread and (d) grain average misorientation. Data were
obtained from 100 randomly selected grains from the 5% deformed plus sensitized sample.
Where is the WLI measured depth of attack at point ‘i’ in a grain containing a total of Ni
points. As shown in figure 3.9, there was no correlation between with grain size and
92
in-grain misorientations. also did not have a relation with the gradient (Gi) of the
NBGZ (figure 3.10a). However, a clear scaling between and Xi (relative dimension
of the NBGZ) was observed, as shown in figure 3.10b. Figures 3.9 and 3.10 involve 100
randomly selected grains in a sample subjected to 5% cold rolling followed by sensitization heat
treatment. It needs to be noted that similar patterns were also observed for the other
specimens/conditions as well.
(a) (b)
Figure 3.10 Grain average depth of attack, , versus (a) gradient (Gi) and (b) normalized
dimension ( Xi) of the gradient zone. Data were obtained from 100 randomly selected grains
from the 5% deformed plus sensitized sample.
93
3.4 Discussion
As depicted from Table 3.2, signatures of the plastic deformation remained on the deformed and
sensitized microstructures. Even the as-received (hot rolled, solution annealed and undeformed)
material was not strain-free. A drop in almost 40 DPH (diamond pyramid hardness): Table 3.2
on sensitization confirms this. A decrease in hardness was observed after all sensitization
treatments (Table 3.2) indicating recovery and limited recrystallization during sensitization.
However, the sensitization treatment did not fully eliminate all ‘remnant’ cold work.
The sensitized microstructures were classified as fragmented and non-fragmented. As shown in
figure 3.2d, the quantification of fragmentation was based on noticeable reduction in grain size.
All specimens with visible fragmentation also had high DoS (>10.25) values. A sharp contrast
emerged for deformed specimens without grain fragmentation (see figure 3.1d), they all had low
DoS (<0.20). As mentioned earlier, all these sensitized specimens did not contain strain induced
martensite. Hence the effect on DoS appears to originate from the non-fragmented deformed
microstructures. All fragmented structures were neglected for subsequent detailed
microstructural analysis.
The overall sensitization behavior did not appear to depend on the grain size or in-grain
misorientation (figure 3.9), for the conditions tested herein. Pre-sensitization plastic deformation
degraded the presence of 3 (figure 3.5b). Though this is explainable from the available
understanding [101] on twin-decay, the grain boundary nature clearly does not provide a
rationale for the improved resistance to sensitization (figure 3.5b). An explanation for both
macroscopic (figure 3.7b) and microscopic (figure 3.10b) resistance to sensitization appeared to
exist on the creation of the so-called near boundary gradient zone (NBGZ).
The control of grain boundary nature has long been presented as a viable possibility towards
improved sensitization resistance [28,31–41,51,55–58]. It has been shown [37,39], albeit
empirically, that clear improvements in resistance to sensitization is achieved at extreme
concentrations, both high and low, of special grain boundaries. Large cold work followed by
recrystallization annealing was shown to randomize grain boundaries [37], while low cold work
with annealing was reported [36,38,51] to enhance special boundary concentrations. The present
94
study brings out another possibility, namely, sensitization control through engineering the near
boundary gradient zone (NBGZ).
Plastic deformation of polycrystalline metallic material is known to cause large near boundary
shear strains [91]. In polycrystalline zirconium, deformed to only few percentage reductions by
plane strain compression, such shear can be one order of magnitude more than the imposed Von
Misses equivalent plastic strain. This creates the so-called near boundary gradient zone (NBGZ).
The NBGZ, a near boundary region of high misorientation, is a consequence of plasticity
difference between the neighboring crystals [77,85,91,99]. This is also a subject of large interest
in contemporary mechanics [85,91,99,100,102]. The present study shows that such interest on
NBGZ needs to extend to the sensitization of austenitic stainless steels as well. NBGZ is
expected to contain higher dislocation densities. This may lead to finer precipitation in the
specimens containing clear NBGZ. With or without such precipitates, the NBGZ is also expected
to enhance diffusivities by virtue of the pipe (dislocation) diffusion. Individually or together,
these are expected to create lower Cr-depleted zone. Though this study provided clear evidence
of reduced Cr-depleted zone in specimens with NBGZ, the actual mechanism for the remains to
be resolved.
The grain boundary engineering [28,31–41,55], best reflected in the percolation theory [56–58],
is expected to enhance [45] the grain boundary Cr flux when there is a high fraction of random
boundaries and thus reduce the Cr depletion zone. In case of a high fraction of special
boundaries, precipitation of the carbide at grain boundary itself is avoided/delayed resulting in an
apparently improved resistance to sensitization/susceptibility of IGC [36,38]. An alternate
phenomenology however, could be that faster diffusion and the diffusion short-cuts or high
diffusivity paths [102] can also be enabled through pipe diffusion and help to keep the Cr levels
higher than 12% even though Cr rich carbide precipitation has occurred. The NBGZs, and the
associated dislocations, appear to provide such diffusion short-cuts. Presence of NBGZ not only
provided an apparent immunity to overall sensitization (figure 3.3b), but also controlled the
extent of mesoscopic grain average depth of attack: NBGZ as an effective tool for sensitization
control. Thereby, localized attack of depth profile can be related to development of NBGZ with
the aid of WLI +EBSD combinations. It is acknowledged that grain boundaries have five degree
95
of freedom, and any further insights would necessarily require the transition towards three-
dimensional characterization of individual grains in order to develop a more complete model of
the microstructure-IGC response. Further, sensitization can be controlled by creating larger
NBGZ. This notion however, requires future studies in order to develop a more generalized
understanding.
3.5 Conclusions
Based on the systematic study relating remnant deformation (from cold and warm rolling) and
heat treatments to sensitization behavior of AISI 304L, the following conclusions are arrived.
The presence of visible grain fragmentation was shown to correlate with enhanced sensitization,
which is the result of enhanced precipitation of chromium carbides. The grain structures that
evolved from prior deformation and sensitization heat treatment, but with presence of near
boundary orientation/misorientation gradients (without grain fragmentation) indicated a
resistance to sensitization. The resistance was determined through macroscopic electrochemical
measurements, and in-grain mesoscopic average depth of attack. It was shown that grains with a
larger NBGZ suffered less attack and offered resistance to sensitization, i.e. sensitization control
through a near boundary gradient zone, which can also be stated as restricting the kinetics of
carbide precipitation via imparting unfavorable precipitate growth conditions from
microstructural control.
96
Appendix 3.1
where, , , and are the WLI values at points , , and
belonging to scan grind of WLI and the P is the interpolated WLI (depth) value at
data point which belongs to EBSD scan grid.
References
[1] M.H.Lewis, B.Hattersley, Precipitation ofM23C6 in austenitic steels, Acta.Metall.Mater. 13
(1965) 1159–1168.
[2] C.S.Tedmon, D.A.Vermilyea, J.H.Rosolowski, Intergranular corrosion of austenitic
stainless steel, J.Electrochemical.Soc. 118 (1971) 192–202.
97
[3] P.Marshall, Austenitic Stainless Steels Microstructure and Mechanical Properties, first ed.,
Elsevier applied science publishers, England, 1984.
[4] V.Cihal, Intergranular Corrosion of Steels and Alloys, first ed., Elsevier Applied Science
Publishers, New York, 1984.
[5] M.G.Fontana, Corrosion Engineering, first ed., Tata Mc-Graw Hill Edition, New Delhi,
1986.
[6] A.J.Sedriks, Corrosion of Stainless Steels, second ed., A Wiley-Interscience Publication,
New York, 1996.
[7] R.W.Revie, H.H.Uhlig, Corrosion and Corrosion Control: An introduction to Corrosion
Science and Engineering, fourth ed., Wiley Interscience, New Jersey, 2008.
[8] P.J.Gellings, M.A.de Jongh, Grain boundary oxidation and the chromium depletion theory
of intercrystalline corrosion of austenitic stainless steels, Corros.Sci. 7 (1967) 413–421.
[9] R.L.Fullman, A thermodynamic model of the effects of composition on the susceptibility
of austenitic stainless steels to intergranular stress corrosion cracking, Acta.Metall.Mater.
30 (1982) 1407–1415.
[10] E.Hall, C.Briant, Chromium depletion in the vicinity of carbides in sensitized austenitic
stainless steels, Metall. Trans. A. 15 (1984) 793–811.
[11] S.M.Bruemmer, L.A. Charlot, Development of grain boundary chromium depletion in
type 304 and 316 stainless steels, Scripta.Metall.Mater. 20 (1986) 1019–1024.
[12] T.M.Devine, The mechanism of sensitization of austenitic stainless steel, Corros.Sci. 30
(1990) 135–151.
[13] C. Stawstrom, M. Hillert, An improved depleted-zone theory of intergranular corrosion of
18-8 stainless steel , J.Iron.Steel.I. 207 (1969) 77–85.
[14] G.S.Was, R.M.Kruger, A thermodynamic and kinetic basis for understanding chromium
depletion in Ni-Cr-Fe alloys, Acta.Metall.Mater. 33 (1985) 841–854.
[15] S.M.Bruemmer, B.W.Arey, L.A.Charlot, Influence of chromium depletion on
intergranular stress corrosion cracking of 304 stainless steel, Corrosion. 48 (1992) 42–49.
[16] M.A.Gaudett, J.R.Scully, Distributions of Cr depletion levels in sensitized AISI 304
stainless steel and its implications concerning intergranular corrosion phenomena,
J.Electrochem.Soc. 140 (1993) 3425–3435.
98
[17] V.Kain, R.C.Prasad, P.K.De, Testing sensitization and predicting susceptibility to
intergranular corrosion and intergranular stress corrosion cracking in austenitic stainless
steels, Corrosion. 58 (2002) 15–37.
[18] V.Kain, Stress corrosion cracking (SCC) in stainless steels, in: V.S.Raja, T. Shoji (Eds.),
Stress Corrosion Cracking Theory and Practice., 1st ed.,Woodhead Publishing limited,
Cambridge, 2011, pp. 199–244.
[19] V.Cihal, R.Stefec, T.Shoji, T.Watanabe, V.Kain, Electrochemical potentiodynamic
reactivation: development and applications of the EPR test, Key. Engg.Mat. 261-263
(2004) 855–864.
[20] A.P.Majidi, M.A.Streicher, The double loop reactivation method for detecting
sensitization in AISI 304 stainless steels, Corrosion. 40 (1984) 584–593.
[21] British Standards Institution, Corrosion of metals and alloys- Electrochemcial
potentiokinetic reactivation measurement using the double loop method (based on Cihal’s
method), BS ISO 127 (2006).
[22] R.J. Bendure, L.C. Ikenberry, J.H. Waxweiler, Quantity and form of carbides in austenitic
and precipitation hardening stainless steels, T.Metall.Soc.AIME. 221 (1961) 1032–1039.
[23] R.Pascali, A.Benvenuti, D.Wenger, Carbon content and grain size effects on the
sensitization of AISI type 304 stainless steels, Corrosion. 40 (1984) 21–32.
[24] A.H.Advani, D.G. Atteridge, L.E.Murr, Solution annealing effects on sensitization of 316
stainless steels, Scripta.Metallurgica Mater. 25 (1991) 2221–2226.
[25] Y.Watanabe, V.Kain, T.Tonozuka, T.Shoji, T.Kondo, F. Masuyama, Effect of Ce addition
on the sensitization properties of stainless steels, Scripta.Mater. 42 (2000) 307–312.
[26] A.I.Z.Farahat, T.A. El-Bitar, Effect of Nb, Ti and cold deformation on microstructure and
mechanical properties of austenitic stainless steels, Mat.Sci.Eng.A. 527 (2010) 3662–
3669.
[27] G.Bai, S.Lu, D.Li, Y.Li, Intergranular corrosion behavior associated with delta-ferrite
transformation of Ti-modified Super304H austenitic stainless steel, Corros. Sci. 90 (2015)
347–358.
[28] R.Singh, S. Chowdhury, I. Chattoraj, Modification of sensitization resistance of AISI
304L stainless steel through changes in grain size and grain boundary character
distributions, Metall. Mater. Trans. A. 39 (2008) 2504–2512.
[29] S.X.Li, Y.N.He, S.R.Yu, P.Y. Zhang, Evaluation of the effect of grain size on chromium
carbide precipitation and intergranular corrosion of 316L stainless steel, Corros. Sci. 66
(2013) 211–216.
99
[30] N.Ortiz, F.F.Curiel, V.H.López, A.Ruiz, Evaluation of the intergranular corrosion
susceptibility of UNS S31803 duplex stainless steel with thermoelectric power
measurements, Corros. Sci. 69 (2013) 236–244.
[31] T. Watanabe, Approach to grain boundary design for strong and ductile polycrystals, Res.
Mech. 11 (1984) 47–84.
[32] G.Palumbo, K.T.Aust, Localized corrosion at grain boundary intersections in high purity
nickel, Scripta.Metall.Mater. 22 (1988) 847–852.
[33] K.T.Aust, U.Erb, G.Palumbo, Interface control for resistance to intergranular cracking,
Mat.Sci.Eng.A. 176 (1994) 329–334.
[34] P.Lin, G.Palumbo, U. Erb, K.T.Aust, Influence of grain boundary character distribution on
sensitization and Intergranular corrosion of alloy 600, Scripta.Metall.Mater. 33 (1995)
1387–1392.
[35] V.Y.Gertsman, S.M.Bruemmer, Study of grain boundary character along intergranular
stress corrosion crack paths in austenitic alloys, Acta. Mater. 49 (2001) 1589–1598.
[36] M. Shimada, H. Kokawa, Z.J. Wang, Y.S. Sato, I. Karibe, Optimization of grain boundary
character distribution for intergranular corrosion resistant 304 stainless steel by twin-
induced grain boundary engineering, Acta. Mater. 50 (2002) 2331–2341.
[37] D.N. Wasnik, V. Kain, I. Samajdar, B. Verlinden, P.K. De, Resistance to sensitization and
intergranular corrosion through extreme randomization of grain boundaries, Acta. Mater.
50 (2002) 4587–4601.
[38] H.Kokawa, M.Shimada, M.Michiuchi, Z.J.Wang, Y.S.Sato, Arrest of weld-decay in 304
austenitic stainless steel by twin-induced grain boundary engineering, Acta. Mater. 55
(2007) 5401–5407.
[39] N.Parvathavarthini, S.Mulki, R.K.Dayal, I.Samajdar, K.V.Mani, B.Raj, Sensitization
control in AISI 316L(N) austenitic stainless steel: defining the role of the nature of grain
boundary, Corros. Sci. 51 (2009) 2144–2150.
[40] R.Jones, V.Randle, Sensitisation behaviour of grain boundary engineered austenitic
stainless steel, Mat. Sci.Eng.A. 527 (2010) 4275–4280.
[41] C.Hu, S.Xia, H.Li, T.Liu, B.Zhou, W.Chen, N.Wang, Improving the intergranular
corrosion resistance of 304 stainless steel by grain boundary network control, Corros. Sci.
53 (2011) 1880–1886.
[42] V.Randle, Grain boundary engineering: an overview after 25 years, Mater. Sci. Technol.
26 (2010) 253–261.
100
[43] B. Sunil Kumar, B.S.Prasad, V. Kain, J. Reddy, Methods for making alloy 600 resistant to
sensitization and intergranular corrosion, Corros. Sci. 70 (2013) 55–61.
[44] V. Randle, The Role of Coincident Site Lattice in Grain Boundary Engineering, first ed.,
Ashgate Publishing, Cambridge, United Kingdom, 1996.
[45] B.Verlinden, J.Driver, I.Samajdar, R.D.Doherty, Thermo Mechanical Processing of
Metallic Materials, first ed., Pergamon Materials Series, Great Briton, 2007.
[46] D.H.Warrington, P.Bufalini, The coincidence site lattice and grain boundaries,
Scripta.Mater. 5 (1971) 771–776.
[47] D.H.Warrington, M.Boon, Ordered structures in random grain boundaries; some
geometrical probabilities, Acta Metall. 23 (1975) 599–607.
[48] D.A.Smith, R.C.Pond, Bollmann’s O-lattice theory; a geometrical approach to interface
structure, Int. Met. Rev. (1976) 61–74.
[49] D.G.Brandon, The structure of high-angle grain boundaries, Acta.Metall.Mater. 14 (1966)
1479–1484.
[50] O.Engler, V.Randle, Introduction to Texture Analysis: Macrotexture, Microtexture, and
Orientation Mapping, second ed., CRC Press, Florida, 2009.
[51] D.L.Engelberg, R.C.Newman, T.J.Marrow, Effect of thermomechanical process history on
grain boundary control in an austenitic stainless steel, Scripta. Mater. 59 (2008) 554–557.
[52] Y.Takehara, H.Fujiwara, H.Miyamoto, Special to general transition of intergranular
corrosion in Σ3{111} grain boundary with gradually changed misorientation, Corros. Sci.
77 (2013) 171–175.
[53] T.Thorvaldsson, G.Dunlop, Grain boundary Cr-depleted zones in Ti and Nb stabilized
austenitic stainless steels, J.Mater. Sci. 18 (1983) 793–803.
[54] E.A. Trillo, L.E. Murr, Effects of carbon content, deformation, and interfacial energetics
on carbide precipitation and corrosion sensitization in 304 stainless steel, Acta. Mater. 47
(1998) 235–245.
[55] V.Randle, Refined approaches to the use of the coincidence site lattice, JOM J. Min.
Metals Mater. Soc. 50 (1998) 56–58.
[56] D.B.Wells, J.Stewart, A.W.Herbert, P.M.Scott, D.E.Williams, The use of percolation
theory to predict the probability of failure of sensitized, austenitic stainless steels by
intergranular stress corrosion cracking, Corrosion. 45 (1989) 649–660.
101
[57] M.A.Gaudett, J.R. Scully, Applicability of bond percolation theory to intergranular stress-
corrosion cracking of sensitized AlSl 304 stainless steel, Metall.Mater.Trans.A. 25 (1994)
775–787.
[58] S.Tsurekawa, S.Nakamichi, T.Watanabe, Correlation of grain boundary connectivity with
grain boundary character distribution in austenitic stainless steel, Acta. Mater. 54 (2006)
3617–3626.
[59] N.Parvathavarthini, R.K.Dayal, Time temperature sensitization diagrams and critical
cooling rates of different nitrogen containing austenitic stainless steels, J.Nucl.Mater. 399
(2010) 62–67.
[60] R.K.Dayal, J.B.Gnanamoorthy, Predicting extent of sensitization during continuous
cooling from TTS diagram, Corrosion. 36 (1980) 104–106.
[61] D.Borah, Establishing the role of alloying additions in austenitic stainless steels on
susceptibility to IGC and IGSCC through time temperature sensitization diagrams, Homi
Bhabha National Institute, 2012.
[62] N.Parvathavarthini, R.K.Dayal, S.K.Seshadri, J.B.Gnanamoorthy, Continuous cooling and
low temperature sensitization of AISI Types 316 SS and 304 SS With different degrees of
cold work, J.Nucl.Mater. 168 (1989) 83–96.
[63] R.K.Dayal, N.Parvathavarthini, B.Raj, Influence of metallurgical variables on
sensitisation kinetics in austenitic stainless steels, Int.Mater.Rev. 50 (2005) 129–155.
[64] C.S.Tedmon, D.A.Vermilyea, D.E.Broecker, Effect of cold work on intergranular
corrosion of sensitized stainless steel, Corrosion. 27 (1971) 104–106.
[65] C.L.Briant, A.M. Ritter, The effect of cold work on the sensitization of 304 stainless steel,
Scripta.Metall.Mater. 13 (1979) 177–181.
[66] S.Pednekar, S.Smialowska, The effect of prior cold work on the degree of sensitization in
type 304 stainless steel, Corrosion. 36 (1980) 565–577.
[67] A.Bose, P.K.De, An EPR study on the influence of prior cold work on the degree of
sensitization of AISI 304 stainless steel, Corrosion. 43 (1987) 624–631.
[68] C.Garcia, F.Martin, P.De.Tiedra, J.A.Heredero, M.L.Aparicio, Effect of prior cold work
on intergranular and transgranular corrosion in type 304 stainless steels: quantitative
discrimination by image analysis, Corrosion. 56 (2000) 243–255.
[69] P.De.Tiedra, Ó.Martín, C.García, F.Martín, M.López, Effect of prior cold work on the
degree of sensitisation of welded joints of AISI 316L austenitic stainless steel studied by
using an electrochemical minicell, Corros. Sci. 54 (2012) 153–160.
102
[70] A.H.Advani, L.E.Murr, D.G.Atteridge, R.Chelakara, Mechanisms of deformation-induced
grain boundary chromium depletion (sensitization) development in type 316 stainless
steels, Metall. Trans. A. 22 (1991) 2917–2934.
[71] T.A.Mozhi, M.C.Juhas, B.E.Wilde, Modeling low temperature sensitization of austenitic
stainless steels, Scripta.Metall.Mater. 21 (1987) 1547–1552.
[72] P.G.Shewmann, Diffusion in Solids, second ed., Mc Graw Hill Co, New York, 1963.
[73] V.Kain, K.Chandra, K.N.Adhe, P.K.De, Detecting classical and martensite-induced
sensitization using the electrochemical potentiokinetic reactivation test, Corrosion. 61
(2005) 587–593.
[74] Japanese, Standards, Association, Method of electrochemical potentiokinetic reactivation
ratio measurement for stainless steels, JSA JIS G 0580. (1986) 1–4.
[75] S.Rahimi, D.L.Engelberg, T.J.Marrow, A new approach for DL-EPR testing of thermo-
mechanically processed austenitic stainless steel, Corros. Sci. 53 (2011) 4213–4222.
[76] L.Cihal, T.Shoji, V.Kain, Y.Watanabe, R. Stefac, EPR -A Comprehensive review, Sendai
Jap (2004) 9–20.
[77] R.A.Schwarzer, D.P.Field, B.L.Adams, M.Kumar, A.J. Schwartz, Present state of electron
backscatter diffraction and prospective developments, in: A.J. Schwartz, M. Kumar, B.L.
Adams, D.P. Field (Eds.), Electron Backscatter Diffraction in Materials Science, Springer
Science + Business media, New York, 2009: pp. 1–20.
[78] G.I.Taylor, The mechanism of plastic deformation of crystals, P. R. Soc.London. 145
(1934) 362–387.
[79] J.F.W.Bishop, R.Hill, A theory of the plastic distortion of a polycrystalline aggregate
under combined stresses, Philos. Mag. 42 (1951) 414–427.
[80] J.G.Sevillano, P.Van Houtte, E. Aernoudt, Large strain work hardening and textures, Prog.
Mater. Sci. 25 (1980) 69–134.
[81] B.Bay, N.Hansen, D.A.Hughes, D.Kuhlmann-Wilsdorf, Evolution of f.c.c. deformation
structures in polyslip, Acta.Metall.Mater. 40 (1992) 205–219.
[82] E.M.Lehockey, Y.P.Lin, O.E.Lepik, Mapping residual plastic strain in materials using
electron backscatter diffraction, in: Electron Backscatter Diffraction in Materials Science.,
Springer Science + Business media, New York, 2000: pp. 247–263.
[83] D.Raabe, M.Sachtleber, Z.Zhao, F.Roters, S.Zaefferer, Micromechanical and
macromechanical effects in grain scale polycrystal plasticity experimentation and
simulation, Acta.Mater 49 (2001) 3433-3441
103
[84] L.N.Brewer, D.P.Field, C.C.Merriman, Mapping and assessing plastic deformation using
EBSD, in: A.J. Schwartz, M. Kumar, B.L. Adams, D.P. Field (Eds.), Electron Backscatter
Diffraction in Materials Science, Springer Science + Business media, New York, 2009:
pp. 251–262.
[85] S.K.Mishra, P.Pant, K.Narasimhan, A.D.Rollet, I.Samajdar, On the widths of orientation
gradient zones adjacent to grain boundaries, Scripta. Mater. 61 (2009) 273–276.
[86] M.Calcagnotto, D.Ponge, E.Demir, D.Raabe, Orientation gradients and geometrically
necessary dislocations in ultrafine grained dual-phase steels studied by 2D and 3D EBSD,
Mat.Sci.Eng.A. 527 (2010).
[87] R.Yoda, T.Yokomaku, N.Tsuji, Plastic deformation and creep damage evaluations of type
316 austenitic stainless steels by EBSD, Mater. Charact. 61 (2010) 913–922.
[88] S.I.Wright, M.M.Nowell, D.P.Field, A review of strain analysis using electron backscatter
diffraction, Microsc.Microanal. 17 (2011) 316–329.
[89] L.Saraf, Kernel average misorientation confidence index correlation from FIB sliced Ni-
Fe-Cr alloy surface, Microsc Microanal. 17 (2011) 424–425.
[90] Y.Zhong, F.Yin, T.Sakaguchi, K.Nagai, K.Yang, Dislocation structure evolution and
characterization in the compression deformed Mn-Cu alloy, Acta. Mater. 55 (2007) 2747–
2756.
[91] N.Keskar, S.Mukherjee, K.V.M.Krishna, D.Srivastava, G.K.Dey, P. Pant, R.D.Doherty,
I.Samajdar, Quantifying the mesoscopic shear strains in plane strain compressed
polycrystalline zirconium, Acta. Mater. 69 (2014) 265–274.
[92] T.Angel, Formation of martensite in austenitic stainless steels: effects of deformation,
temparature, and composition, J. Iron Steel Inst. 177 (1954) 165–174.
[93] V.Seetharaman, R.Krishnan, Influence of the martensitic transformation on the
deformation behaviour of an AISI 316 stainless steel at low temperatures, J. Mater. Sci. 16
(1981) 523–530.
[94] V.Seetharaman, Deformation and martensitic transformation, Bull. Mater. Sci. 6 (1984)
703–716.
[95] V.Kain, K.Chandra, K.N.Adhe, P.K.De, Effect of cold work on low-temperature
sensitization behaviour of austenitic stainless steels, J.Nucl.Mater. 334 (2004) 115–132.
[96] P.M.Ahmedabadi, V.Kain, B.K.Dangi, I.Samajdar, Role of grain boundary nature and
residual strain in controlling sensitisation of type 304 stainless steel, Corros. Sci. 66
(2013) 242–255.
104
[97] K.Chandra, V.Kain, R.Tewari, Microstructural and electrochemical characterisation of
heat-treated 347 stainless steel with different phases, Corros. Sci. 67 (2013) 118–129.
[98] S.Mishra, K.Narasimhan, I.Samajdar, Deformation twinning in AISI 316L austenitic
stainless steel: role of strain and strain path, Mater Sci Tech. 23 (2007) 1118–1126.
[99] D.Raabe, Z.Zhao, S.J.Park, F.Roters, Theory of orientation gradients in plastically
strained crystals, Acta. Mater. 50 (2002) 421–440.
[100] S.Raveendra, A.K.Kanjarala, H.Paranjape, S.K.Mishra, S.Mishra, L.Delannay,
I.Samajdar, Strain mode dependence of deformationtexture developments:microstructural
origin, Metall. Mater. Transcations A. 42A (2011) 2011–2113.
[101] T.R.Bieler, P.Eisenlohr, C.Zhang, H.J.Phukan, M.A.Crimp,Grain boundaries and
interfaces in slip transfer, Curr. Opin. Solid State Mater. Sci. 18 (2014) 212–226.
[102] D.A.Porter, E.A.Easterling, M.A. Sherif, Phase Transformations in Metals and Alloys,
third ed., CRC press, Noida, 2014.
105
CHAPTER 4
Plastic Deformation and Corrosion in Austenitic Stainless Steels:
A Novel Approach through Microtexture and Infrared
Spectroscopy
4.1 Introduction
The nature and stability of surface films play a key role in determining the corrosion resistance
of austenitic stainless steels [1–7]. The surface films are typically metallic oxides (chromium
rich) and may include hydroxides [3,8,9]. Chromium oxide formation provides passivation,
while local breakdown – arising from the microstructure, inclusions or from surface film defects
- creates activation [1,10–13]. It is nowadays widely acknowledged that film thickness,
stoichiometry, microstructure and electronic properties are of critical importance in determining
the extent of passivation [14–16]. The microstructure of the metallic substrate is also critically
relevant [17,18]. For example, features of the metallic substrate may affect the state of stress and
the conduction properties of the film [19–21]. The formation and breakdown of the passive film
are mainly controlled by ionic and electronic transport processes [17,22–24], and dislocations in
the metallic substrate may affect conductivity. However generally speaking, with the exclusion
of local inclusions (such as sulphides) or Cr-depletion from so-called sensitization, the literature
relating the functional substrate microstructure and the resultant nature/stability of the passive
film remains limited [17,18,25–27].
Passive films upon austenitic stainless steels are typically a few nanometers in thickness [7,28–
30]. This makes their quantification relatively challenging. The characterization of the passive
film may involve indirect electrochemical studies: typically potentiodynamic polarization [31–
36], electrochemical impedance spectroscopy (EIS) and Mott-Schottky analysis [37–39]. The
potentiodynamic polarization can qualitatively indicate activation/passivation behavior while
Mott-Schottky analysis allows probing of the semiconductive nature of the film. Of note with
respect to prior studies, Mott-Schottky analysis has been used to relate substrate microstructure,
grain size and strain induced martensite formation (SIMF) with acceptor/donor defect densities
106
in the passive film [38–40]. The study of passive films also lends itself to direct characterization.
Such efforts, in the literature, involve electron spectroscopy for chemical analysis (ESCA) [41–
44], auger electron spectroscopy (AES) [45–47] and secondary ion mass spectroscopy (SIMS)
[48–51]. Though Raman spectroscopy has been used [52–56], there is a notable absence of the
use of infrared spectroscopy. Absorption, or transmission, of the infrared spectrum can be
studied as a function of wavelength in infrared spectroscopy [57]. The technique involves use of
the thermal spectrum originating from vibrations and accompanying rotational absorption bands.
This has been used for routine characterization of oxides [58–60], including characterization of
oxide films [61,62]. However, use of infrared spectra in electrochemistry or corrosion is less
common, the authors came across to only one such example [63]: relating the infrared signal to
possible corrosion products. The use of infrared spectroscopy therefore is therefore a novel
aspect of the present study.
Plastic deformation is a simple means for modifying microstructures in a metallic substrate.
Other than changing the grain shape (and possibly the grain size), plastic deformation increases
dislocation densities and may result in substructures depending on the applied strain. In
austenitic stainless steels, plastic deformation is also expected to generate strain induced
martensite [64–69]. Such microstructural modifications are expected to alter the electrochemical
behavior [70–77], namely the nature/stability of resultant oxide films. This study aims to relate
microstructural features in a stainless steel substrate with the characteristics of the attendant
oxide film via a combined electron backscattered diffraction (EBSD) and post-potentiodynamic
polarization oxide film quantification using Fourier transform infrared spectroscopy (FTIR)-
imaging.
4.2 Experimental Methods
Three grades of austenitic stainless steels were employed in this work. These were designated as
alloys A, 316L and 304L according to Table 4.1. Alloy A, is marketed by Sandvik®. The alloy is
sold under the trademark SanicroTM
28 and has been referred to as alloy A in this thesis. It is
noted that alloy ‘A’ is rich in Cr, Ni, contains Cu and Mo and has no added N. The samples of all
107
the three grades (alloy A, 316L and 304L) were supplied in the fully recrystallized condition, and
had average grain sizes of 150, 70 and 30 µm, respectively Specimens were deformed at room
temperature (25ºC). Two different types of deformation were used, (i) laboratory cold rolling to
true strains of 0.26 and 0.58, and (ii) split channel plane strain compression [78–80] to true
strains of 0.04 and 0.09. It is noted that the split channel plane strain compression technique
allows direct observations of the deformed microstructure development.
After laboratory rolling, microstructural and FTIR- imaging measurements were made at the
mid-thickness section of the rolling plane (containing the rolling and transverse directions). For
split channel die specimens, the geometric constraints enforced observations on the long-
transverse section (containing rolling and normal directions). Measurements were taken at the
mid-thickness section. Past studies [78–82] had shown effective use of this technique to observe
the same grain structures before and after plastic deformation.
Table 4.1 The chemical composition (in wt% alloying elements) of the three austenitic stainless
steel grades.
Deformed specimens were tested using anodic potentiodynamic polarization. Mounted
specimens were prepared with a suitable electrical connection and metallographically polished to
one-micron diamond finish. All samples (for both electrochemical properties and EBSD
(electron backscattered diffraction)) were then electropolished. Electropolishing ascertained
absence of near surface deformed material. Samples were electropolished in an electrolyte of
80% methanol (CH4O) and 20% perchloric acid (HClO4). Electropolishing was carried out at -
20ºC and 15 V using a StruersTM
Lectropol-5.
Before electrochemical measurements, lacquer was applied to help ensure the absence of crevice
corrosion between the mount and the specimen. A Gill-AC Potentiostat (ACMTM
instruments)
was used along with a conventional 3 electrode cell configuration employing a saturated calomel
C S P Mn Si Cr Ni N Cu Mo
Alloy A 0.020 0.015 0.025 2.0 0.60 27.00 31.00 0 1.09 3.6
316L 0.020 0.020 0.010 1.0 0.38 16.25 10.73 0.10 0.03 2.37
304L 0.029 0.010 0.025 1.78 0.20 18.01 8.21 0.037 0.2 Trace
108
reference electrode (SCE) and a platinum counter electrode. Anodic potentiodynamic
polarization tests were conducted following the attainment of a stable open circuit potential
(OCP) in a deaerated test solution of 0.5M H2SO4. Anodic potentiodynamic polarization scans
were conducted at a scan rate of 20 mV/min at 26˚C and the test solution was continuously
deaerated during the potentiodynamic polarization. The scans were terminated at 750 mV versus
the reference (SCE). This allowed samples of known substrate microstructure to develop thin
passive Cr2O3 films for subsequent study. The specimens were immediately disconnected and
removed after anodic potentiodynamic polarization and rinsed with water and acetone. Optical
microstructures were observed after anodic potentiodynamic polarization test.
The EBSD measurements were carried out using an FEITM
Quanta-3d FEG -SEM and a TSL-
OIMTM
EBSD system; parameters such as step size and beam conditions were kept identical
between all scans. The EBSD data is reported as image quality (IQ) maps. The IQ represents the
number of Kikuchi bands after the Hough transform, and has been shown effective in identifying
grain boundaries and substructure formation [83–86]. The data above a 0.1 confidence index (CI)
were used for further analysis. It is to be noted that CI is a relative measure of the automated
indexing [83–86]. Data above 0.1 CI represent more than 95% accuracy. A grain was defined as
having a boundary if the continuous presence of > 5° misorientation was recorded, from which
the grain size was estimated. Misorientation from grain to grain was presented as grain average
misorientation (GAM) and kernel average misorientation (KAM). GAM represents average
point-to-point misorientation in a grain, while KAM was used to estimate local misorientation
around a measurement point.
The specimen surface films were characterized with FTIR-imaging. For FTIR-imaging, a
BrukerTM
300-Hyperion unit was used. FTIR-imaging background was obtained in the air. This
was then subtracted from the actual FTIR-imaging measurements. Cr2O3 provided an FTIR-
imaging peak at the approximate wavenumber of 660 cm-1
[58]. Area under this peak was
considered to represent relative presence of Cr2O3. Area under the peak was estimated by
standard integration (and then background subtracted) using a commercial software Opus6.5TM
.
109
Vickers hardness measurement was carried out in micorhardness tester in Leco TM
LM 300 AT.
It used diamond pyramid indenter. Microhardness (Vickers) of as-received and deformed
specimens was measured with an applied load of 300 g and dwell time is 10 s. Microhardness of
the deformed specimens were determined from at least 10 measurements. The martensite
percentages were measured from saturation magnetization in a Quantum DesignTM
vibrating
sample magnetometer (VSM). Details regarding measurement of martensite percentage using
VSM method is covered elsewhere [87–89].
The surface oxides of the post-anodic potentiodynamic polarization samples were also
characterized by time of flight secondary ion mass spectrometry (ToF-SIMS) using a Physical
ElectronicsTM
instrument. For sputtering 3 keV Cs+
ions (180 nA) were used, while detection was
through Ga+ (30 keV, 19 nA) ions. The respective raster sizes were 700 m
2 and 50 m
2.
Operating parameters (beam current and raster size) were kept identical between the scans. Cr
mass 51.94 amu was selected and positive ions were used. After sputtering by Cs+, crater depths
were measured in Dekta KXT BRUKERTM
stylus-based profilometer. The vertical resolution of
the profilometer was 1Å. The depth measurements were repeated at five different crater locations
and average crater depth of 67.53 nm (with 2% measurement uncertainty) was measured over
sputtering time of 680 s. Therefore, the sputtering rate was 0.09 nm/s. Appropriate cleanliness
was maintained in generating/analyzing the ToF-SIMS specimens. Spectral data acquisition and
post-processing were accomplished using WinCadenceNTM
software.
4.3. Results
The anodic potentiodynamic polarization curves for specimens tested are shown in figure.4.1.
Parameters of interest are shown schematically in figure 4.1a. Ecrit is respective value of
maximum voltage needed to induce passivity during anodic potentiodynamic polarization and ip
represents the passivation current and is the current measured at 200 mVSCE. Since the focus in
the present study is to relate microstructure with the determined properties of the passive film,
experiments related to pitting and repassivation were not carried out.
110
The anodic potentiodynamic polarization curves (figure 4.2b-d) clearly exhibit different
characteristics between the as received and the cold-rolled (i.e. plastically deformed) specimens.
(a) (b)
(c) (d)
Figure 4.1 (a) Schematic of a anodic potentiodynamic polarization curve showing Ecorr,
ip, icrit and Ecrit. Anodic potentiodynamic polarization curves after progressive plane strain
compression (true strains of 0.09,0.26,0.58) in (b) alloy A, (c) 316L and (d) 304L.
As indicated in figure 4.1 and collated in figure 4.2, both icrit and ip increased with plastic strain.
Change in anodic potentiodynamic polarization parameters with strain listed in Table 4.2 A low
value of icrit and ip indicates quick formation of passivity for the as-received specimens [90]. The
increases in the respective currents, reflecting difficulties in achieving passivity due to
111
developments in deformed microstructure, were non-linear. They also differed between the
grades. As-received alloy A had passivation (i.e. low values of icrit and ip). However, this
behavior changed rapidly with cold work. More specifically, icrit and ip increased 11 and 23 times
respectively in alloy A with deformation. These were significantly higher than respective
increases of 5 and 2-7 times in 316L and 304L. To appreciate differences in anodic
potentiodynamic polarization with cold work further, detailed micro-textural measurements were
carried out.
(a) (b)
Figure 4.2 (a) icrit and (b) ip (as in figure 4.1) for three different grades as a function of true
strain. In the respective figures, the extent of increase in icrit and ip are indicated for the alloy A,
316L and 304L.
112
Figure 4.3 shows the post-deformation microstructural developments of the specimens studied.
EBSD IQ maps (figure 4.3a) reveal strain localizations at, and after, a true strain of 0.26. At
different stages of plastic deformation, strain localizations were distinguished from EBSD
images as new lattice curvatures inside the prior deformation grain structure. Plastic deformation
reduced the average grain size (see figure.4.3b) and also increased the GAM (see figure 4.3c).
However, as indicated in figure 4.3b and figure 4.3c, refinement in grain size and an increase in
misorientation were comparable between the grades. Other than dislocation substructure,
deformation in austenitic stainless steels can introduce strain induced martensite [64–66]. As
shown in figure 4.4a, the deformation resulted in hardening (see figure 4.4a) and SIMF (see
figure 4.4b). The maximum hardening as well as SIMF was observed in 304L, while alloy A did
not have SIMF. These observations are further deliberated latter in the discussion in terms of the
observed degradation in passivation behavior (see figure 4.2).
It was decided to characterize the compositional gradients in the respective passive films. As in
figure.4.5, Cr-O surface films were typically a few nanometers in thickness and had clear
gradients of Cr concentration. The as-received state of all the grades had exhibited strong
chromium oxide surface films than that formed on the deformed specimens. and area under
chromium oxide was estimated. The thickness of the passive films reduced with prior plastic
strain in alloy A (see figure.4.5a) from 2-3 nm for the as-received specimen to 1-2 nm for the
deformed alloy A. However, such changes were less appreciable in 316L and 304L (see figure
s.4.5b and 4.5c). Though ToF-SIMS has an excellent depth resolution, combinations of film
roughness and imposed etching rate provide practical difficulties in relating substrate
microstructure with the local nature (thickness and Cr concentration gradient) of the passive
films. FTIR-imaging provided an easier alternative. FTIR-imaging provided the characteristic
Cr2O3 peak at approximately 660 cm-1
wave number [58]. At different levels of plastic
deformation, and for different microstructural features, areas under the Cr2O3 films were thus
measured. FTIR-imaging data are collated in figure.4.6. The figure shows 100 data points (area
under Cr2O3 peak) plotted vertically one over the other, for different strains and grades. In the
same figure, the average values and respective standard deviations are also marked. It is
important to appreciate possible measurement uncertainty.
113
(a)
strain Alloy A 316L 304L
0
0.09
0.26
0.58
100 µm
114
(b) (c)
Figure 4.3 (a) EBSD image quality (IQ) maps of the prior and post deformation specimens. (b)
Average grain sizes and (c) grain average misorientions were plotted as a function of true strain.
In (b) and (c) times decrease/increase in average grain size and grain average misorientation are
indicated for the respective grades. Error bars in (b) and (c) represent standard deviations from
multiple EBSD scans.
115
(a)
(b)
Figure 4.4 (a) Hardness and (b) percentage martensite versus true strain. Error bar in (a)
represents standard deviations from multiple measurements.
116
Table 4.2 Change in anodic potentiodynamic polarization parameters (ip and icrit) with strain.
These are shown for all three grades (alloy A, 316L and 304L) and respective strain increments
of 0-0.09, 0.09-0.26 and 0.26-0.58.
ε increment Quantity Alloy A 316L 304L
0-0.09
icrit
100 247 121
ip
77 80 226
Average
grain
size
11 5 15
GAM 89
58 84
SIMF 0 100 100
0.09-0.26
icrit
9 5 37
ip
68 3 73
Average
grain
size
42 1 7
GAM 35 82 44
SIMF 0 3 64
0.26-0.58
icrit
397 46 60
ip
40 2 27
Average
grain
size
0 75 25
GAM 10 29 10
SIMF 0 26 57
117
Table 4.3 Integration of chromium oxide (Cr2O3) signal intensity for cold rolled alloys.
For this, two characteristic FTIR-imaging spectra (transmittance versus wavenumber) are
included in figure 4.6b. A FTIR-imaging spectra or difference between two spectra was
noticeably till second decimal place. The trends deliberated need to be viewed under such
uncertainty. In alloy A, the degradation in Cr2O3 films with progressive plastic strain (figure
4.6a) was clear. However, no such clear trend was apparent for 316L and 304L. In all these
grades, however, the relative presence of Cr2O3 films differed noticeably with substrate
microstructure. This point is discussed further in the next paragraph.
As shown in figure 4.7a, split channel die plane strain compression enabled direct observations
of surface grains on progressive plastic deformation [78–82]. More specifically, post
deformation grains developed slip bands and local misorientation. These samples were polished
Strain 0 0.09 0.26 0.58
Alloy
A
Average 0.341 0.082 0.056 0.023
Non strain localized --
--
0.062 0.045
strain localized --
--
0.023 0.011
316L
Average
0.081
0.036
0.015
0.012
Non strain localized -- -- 0.030 0.021
Strain localized -- -- 0.005 0.007
Strain
localized+Martensite --
0.191
0.211
0.063
304L
Average 0.041 0.034 0.003 0.005
Non strain localized -- -- 0.014 0.022
Strain localized -- -- 0.001 0.001
Strain
localized+Martensite --
0.093
0.082
0.041
118
and then passivated by scanning specimens potentiodynamically from OCP to nobel direction till
750 mVSCE. Areas under the respective Cr2O3 peaks were measured with respect to local
(a) (b)
(c)
Figure 4.5 Chromium concentration (in wt%) versus depth. Data were obtained from the
respective post-passivation specimens of (a) alloy A, (b) 316L, and (c) 304L.
119
misorientation. Figure 4.7b represents this data. It appears that the relative presence of Cr2O3
film (or area under the FTIR-imaging peak corresponding to Cr2O3) was affected by kernel
average misorientation (KAM): a steep drop in area under Cr2O3 peak till an approximate KAM
of 0.6°. However, at higher KAM the relative presence of the Cr2O3 peak appeared insignificant.
EBSD plus FTIR-imaging thus provided an effective (and novel) means for characterizing
relative intensity of Cr2O3 film at different substrate microstructure.
(a)
120
(b)
Figure 4.6 (a) FTIR-imaging estimated area under Cr2O3 peak as a function of true
strain of three grades of austenitic stainless steels. Multiple measurements were taken in
the three grades after progressive deformation. The data include ‘all’ measurement points
and also their respective average and standard deviation (as error bars). At least 100
measurement points were taken in each case. (b) Two characteristic FTIR-imaging
spectra (transmittance versus wavenumber) are also included as reference.
(a)
121
(b)
Figure 4.7 (a) Direct observation on progressively plane strain compressed alloy A. This is
shown with EBSD IQ maps for true strains of 0, 0.04 and 0.09. (b) after establishing KAM
measurements in specific grains from EBSD, KAM is correlated to area under Cr2O3 peaks from
FTIR-imaging for the same grains.
This is shown further in figure 4.8 for 316L subjected to a true strain of 0.26. For easy reference,
the figure.4.8 shows measurements at three different locations. Region(s) without strain
localizations had lower KAM (0.46° versus 0.7°) and higher Cr2O3 (0.05 versus 0.006 cm-1
)
intensity. However, strain localized regions with clear presence of SIMF showed high KAM
(0.86°) and strong FTIR-imaging signal (0.21 cm-1
). Figure 4.9 summarizes FTIR-imaging data
from all samples in reference to the substrate microstructure. This brings out clear, and
reproducible, correlation between substrate structure and the relative presence of Cr2O3 films.
122
Figure 4.8 EBSD plus FTIR-imaging data in 316L after a true strain of 0.26. Area under Cr2O3
peak (and corresponding FTIR-imaging spectra) and EBSD estimated KAM values are shown at
three locations: (i) without strain localization (KAM = 0.45˚and FTIR = 0.05 cm-1
), (ii) with
strain localization (KAM = 0.70˚ and FTIR = 0.006 cm-1
) and (iii) with strain localization plus
SIMF (strain induced martensite formation) (KAM = 0.86˚ and FTIR 0.21cm-1
). SIMF is also
shown through EBSD phase map.
Strain localizations degraded the intensity of Cr2O3. However, presence of SIMF in strain
localized regions clearly provided enhanced FTIR-imaging signal.
4.4. Discussion
The relative presence of the passive Cr-oxide film holds the key to corrosion resistance of
stainless steels [1–9]. Naturally, the characterization of such films has drawn significant
123
scientific attention through studies ranging from involved electro-chemical techniques [31–39] to
specialized analytical tools [41–47,50,51]. However, this is the first of such studies that used
FTIR-imaging signal as a relative measure of the Cr2O3 presence.
Figure 4.9 Average FTIR-imaging estimated area under Cr2O3 peak as a function of true stain of
three grades of austenitic stainless steels. This is given for different microstructural features in
the three alloys at different stages of plastic deformation. The error bars represent standard
deviations from multiple measurement points.
124
The combined microtexture and FTIR-imaging measurement is clearly a ‘niche’, which has been
established in this study with careful experimentation. Plastic deformation affects corrosion
performance: difficulty in achieving passivity in the alloy A being more extensive (see figures
4.1-4.2). All the three grades had similar trends in microtexture evolution (see figure 4.3).
However, alloy A did not have strain induced martensite formation, see figure.4.4. It is
important, at this stage, to deliberate on the deformation induced microstructure evolution and its
possible role on corrosion performance. Deformation in low stacking fault energy face centered
cubic (fcc) material (such as the austenitic stainless steels used in the present study) leads to
dislocation domains [91–93],crystallographic and non-crystallographic micro-bands [91,94–97]
and SIMF [64–67,69,98–102].
This study did not try to distinguish between different deformation heterogeneities, but broadly
classified them as strain localizations and SIMF. The former was easily identified in the EBSD
IQ maps (see figure 4.3a -4.8). As the IQ represents the number of detected Hough peaks, the
regions of intense inelastic scattering or enhanced dislocation presence appeared ‘dark’. It was
relatively straightforward to evaluate EBSD structures and identify regions which were strain
localized. The strain localized regions had a higher misorientation and lower FTIR-imaging
signal. Some of these strain localized regions also had presence of SIMF. The martensite is
expected to nucleate [66,69,103–107] on the strain localizations. Identification of such SIMF is
not simple. For reliable phase identification at least 5 Hough peaks plus high resolution EBSD
was used. Interestingly, wherever EBSD identified such SIMF, the FTIR imaging signal was
significantly stronger (see figure.4.8). In other words, clear microstructural evidence (see figure
4.9) indicated a stronger presence of post-passivation Cr2O3 film on the locations containing
SIMF.
Published literature, in general, attributed SIMF with reduced corrosion performance [70,108–
110]. More specifically, bulk measurements overwhelmingly indicated that deformation leading
to SIMF reduce corrosion performance [70,74,110,111]. This has been attributed to the selective
dissolution of martensite [74]. Recent literature, however, indicate other possibilities as well.
Corrosion performance was shown to depend on the grain size, both size and distribution of
125
SIMF playing a critical role [74]. Sub-micron grain structure with SIMF offers significant
improvements in pitting resistance[112]. It has been argued that both dislocation pile-ups and
SIMF may contribute to pitting corrosion [108,109]. It has been also been proposed [108] that
dislocation pile-ups affect pitting, while SIMF plays an indirect role in stabilizing such pile-ups.
It appears that the amount of SIMF does not affect the corrosion performance [108,109,113]. It
has been argued [17,18] that structure of the metallic substrate affects the passive films, and
SIMF was stipulated to provide a ‘more defective oxide’. Summarizing, it is fair to admit that the
conventional wisdom [70,108–110] on the detrimental aspects of SIMF on corrosion
performance in austenitic stainless steels is based primarily on the bulk measurements. Though
the need for ‘smaller scale analysis’ to decouple effects of different microstructural features was
articulated [108], the published literature has largely been silent on that account.
This combination of microtexture measurements and FTIR-imaging is where the scientific
novelty of this study emerged. The FTIR-imaging plus EBSD data established stronger presence
of Cr2O3 films on substrate locations containing SIMF. The scientific rationale for such an
observation needs to be rationalized. The data, however, remain statistical and reproducible. The
thesis thus brings in a novel approach to experimental corrosion studies in stainless steels, a
combined approach of substrate microtexture measurement and post-passivation location-
dependent characterization of the Cr2O3 films through infrared spectroscopy.
4.5. Conclusion
Three grades of austenitic stainless steel, with key compositional variables, were subjected to
progressive plane-strain compression. Post-deformation corrosion performance was then
evaluated. Following are the main conclusions:
1. The grades were alloy A (Cr and Ni rich, N-free, Cu + Mo), 316L (containing N) and
304L. They had similar developments in deformed microstructures. However, alloy A did
not have SIMF.
2. Deformed led to deterioration of bulk corrosion performance: as revealed by
electrochemical polarization tests, and respective numerical values of icrit and ip. The
deterioration in corrosion performance was the maximum in alloy A, the grade without
126
SIMF. This raises a question on the conventional notion that SIMF is bad for corrosion
performance.
3. A combination of EBSD and FTIR-imaging enabled evaluation of the microstructure and
the location-dependent relative presence of the Cr2O3 surface film. Direct observation
showed a clear correlation between local misorienation and the prevalence of the passive
film. However, similar regions with the clear presence of SIMF had a significantly higher
level of Cr2O3 detected.
4. This thesis thus established microtexture measurement plus infrared spectroscopy as an
approach to probe the passivation tendency of different microstructural features. It also
showed, with direct observations and statistical data, that SIMF actually leads to
stability/retention of Cr2O3 film.
References
[1] H.J.Engell, Stability and breakdown phenomena of passivating films, Electrochim. Acta.
22 (1977) 987–993.
[2] I.Olefjord, The passive state of stainless steels, Mater. Sci. Eng. 42 (1980) 161–171.
[3] I.Olefjord, B.O.Elfstrom, The composition of the surface during passivation of stainless
steels, Corrosion. 38 (1982) 46–52.
[4] A.R.Brooks, C.R.Clayton, K.Doss, Y.C.Lu, On the role of Cr in the passivity of stainles
steel, J. Electrochem. Soc. (1986) 2459–2464.
[5] N.Sato, Toward a more fundamental understanding of corrosion processes, Corrosion. 45
(1989) 354–368.
[6] N.Sato, The stability of localized corrosion, Corros. Sci. 37 (1995) 1947–1967.
[7] C.Clayton R,, I. Olefjord, Chapter 7, Passivity of Austenitic Stainless Steels, in: P. Marcus
(Ed.), Corrosion Mechanism in Theory and Practice.,Marcel Dekker INC, New York,
2002: pp. 217–241.
[8] K.J.Vetter, General kinetics of passive layers on metals, Electrochim. Acta. 16 (1971)
1923–1937.
[9] R.C.Newman, Understanding the corrosion of stainless steel, Corrosion. 57 (2001) 1030–
1041.
127
[10] T.P.Hoar, D.C.Mears, G.P.Rothwell, The relationships between anodic passivity,
brightening and pitting, Corros. Sci. 5 (1965) 279–289.
[11] T.P. Hoar, The production and breakdown of the passivity of metals, Corros. Sci. 7 (1967)
341–355.
[12] C.J.Semino, J.R.Galvele, Passivity breakdown of high purity iron and AISI 4340 steel in
0.5M NaCl solution, Corros. Sci. 16 (1976) 297–306.
[13] N.Sato, Some concepts of corrosion fundamentals, Corros. Sci. 27 (1987) 421–433.
[14] M.H.Dean, U.Stimming, The electronic properties of disordered passive films, Corros.
Sci. 29 (1989) 199–211.
[15] J.W.Schultze, M.M.Lohrengel, Stability, reactivity and breakdown of passive films.
problems of recent and future research, Electrochim. Acta. 45 (2000) 2499–2513.
[16] N.E.Hakiki, M.F.Montemor, M.G.S. Ferreira, M. da Cunha Belo, Semiconducting
properties of thermally grown oxide films on AISI 304 stainless steel, Corros. Sci. 42
(2000) 687–702.
[17] C.M.Rangel, T.M.Silva, M.da.C.Belo, Semiconductor electrochemistry approach to
passivity and stress corrosion cracking susceptibility of stainless steels, Electrochim. Acta.
50 (2005) 5076–5082.
[18] S.Lozano-Perez, T.Yamada, T.Terachi, M.Schröder, C.A.English, G.D.W.Smith,
C.R.M.Grovenor, B.L.Eyre, Multi-scale characterization of stress corrosion cracking of
cold-worked stainless steels and the influence of Cr content, Acta. Mater. 57 (2009) 5361–
5381.
[19] F.Navaï, Effects of tensile and compressive stresses on the passive layers formed on a type
302 stainless steel in a normal sulphuric acid bath, J. Mater. Sci. 30 (1995) 1166–1172.
[20] F.Navaï, O.Debbouz, AES study of passive films formed on a type 316 austenitic
stainless-steels in a stress field, J. Mater. Sci. 34 (1999) 1073–1079.
[21] A.H. Heuer, H. Kahn, P.M. Natishan, F.J. Martin, L.E. Cross, Electrostrictive stresses and
breakdown of thin passive films on stainless steel, Electrochim. Acta. 58 (2011) 157–160.
[22] N.Sato, Anodic breakdown of passive films on metals, J. Electrochem. Soc. 129 (1982)
255–260.
[23] N.Sato, An overview on the passivity of metals, Corros. Sci. 31 (1990) 1–19.
[24] T.L.S.L.Wijesinghe, D.J.Blackwood, Characterisation of passive films on 300 series
stainless steels, Appl. Surf. Sci. 253 (2006) 1006–1009.
128
[25] N.E.Hakiki, Comparative study of structural and semiconducting properties of passive
films and thermally grown oxides on AISI 304 stainless steel, Corros. Sci. 53 (2011)
2688–2699.
[26] V.Vignal, D.Ba, H.Zhang, F.Herbst, S.Le Manchet, Influence of the grain orientation
spread on the pitting corrosion resistance of duplex stainless steels using electron
backscatter diffraction and critical pitting temperature test at the microscale, Corros. Sci.
68 (2013) 275–278.
[27] V.Vignal, H.Krawiec, O.Heintz, D.Mainy, Passive properties of lean duplex stainless
steels after long-term ageing in air studied using EBSD, AES, XPS and local
electrochemical impedance spectroscopy, Corros. Sci. 67 (2013) 109–117.
[28] N.D.Tomashov, Passivity and corrosion resistance of metal systems, Corros. Sci. 4 (1964)
315–334.
[29] G.T.Burstein, 1.5, Passivity and localised corrosion, in: L.L.Shreir, R.A.Jarman,
G.T.Burstein (Eds.), Corrosion Vol.1Metal/Environmental Reactions, Butterworth
Heinemann, Great Briton, 1994: pp. 118–150.
[30] J.Kruger, Passivity, in: S.D. Cramer, B.S. Covino (Eds.), Corros. Testing, Prot., 9th
Editio, ASM International , USA, 2003.
[31] J.D.Sudbury, O.L.Riggs, D.A.Shock, Anodic passivation studies, Corrosion. 16 (1960)
47t–54t.
[32] W.A.Mueller,The polarization curve and anodic protection, Corrosion. 18 (1962) 359t–
367t.
[33] K.Osozawa, H.J.Engell, The anodic polarization curves of iron-nickel-chromium alloys,
Corros. Sci. 6 (1966) 389–393.
[34] H.C.Man, D.R.Gabe, A study of pitting potentials for some austenitic stainless steels using
a potentiodynamic technique, Corros. Sci. 21 (1981) 713–721.
[35] V.S.Rao, V.S.Raja, Anodic polarization and surface composition of Fe-16Al-0.14C alloy
in 0.25 M sulfuric acid, Corrosion. 59 (2003) 575–583.
[36] Y.Yi, P.Cho, A.Al Zaabi, Y.Addad, C. Jang, Potentiodynamic polarization behaviour of
AISI type 316 stainless steel in NaCl solution, Corros. Sci. 74 (2013) 92–97.
[37] L.V.Taveira, M.F.Montemor, M.Da Cunha Belo, M.G.Ferreira, L.F.P.Dick, Influence of
incorporated Mo and Nb on the Mott-Schottky behaviour of anodic films formed on AISI
304L, Corros. Sci. 52 (2010) 2813–2818.
129
[38] Z.Feng, X.Cheng, C.Dong, L.Xu, X. Li, Passivity of 316L stainless steel in borate buffer
solution studied by Mott–Schottky analysis, atomic absorption spectrometry and X-ray
photoelectron spectroscopy, Corros. Sci. 52 (2010) 3646–3653.
[39] M.BenSalah, R.Sabot, E.Triki, L.Dhouibi, P.Refait, M.Jeannin, Passivity of Sanicro28
(UNS N-08028) stainless steel in polluted phosphoric acid at different temperatures
studied by electrochemical impedance spectroscopy and Mott–Schottky analysis, Corros.
Sci. 86 (2014) 61–70.
[40] W.P.Gomes, D.Vanmaekelbergh, Impedance spectroscopy at semiconductor electrodes:
Review and recent developments, Electrochim. Acta. 41 (1996) 967–973.
[41] K.Hashimoto, K.Asami, K.Teramoto, An X-ray photo-electron spectroscopic study on the
role of molybdenum in increasing the corrosion resistance of ferritic stainless steels in
HCl, Corros. Sci. 19 (1979) 3–14.
[42] J.M.Bastidas, M.F.López, A.Gutierrez, C.L.Torres, Chemical analysis of passive films on
type AISI 304 stainless steel using soft X-ray absorption spectroscopy, Corros. Sci. 40
(1998) 431–438.
[43] A.A. Hermas, XPS analysis of the passive film formed on austenitic stainless steel coated
with conductive polymer, Corros. Sci. 50 (2008) 2498–2505.
[44] R.Steinberger, J.Duchoslav, T.Greunz, M.Arndt, D.Stifter, Investigation of the chemical
stability of different Cr (VI) based compounds during regular X-ray photoelectron
spectroscopy measurements, Corros. Sci. 90 (2015) 562–571.
[45] J.E.Castle, R.Ke, Studies by augur spectroscopy of pit initiation at the site of inclusions in
stainless steel, Corros. Sci. 30 (1990) 409–428.
[46] V.S.Rao, M.Norell, V.S.Raja, Scanning auger electron spectroscopy study of the oxide
film formed on dendritic and interdendritic regions of C containing Fe3Al intermetallic,
Corros. Sci. 45 (2003) 2717–2728.
[47] M.Odziemkowski, Spectroscopic studies and reactions of corrosion products at surfaces
and electrodes, in: S.D. Jack Yarwood, Richard Douthwaite (Ed.), Spectrscopic Prop.
Inorg. Organomet. Compd., 2009: pp. 385–449.
[48] I.Olefjord, L.Wegrelius, Surface analysis of passive state, Corros. Sci. 31 (1990) 89–98.
[49] S.Mischler, A.Vogel, H.J.Mathieu, D.Landolt, The chemical composition of the passive
film on Fe-24Cr and Fe-24Cr-11Mo studied by AES, XPS and SIMS, Corros. Sci. 32
(1991) 925–944.
130
[50] A.Seyeux, M. Liu, P. Schmutz, G.Song, A.Atrens, P.Marcus, ToF-SIMS depth profile of
the surface film on pure magnesium formed by immersion in pure water and the
identification of magnesium hydride, Corros. Sci. 51 (2009) 1883–1886.
[51] M.Salasi, G.B.Stachowiak, G.W.Stachowiak, M.R.Kilburn, NanoSIMS investigation of
passive oxide films on high-Cr cast iron, Corros. Sci. 67 (2013) 298–303.
[52] K.F.McCarty, D.R.Boehme, A Raman study of the systems Fe3−xCrxO4 and Fe2−xCrxO3,
J. Solid State Chem. 79 (1989) 19–27.
[53] L.J.Oblonsky, T.M.Devine, A surface enhanced Raman spectroscopic study of the passive
films formed in borate buffer on iron, nickel, chromium and stainless steel, Corros. Sci. 37
(1995) 17–41.
[54] D.L.A.de Faria, S.V.Silva, M.T.de Oliveira, Raman microspectroscopy of some iron
oxides and oxyhydroxides, J. Raman Spectrosc. 28 (1997) 873–878.
[55] S.Ramya, T.Anita, H.Shaikh, R.K.Dayal, Laser Raman microscopic studies of passive
films formed on type 316LN stainless steels during pitting in chloride solution, Corros.
Sci. 52 (2010) 2114–2121.
[56] E.Hazan, Y.Sadia, Y.Gelbstein, Characterization of AISI 4340 corrosion products using
Raman spectroscopy, Corros. Sci. 74 (2013) 414–418.
[57] J.S.Gaffney, N.A.Marley, D.E. Jones, Fourier transform infrared (FTIR) spectrscopy, in:
E.N. Kaufmann (Ed.), Charact. Mater., John Wiley & Sons, Ltd., 2012: pp. 1104–1135.
[58] N.T.McDevitt, W.L.Baun, Infrared absorption study of metal oxides in the low frequency
region (700-240 cm−1
), Spectrochim. Acta. 20 (1964) 799–808.
[59] P.Marshall, S.S.Mitra, P.J.Gielisse, J.N.Plendl, L.C.Mansur, Infrared lattics spectra of
Al2O3 and Cr2O3, J. Chem. Phys. 43 (1965) 2893–2894.
[60] D.K.Ottesen, A.S.Nagelberg, Infrared spectroscopic studies of surface oxides, Thin Solid
Films. 73 (1980) 347–352.
[61] A.Atrens, B.Baroux, M. Mantel, The secondary passive film for type 304 stainless steel in
0. 5 M H2SO4, J. Electrochem. Soc. 144 (1997) 3697–3704.
[62] G.Hultquist, M. Seo, T. Leitner, C. Leygraf, N. Satot, The dissolution behaviour of iron,
chromium, molybdenum and copper from pure metals and from ferritic stainless steels,
Corros. Sci. 27 (1987) 937–946.
[63] M.Prakash, S.Shekhar, A.P.Moon, K.Mondal, Journal of Materials Processing Technology
Effect of machining configuration on the corrosion of mild steel, J. Mater. Process. Tech.
219 (2015) 70–83.
131
[64] T.Angel, Formation of martensite in austenitic stainless steels: effects of deformation,
temparature, and composition, J. Iron Steel Inst. 177 (1954) 165–174.
[65] V.Seetharaman, R.Krishnan, Influence of the martensitic transformation on the
deformation behaviour of an AISI 316 stainless steel at low temperatures, J. Mater. Sci. 16
(1981) 523–530.
[66] V.Seetharaman, Deformation and martensitic transformation, Bull. Mater. Sci. 6 (1984)
703–716.
[67] A.Das, S.Sivaprasad, P.C.Chakraborti, S.Tarafder, Connection between deformation-
induced dislocation substructures and martensite formation in stainless steel, Philos. Mag.
Lett. 91 (2011) 664–675.
[68] A.Das, S.Tarafder, P.C.Chakraborti, Estimation of deformation induced martensite in
austenitic stainless steels, Mat. Sci.Eng.A. 529 (2011) 9–20.
[69] A.Das, P.C.Chakraborti, S.Tarafder, H.K.D.H.Bhadeshia, Analysis of deformation
induced martensitic transformation in stainless steels, Mater. Sci. Technol. 27 (2011) 366–
370.
[70] K.Elayaperumal, P.K.De, J.Balachandra, Passivity of type 304 stainless steel–effect of
plastic deformation, Corrosion. 28 (1972) 269–273.
[71] G.C.Palit, V.Kain, H.S.Gadiyar, Electrochemical investigations of pitting corrosion in
nitrogen-bearing type 316LN stainless steel, Corrosion. 49 (1993) 977–991.
[72] B.Mazza, P.Pedeferri, D.Sinigaglia, A.Cigada, L.Lazzari, G.Re, D.Wenger, Relationship
between the electrochemical and corrosion behavior and the structure of stainless steels
subjected to cold plastic deformation, J. Electrochem. Soc. 123 (1976) 1157–1163.
[73] B.Mazza, P.Pedeferri, D.Sinigaglia, A.Cigada, G.Fumagalli, G.Re, Electrochemical and
corrosion behaviour of work-hardened commercial austenitic stainless steels in acid
solutions, Corros. Sci. 19 (1979) 907–921.
[74] S.M. Alvarez, A. Bautista, F.Velasco, Influence of strain-induced martensite in the anodic
dissolution of austenitic stainless steels in acid medium, Corros. Sci. 69 (2013) 130–138.
[75] T.J.Mesquita, E.Chauveau, M.Mantel, N.Bouvier, D.Koschel, Corrosion and metallurgical
investigation of two supermartensitic stainless steels for oil and gas environments, Corros.
Sci. 81 (2014) 152–161.
[76] M.Zamanzade, A.Barnoush, Effect of chromium on the electrochemical properties of iron
aluminide intermetallics, Corros. Sci. 78 (2014) 223–232.
132
[77] C.Örnek, D.L.Engelberg, SKPFM measured volta potential correlated with strain
localisation in microstructure to understand corrosion susceptibility of cold-rolled grade
2205 duplex stainless steel, Corros. Sci. (2015) 4–11.
[78] S.Panchanadeeswaran, R.D.Doherty, R.Becker, Direct observation of orientation change
by channel die compression of polycrystalline aluminum- use of a split sample, Acta
Mater. 44 (1996) 1233–1262.
[79] I.Samajdar, B.Verlinden, P.Van Houtte, Developments in macro and micro texture during
plane strain channel die compression of IF steel., ISIJ Int. 38 (1998) 759–765.
[80] M.Darrieulat, J.Y.Poussardin, R.Y.Fillit, C.Desrayaud, Homogeneity and heterogeneity in
channel-die compressed Al-1%Mn single crystals: considerations on the activity of the
slip systems, Mater. Sci. Eng. A. 445-446 (2007) 641–651.
[81] C.Chovet, C.Desrayaud, F.Montheillet, A mechanical analysis of the plane strain channel-
die compression test: friction effects in hot metal testing, Int. J. Mech. Sci. 44 (2002) 343–
357.
[82] N.Keskar, S.Mukherjee, K.V.M.Krishna, D.Srivastava, G.K.Dey, P.Pant, R.D.Doherty,
I.Samajdar, Quantifying the mesoscopic shear strains in plane strain compressed
polycrystalline zirconium, Acta. Mater. 69 (2014) 265–274.
[83] S.Wright, B.Adams, Automatic analysis of electron backscatter diffraction patterns,
Metall. Trans. A. 23 (1992) 759–767.
[84] J. Wu, P.J.Wray, C.I.Garcia, M.Hua, A.J.Deardo, Image quality analysis: a new method of
characterizing microstructures, ISIJ Int. 45 (2005) 254–262.
[85] R.A.Schwarzer, D.P.Field, B.L.Adams, M.Kumar, A.J. Schwartz, Present state of electron
backscatter diffraction and prospective developments, in: A.J. Schwartz, M. Kumar, B.L.
Adams, D.P. Field (Eds.), Electron Backscatter Diffr. Mater. Sci., Springer Science +
Business media, New York, 2009: pp. 1–20.
[86] S.I.Wright, M.M.Nowell, D.P.Field, A review of strain analysis using electron backscatter
diffraction, Microsc.Microanal. 17 (2011) 316–329.
[87] E.Geroult, Ph.D thesis, Department of MTM, Katholieke Universiteit Leuven, Belgium,
1999.
[88] D.N.Wasnik, I.K.Gopalakrishnan, J.V.Yakhmi, V.Kain, I.Samajdar, Cold rolled texture
and microstructure in types 304 and 316L austenitic stainless steels, ISIJ Int. 43 (2003)
1581–1589.
133
[89] K.Mumtaz, S.Takahashi, J.Echigoya, Y. Kamada, L.F. Zhang, H. Kikuchi, K.Ara, M.Sato,
Magnetic measurements of martensitic transformation in austenitic stainless steel after
room temperature rolling, J. Mater. Sci. 39 (2004) 85–97.
[90] R.W.Revie, H.H.Uhlig, Corrosion and Corrosion Control: An introduction to Corrosion
Science and Engineering, fourth ed., Wiley Interscience, New Jersey, 2008.
[91] C.Donadille, R.Valle, P.Dervin, R.Penelle, Development of texture and microstructure
during cold-rolling and annealing of F.C.C. alloys: Example of an austenitic stainless
steel, Acta.Metall.Mater. 37 (1989) 1547–1571.
[92] N.A.Fleck, G.M.Muller, M.F.Ashby, J.W.Hutchinson, Strain gradient plasticity: Theory
and experiment, Acta Metall. Mater. 42 (1994) 475–487.
[93] T.Kruml, J.Polak, K.Obrtlik, S.Degallaix, Dislocation structures in the bands of localised
cyclic plastic strain in austenitic 316L and austenitic-ferritic duplex stainless steels, Acta
Mater. 45 (1997) 5145–5151.
[94] D.Kuhlmann-Wilsdorf, Theory of plastic deformation: - properties of low energy
dislocation structures, Mat. Sci.Eng.A. 113 (1989) 1–41.
[95] B.Bay, N.Hansen, D.A.Hughes, D.Kuhlmann-Wilsdorf, Evolution of f.c.c. deformation
structures in polyslip, Acta.Metall.Mater. 40 (1992) 205–219.
[96] D.A.Hughes, N.Hansen, High angle boundaries formed by grain subdivision mechanisms,
Acta. Mater. 45 (1997) 3871–3886.
[97] V.M.Nandedkar, I.Samajdar, K.Narasimhan, Development of grain interior strain
localizations during plane strain deformation of a deep drawing quality sheet steel., ISIJ
Int. 41 (2001) 1517–1523.
[98] V.Shrinivas, S.K.Varma, L.E.Murr, Deformation-induced martensitic characteristics in
304 and 316 stainless steels during room-temperature rolling, Metall. Mater. Trans. A. 26
(1995) 661–671.
[99] M.Baeva, Compositional dependence of gamma-alpha transition induced by plastic
deformation nitrified Fe-Cr-Ni alloys, Scripta.Mater. 37 (1997) 1449–1452.
[100] Q.Dai, R.Yang, K.Chen, Deformation behavior of Fe-Mn-Cr-N austenitic steel, Mater.
Charact. 42 (1999) 21–26.
[101] S.S.M.Tavares, D.Fruchart, S.Miraglia, Magnetic study of the reversion of martensite
alpha in a 304 stainless steel, J.Alloy.Compd. 307 (2000) 311–317.
[102] R.W.Rathbun, D.K.Matlock, J.G.Speer, Strain aging behavior of austenitic stainless steels
containing strain induced martensite, Scr. Mater. 42 (2000) 887–891.
134
[103] G.B.Olson, M.Cohen, A mechanism for the strain-induced nucleation of martensitic
transformations, J. Less Common Met. 28 (1972) 107–118.
[104] G.B.Olson, M. Cohen, Kinetics of strain-induced martensitic nucleation, Metall. Trans. A.
6 (1975) 791–795.
[105] W.S.Lee, C.F.Lin, Impact properties and microstructure evolution of 304L stainless steel,
Mat.Sci.Eng.A. 308 (2001) 124–135.
[106] K.Spencer, J.D.Embury, K.T.Conlon, M.Véron, Y.Bréchet, Strengthening via the
formation of strain-induced martensite in stainless steels, Mat. Sci.Eng.A. 387-389 (2004)
873–881.
[107] B.Verlinden, J.Driver, I.Samajdar, R.D.Doherty, Thermo Mechanical Processing of
Metallic Materials, first ed., Pergamon Materials Series, Great Briton, 2007.
[108] L.Peguet, B.Malki, B.Baroux, Influence of cold working on the pitting corrosion
resistance of stainless steels, Corros. Sci. 49 (2007) 1933–1948.
[109] L.Peguet, B.Malki, B.Baroux, Effect of austenite stability on the pitting corrosion
resistance of cold worked stainless steels, Corros. Sci. 51 (2009) 493–498.
[110] R.D.Moser, P.M.Singh, L.F.Kahn, K.E.Kurtis, Chloride-induced corrosion resistance of
high-strength stainless steels in simulated alkaline and carbonated concrete pore solutions,
Corros. Sci. 57 (2012) 241–253.
[111] A.Randak, F.W.Trautes, Influence of austenite stability of 18-8 Cr-Ni-steels on the cold
working and corrosion properties of these steels, Mater. Corros. 21 (1970) 97–109.
[112] A.S.Hamada, L.P.Karjalainen, M.C.Somani, Electrochemical corrosion behaviour of a
novel submicron-grained austenitic stainless steel in an acidic NaCl solution, Mat.Sci.Eng
A. 431 (2006) 211–217.
[113] A.Barbucci, G.Cerisola, P.L.Cabot, Effect of cold-working in the passive behavior of 304
stainless steel in sulfate media, J. Electrochem. Soc. 149 (2002) B534–B542.
135
CHAPTER 5
Defining the Post-Machined Sub-Surface Damage in Austenitic
Stainless Steels
5.1 Introduction
Components made from austenitic stainless steel often require machining either to obtain the
desired dimensions and/or to attain a desired surface finish. Austenitic stainless steels have an
excellent corrosion resistance however, machining has the potential to be detrimental to
corrosion resistance [1–4]. Therefore, the governing processes of machining require a systematic
study. Higher surface roughness is shown to deteriorate resistance to corrosion damage [4–8].
While machining does change surface roughness [1,2,4,9], it has also been shown to alter the
sub-surface layer by forming nano-crystalline grain structure [1,3,7,10], enforcing strain
hardening [1,7,11] and introducing tensile residual stress [2,4,12–15]. Naturally, the topic has
attracted academic and applied research, with such interests broadly classified into two
categories: (a) interests originating from the mechanics of machining [15] and (b) interests
related to microstructural developments [2,7,8]. Both the interests are, however, linked to the
performance (mechanical as well as electrochemical) of machined surfaces and sub-surfaces.
The demands of industry has lead to incorporation of higher speeds in machining processes
[16,17]. Though higher speeds are expected to provide increase in strain rates and hence in the
effective plastic deformation of the sub-surface layer, higher machining speed may also cause
higher resultant surface temperature [14]. A higher strain rate may lead to a higher strain
hardening of the material, while a higher temperature may tend to reduce the strain hardening.
These counter-balancing effects determine the performance of the machined surface and sub-
surface. Development of sub-surface microstructure is critical in determining the nature and
stability of passive Cr2O3 film. The stability of the passive film and the extent of introduced
residual stress would affect its susceptibility to stress corrosion cracking [7,18,19]. In this paper,
the response of three grades of stainless steels to machining at different speeds is studied. The
effect of machining speed is studied by characterizing surface roughness, residual stress
distribution in the affected sub-surface, misorientation developed due to machining and stability
of passive film on surfaces. The different response of three differently alloyed stainless steels to
136
machining at different speeds is explained based on differences in stacking fault energy and
thermal conductivity.
5.2 Experimental Methods
5.2.1 Materials
For the present study, three grades of austenitic stainless steels were selected. The first grade,
Sanicro 28TM
, is an alloy marketed by Sandvik®. It is sold under the trademark Sanicro 28TM
,
has been referred to as alloy A in this thesis. Commercial AISI (American Iron and Steel
Institute) 316L and 304L stainless steels are the other two grades used. The chemical
compositions of the three alloys used in the study are listed in table 5.1.
Table 5.1 The chemical composition (in wt% alloying elements) of the three austenitic stainless
steel grades.
5.2.2 Machining
The fully recrystallized specimens were subjected to vertical milling using uncoated tungsten
carbide tools. During the vertical milling machining process, coolant was used. Machining was
done systematically by varying three parameters: (a) feed rate, (b) spindle speed and (c) depth of
cut. Strain rate is mainly dependent [16,20] on spindle speed and the material being machined.
Through control of machining parameters (mainly spindle speed), a von Mises strain of 3.0 (at
three different strain rates: 2100, 1050 and 105 s-1
) was imposed. These strain and strain rates
values were estimated following broad formulations based on the references [16,20]. Further
details are included in appendix 5.1.
C S P Mn Si Cr Ni N Cu Mo
Alloy A 0.020 0.015 0.025 2.0 0.60 27.00 31.00 Trace 1.09 3.6
316L 0.020 0.020 0.010 1.0 0.38 16.25 10.73 0.10 0.03 2.37
304L 0.029 0.010 0.025 1.78 0.20 18.01 8.21 0.037 0.2 --
137
5.2.3 Surface Roughness Measurement
The surface roughness (Ra) values of the machined specimen were measured from a white light
interferometry (WLI) based non-contact profilometer (VeecoTM
NT9100) and are represented as
standard Ra values [21]. Ra is average surface roughness and it is used for describing surface
roughness of machined specimens. Arithmetic mean of absolute surface roughness values are
calculated based on equation (5.1)
(5.1)
where M and N are data points (in x and y array) and Z is relative surface height with respect to
mean plane. Ra describes the texture of surface, quantifying vertical deviations from reference
surface.
5.2.4 Sub-Surface Characterization
The machining process has been shown to alter the region below the machined surface by the
following three factors: (a) formation of nano crystalline grains, (b) strain hardening and (c)
introduction of tensile residual stresses. The metallurgically and mechanically affected sub-
surface is reported to be of the order of 200– 300 m for austenitic stainless steel [1,7].
Therefore in this study, a depth of upto 500 m has been taken as sub-surface (as shown in figure
5.1) and subjected to detailed characterization. The sub-surface characterization is described in
the following sections.
Figure 5.1 front views of the vertically milled specimens. This was valid for all three grades
(alloy A, 316L, 304L) of austenitic stainless steels.
138
Anodic Potentiodynamic Polarization Test
The specimens of as-received and machined stainless steels (cross-sectional area, see Fig.5.1)
were subjected to anodic potentiodynamic polarization test. The test solution used for anodic
potentiodynamic polarization test was 0.5M H2SO4. This test solution was continuously
deaerated for 45 minutes prior to start of the test. The process of deaeration was also continued
during the test. The sweep rate was kept at 6V/h. A three- electrode setup (reference, auxiliary
and working electrodes) was used. Saturated calomel electrode (SCE) was used as reference
electrode and platinum electrode was used as auxiliary electrode. The potential was scanned
from -500 mVSCE to 800 mVSCE after establishing the open circuit potential (OCP).
Residual Stress Measurement
Multiple {hkl} GIXRD offers a unique means of estimating sub-surface residual stresses [22].
As shown in figure 5.2a, and described in further details elsewhere [23], control of the grazing
incidence angle alters for the respective . It needs to be noted that each peak in a multiple
{hkl} GIXRD (figure 5.2b) has different . This allows determination of d-sin2
plots for
multiple {hkl}, see figure 5.2b. There are two critical advantages. Firstly, the residual stress
components (figure 5.2a) can be determined for all poles. More important to this study, the
measurement of residual stresses can be made at a particular depth of penetration, determined by
the mass absorption coefficient and the values [24]. It is hence possible, through careful
colloidal silica polish to establish [23] through thickness gradients of residual stresses.
Panalytical X’Pert PRO MRD system and a commercial software, X’Pert Stress PlusTM
system
were used to for multiple {hkl} grazing incident X-ray diffraction (GIXRD) residual stress
measurements. It needs to be noted,
ω= angle between X-ray beam and specimen surface
θ= Bragg angle for multiple {hkl}, different (θ) is obtained.
139
Depth of penetration (Ґ), is defined as equation (5.2)
-1
(5.2)
Equation (5.2) can be written when ω is small,
(5.3)
where μ is linear absorption coefficient [24]
Electron Backscattered Diffraction
To visualize the sub-surface microstructures, the machined surface was preserved with 20 m
electroless nickel deposition. The cross-section was then subjected to sub-micron colloidal silica
polish, followed by electron backscattered diffraction (EBSD). EBSD was conducted in a FEITM
Nova-Nano FEG-SEM (field emission gun scanning electron microscope) using a TSLTM
EBSD
system and data collection step size of 0.1 micron. Beam and video conditions were kept
identical between the scans. EBSD data were further analyzed for appropriate mapping and to
extract information on the local misorientation developments. More specifically, this study used
KAM (equation (3.4)) to represent gradual misorientation developments from machined sub-
surface.
KAM(i)= (3.4)
where i is an EBSD data point, with x as neighbors and ωij is misorientations (provided it did not
exceed 5°).
140
(a)
(b)
Figure 5. 2 (a) Schematic of grazing incidence X-ray diffraction (GIXRD) indicating angular
conventions for , and . The figure also includes standard representation of the residual stress
matrix: 3 representing normal to the machining surface. (b) Multiple {hkl} GIXRD
measurement: showing different {hkl} peaks. They were then converted into a d-sin2
Fourier Transform Infrared Spectroscopy -Imaging
Infrared (IR) spectroscopy is based on absorption/transmission of IR radiation as a function of
wavelength or frequency [25–27]. For FTIR (Fourier transformed infrared spectroscopy)-
141
imaging, BrukerTM
300-Hyperion unit was used. It is to be noted that Cr2O3 provided an FTIR-
imaging peak at the approximate wave number of 660 cm-1
[28]. Area under this peak Cr2O3 was
quantified by subtracting the background (taken in air) from the spectra obtained in the real
specimen. Such specimens (passivated) were prepared by scanning them potentiodynamically
from OCP to noble direction till 750 mVSCE at a scan rate of 6 V/h in 0.5M H2SO4 (deaerated).
Area under Cr2O3 peaks were calculated with the help of in-built FTIR-imaging post processing
software OPUS 6.5TM
.
5.2.5 Thermal Conductivity Measurement
Laser flash method [29,30] was used to assess thermal conductivity of the respective grades.
Thermal diffusivities were determined on a commercial system- LINSEISTM
LFA 1000. 10 mm
diameter discs of 3 mm thickness were used for measuring the thermal conductivities at 298K,
673K, 1073K following (equation (5.5))
k(T)= α(T) x Cp (T) x ρ (T) (5.5)
where
k = thermal conductivity of specimen, W/mK,
α = thermal diffusivity of specimen, m2/s,
Cp= specific heat of specimen, J/kg/K,
ρ= density of specimen, kg/m3
5.3 Results
Figure 5.1 describes the typical geometry (front view) of the vertical milled specimens. The
surface roughness decreased with strain rate or machining speed for all three grades, see figure
5.3. However, the drop in surface roughness was significantly more (13 times) in alloy A (and
only 7 and 5 times in 316L and 304L respectively) when strain rate was changed from 105 to
2100 s-1
. Other than measurements of surface roughness, anodic potentiodynamic polarization of
selected, albeit similar, areas (see the darkened area in figure 5.1) was also attempted.
142
Figure 5.3 Measured surface roughness versus strain rates. Error bars represent standard
deviations from multiple measurements (two such representative measurements of surface
textures are included).
Such areas were carefully isolated by lacquering and anodic potentiodynamic polarization tests
were performed on the exposed surfaces. As the focus of this study was to establish the
passivation behavior of machined sub-surfaces, anodic potentiodynamic polarization test
solutions of any chloride, fluoride containing environment was avoided. Figure 5.4 collates the
‘effectiveness’ of anodic potentiodynamic polarization tests in capturing the role of plastic
deformation. It is clear that relatively severe plastic deformation through machining (vertical
milling) did not allow passivation to set in. Though the tests showed clear distinction between as
received (pre-machined) and machined specimens, they were ineffective in capturing differences
(if any) in sub-surface machined layers under different alloy chemistry and/or machining speeds.
Residual stress measurements, however, showed clear differences, see figure 5.5. Machining led
to residual stress gradients. Immediately on the machined surface both 11 and 13 were negative.
The negative stresses sharply became positive (at an approximate depth of 20 m) and then
slowly changed to zero, the stress of the fully recrystallized material before any machining. It is
143
Figure 5.4 Anodic potentiodynamic polarization curves of the subsurface region marked in
figure.5.1. These are shown for all three grades: (a) alloy A, (b) 316L (b) and (c) 304L.
144
Figure 5.5 Multiple {hkl} GIXRD estimated τ 13 and σ11 (for stress conventions refer fig.2a)
versus depth of penetration for different grades of stainless steels. Also included are magnified
stress gradient profiles to establish the role of alloy chemistry and machining speed.
Alloy A
316L
304L
145
to be noted that such a gradient in residual stress is expected: the rules of mechanics demand an
effective force balance in the material. It is important to note that only in alloy A, the gradients
were significantly affected by the machining speed. In summary, machining speed appeared to
affect both surface roughness and sub-surface residual stresses mostly in alloy A. The summary
of maximum τ 13 and σ11 values for all specimens are shown in table 5.2.
Table 5.2 Calculated maximum τ 13 and σ11 for different strain rates of all grades of stainless
steels
It is to be noted, and also seen in figure 5.6a, that alloy A had a higher grain size than 316L and
304L. However, image quality maps of figure 5.6b do not bring out differences in sub-surface
microstructure evolution between the three grades (alloy A, 316L and 304L). This is more
appreciated from the kernel average misorientation (KAM) maps (for details on KAM, see [31–
34]) see figure 5. 6c. Figure 5.6c thus showed a gradual misorientation (KAM) build-up from
surface to sub-surface. Qualitatively, the misorientation build-up appeared more significant for
the lower strain rate or machining speed. At the lower speeds, presence of near-surface ultra-fine
grains and severe strain localizations were observed. Highest machining speed, on the other
hand, provided a subdued picture of in-grain misorientation. To quantitatively present the
misorientation developments with depth, several KAM plots were processed. This provided
statistical KAM profiles, see figure 5.7. Data from a near sigmoidal profile can be exploited in
several different ways. The easiest is to extract an effective height or h*. For example, in a case-
hardened specimen case depth is estimated at a depth corresponding to the ½ (maximum +
minimum) of the hardness values. With a similar argument, effective heights (h*) of the sub-
surface KAM profiles were measured.
Alloy A 316L 304L
Strain
rate
(s-1
)
Depth
of
penetrat
ion
(mm)
Max.
σ11
(MPa)
Max.
τ 13
(MPa)
Depth
of
penetrat
ion
(mm)
Max
σ11
(MP
a)
Max.
τ 13
(MPa)
Depth
of
penetrat
ion
(mm)
Max.
σ11
(MP
a)
Max.
τ 13
(MPa)
2100 30 580 600 30 680 690 30 720 800
1050 30 680 700 30 740 740 30 740 870
105 30 730 680 30 730 750 30 780 940
146
AS-received
Alloy A 316L 304L
Alloy A
2100 s-1
1050 s-1
105 s-1
316L
300 µm
147
304L
(a)
2100 s-1
1050 s-1
100 µm
148
(b)
Figure 5. 6 (a) EBSD IQ (Image quality) maps of as-received state and the sub-surface
machined region in all three grades of austenitic stainless steels machined at 2100, 1050,
105 s-1
strain rates. (b) Magnified region was then used to map out KAM (kernel average
misorientation) in alloy A. This shows strong strain rate (or machining speed)
dependence of KAM developments.
A recent manuscript in Corrosion Science [35] has used a combination of EBSD and FTIR-
imaging. The combination had demonstrated its ability to relate substrate microstructure with the
stability/retention of Cr2O3 films. The same technique was adopted in this thesis as well. The
area under Cr2O3 peak showed a similar (albeit reverse) gradient (see figure 5.8a-c) as that of
KAM (figure 5.7). As shown in figure 8a-c, near surface heavily deformed material had
insignificant presence of Cr2O3. This increased, in a near sigmoidal manner, with depth. The
noticeable change in FTIR-imaging spectra is also shown in figure 5.8d. The near surface Cr2O3
peak was minimal (area under the peak of 0.09 cm-1
), while beyond 500 m the area under the
Cr2O3 peak increased by more than one order (with 2 cm-1
or more as typical area under the
peak). The FTIR- imaging was thus shown to capture the gradients in Cr2O3 of the post-
machined sub-surfaces. For further analysis, h* values were also estimated from the collated
FTIR-imaging data (figure 5.8a-c). The h* values from EBSD and FTIR-imaging are
summarized in figure 5.9. In both cases, h* decreased with increasing in strain rate or machining
105 s-1
149
speed. However, FTIR- imaging provided approximately twice the effective height and appears
to be more sensitive to sub-surface damage evaluation. It is also important to note that in general
(and especially apparent at the highest machining speed) h* was least in alloy A. The change of
h* with machining speed was also
Figure 5.7 Kernel average misorientation (KAM) versus depth (from the top surface) for (a)
alloy A, (b) 316L and (c) 304L. Effective heights (h*) were estimated from the distance
corresponding to ½ (maximum + minimum) readings in y-axis.
marginally more in alloy A (1.23 times in alloy A versus 1.1 times in 316L and 304L). Alloy A
was thus shown to have higher sub-surface damage, and slightly more sensitivity of h* on
machining speed than the other two grades (316L and 304L). To appreciate such differences with
alloy chemistry and machining speed, relevant material properties were explored. Latter in the
discussion section, an explanation is attempted based on differences in stacking fault energy and
thermal conductivity values.
150
Figure 5.8 (a-c) FTIR- imaging estimated area under Cr2O3 peak versus depth for: (a) alloy A,
(b) 316L and (c) 304L. The effective heights (or depths) were measured from as the distance
corresponding to ½ (maximum + minimum) readings in y-axis. (d) Two representative FTIR-
imaging spectra (transmittance vs wavenumber) are included as reference.
151
Figure 5.9 The effective heights (h* values) versus of three grades (alloy A, 316L, 304L) of
austenitic stainless steels. These are shown for all three strain rates.
5.4 Discussion
Modern machining incorporates higher speeds [16,17,36]. Given the demands on productivity,
this is unavoidable. Though higher speeds are expected to provide increase in strain rates and
hence in the effective plastic deformation, they may also offer higher machining temperatures.
These counter-balancing effects determine the performance of the machined surfaces and sub-
surfaces. For example, surface roughness affects the pitting corrosion and passivation behavior
[5,37,38]. Developments of sub-surface microstructures and residual stresses, on the other hand,
are critical in determining the nature and stability of passive Cr2O3 films and the behavior of
stress corrosion cracking [1,2,19,39].
The existing literature in the domain of machining and corrosion of austenitic grades are often
focused to stress corrosion cracking under chloride environment [1,2,5,7,39,40]. This appears to
152
be one of the first such study relating passivation developments of sub-surface microstructural
evolution. At the very beginning this thesis highlights differences in milling induced surface
roughness. Such a difference is expected to reflect on the sub-surface microstructural
developments. However, anodic potentiodynamic polarization electrochemical studies (figure
5.3) could not capture possible differences in the corrosion performance of the post-machined
sub-surfaces. This is where the novelty of this thesis begins: a clear quantification of sub-surface
damage through gradients of residual stress (figure 5.5), microtexture (figures.5.6c, 5.7 and 5.9)
and relative presence of Cr2O3 (figures 5.8 and 5.9). This study could capture, quantitatively, the
role of alloy chemistry and machining speed on the sub-surface damage in austenitic stainless
steel.
The sub-surface damage is expected to arise from grain refinement plus in-grain misorientation
developments. Both are essentially related. Deformation induced introduction of new lattice
curvatures require geometrically necessary dislocations (GNDs) [41–44]. Such dislocations
cause local misorientations, in fact the so-called KAM can be used [45] to represent GND
structures, and lead to grain refinements. Though plastic deformation of 316L and 304L is also
expected to cause [35] strain induced martensite formation, this was not observed in the post-
machined sub-surface. It is to be noted that throughout the machining process the coolant was
used, and this in turn is expected to suppress strain induced martensite. The sub-surface damage
was thus aptly captured with KAM profiles (figure 5.6c and 5.7). But this is not unexpected or
really novel. The novelty is in the effective use of FTIR-imaging and the fact that estimated area
under Cr2O3 peaks appeared to be the most effective means for capturing the effects of alloy
chemistry or machining speed on the sub-surface damage profiles (see figure 5.9). In the next
paragraph, the result of figure 5.9 is further deliberated and rationalized.
It is important to appreciate the possible roles of two material parameters: stacking fault energy
(SFE) and thermal conductivity. As deliberated in this paragraph, these parameters offer a
rationale for the observed differences in sub-surface damage gradients. It needs to be noted [43]
that the material with higher SFE is expected have less separation between partial dislocations.
This allows more recovery, both static and dynamic, and evolution of lower energy dislocation
substructures. SFE were calculated based on equation 5.6 (for alloy A) and equation 5.7 (316L
and 304L) [46]. These are 57, 27, and 20 mJ/m2 for alloy A, 316L and 304L respectively.
153
17.0+2.29 Ni-0.9Cr (5.6)
26.6+0.73Ni+2.26Cr (5.7)
The effect of thermal conductivity would naturally get superimposed. Alloy A had the lowest
thermal conductivity (at 298K, see table 5.3): about 0.63 times of 316L and 304L. As the
temperature increased, the gap between thermal conductivities vanished. This measured data on
thermal conductivity (table 5.3) gives important inputs, albeit qualitative, to the overall
understanding of the sub-surface damage. It appears that the aspect of lower thermal conductivity
in alloy A overrides its higher SFE. As the strain rate or machining speed increased, temperature
of the machining is expected to rise with corresponding (see table 5.3) rise in thermal
conductivity. As estimated experimentally (see table 5.3), the gap between the thermal
conductivities of the grades also diminished. This appears to be in perfect synchronization with
the experimental observations on h*- which diminished for all three grades with increase in
machining speed, the drop being marginally more in alloy A.
Table 5.3 The stacking fault energy and thermal conductivity values of the three austenitic
stainless steel grades.
This thesis thus provides a set of unique experimental results relating appropriate material
parameters (SFE and temperature dependent of thermal conductivity) and post-machined sub-
surface damage profiles. The thesis also establishes the potential of FTIR-imaging, a newly
proposed means [35] for effective quantification of Cr2O3 films, in analyzing sub-surface
damage through severe plastic deformation. Arguably future research needs to take such
observation further. They also need to involve more quantitative numerical/analytical
predictions. The present thesis provided, at best, a qualitative explanation for the otherwise
Stacking fault energy
(mJ/m2 )
Thermal conductivity (W/mK)
298 K 673 K 1073 K
Alloy A 57 10 19 24
316L 27 16 20 25
304L 20 16 20 25
154
exciting and statistically reproducible results relating material parameters with post-machined
sub-surface damage in austenitic stainless steel.
5.5 Conclusion
Three grades (alloy A, 316L and 304L) of austenitic stainless steels, with compositional
variations, were subjected to vertical milling. The machining was conducted under a fixed (a von
Mises strain of 3.0) strain, but three different strain rates. The following are the main conclusions
defining the post-machined sub-surface damage profiles:
1. Standard anodic potentiodynamic polarization failed to quantify possible differences in
sub-surface damage with alloy chemistry and/or strain rate. However, the latter was
reflected on surface roughness and sub-surface damage profiles of residual stress, local
misorientation and FTIR-imaging estimated relative presence of Cr2O3 films.
2. FTIR-imaging provided the most effective means in capturing relative differences in
post-machined sub-surface damage profiles. The latter reduced with machining speed, the
effect being most pronounced in alloy A.
3. The observation that machining speed or strain rate affected sub-surface damage in alloy
A most, was rationalized in terms of temperature dependent thermal conductivity. Alloy
A had a lower (0.63 times) thermal conductivity at ambient temperature. However,
thermal conductivities of all three grades were similar at elevated temperatures. An
explanation, though qualitative at best thus appears rationale; but importantly the results
presented are novel and exciting and statistically reproducible.
Appendix 5.1
Strain (ε) and strain rate (έ) calculated as per (equation A.5.1) and (equation A.5.2) respectively.
Spindle speed was calculated as per (equation A.5.3)
ε= (A.5.1)
155
έ= (A.5.2)
ηs= tan-1
(A.5.3)
Nomenclature
f feed rate (mm/min)
ns spindle speed (rpm)
td depth of cut (mm)
ε strain
έ strain rate (s-1
)
α clearance /rake angle (˚)
αn normal clearance /rake angle (˚)
D diameter of the tool (mm)
tc chip thickness (or) cutting ratio (˚)
ω helix angle (˚)
ηs shear flow angle (˚)
ηc chip flow angle (˚)
γn normal rake angle (˚)
Vs shear velocity component along the shear plane (mm/min)
Nc rotation of spindle speed (rpm)
фn shear plane angle (˚)
So feed per tooth (mm)
V cutting speed (mm/min)
∆Y shear band spacing ( m)
156
References
[1] S.Ghosh, V.Kain, Effect of surface machining and cold working on the ambient
temperature chloride stress corrosion cracking susceptibility of AISI 304L stainless steel,
Mater. Sci. Eng. A. 527 (2010) 679–683.
[2] A.Turnbull,K.Mingard,J.D.Lord,B.Roebuck,D.R.Tice, K.J.Mottershead, N.D.Fairweather,
A.K.Bradbury, Sensitivity of stress corrosion cracking of stainless steel to surface
machining and grinding procedure, Corros. Sci. 53 (2011) 3398–3415.
[3] S.G.Acharyya, A.Khandelwal, V. Kain, A. Kumar, I. Samajdar, Surface working of 304L
stainless steel: Impact on microstructure, electrochemical behavior and SCC resistance,
Mater. Charact. 72 (2012) 68–76.
[4] J.Gravier, V.Vignal, S.Bissey-Breton, Influence of residual stress, surface roughness and
crystallographic texture induced by machining on the corrosion behaviour of copper in
salt-fog atmosphere, Corros. Sci. 61 (2012) 162–170.
[5] G.T.Burstein, P.C.Pistorius, Surface roughness and the metastable pitting of stainless steel
in chloride solutions, Corrosion. 51 (1995) 380–385.
[6] T.Hong, M.Nagumo, Effect of surface roughness on early stages of pitting corrosion of
Type 301 stainless steel, Corros. Sci. 39 (1997) 1665–1672.
[7] S.Ghosh, V.Kain, Microstructural changes in AISI 304L stainless steel due to surface
machining: Effect on its susceptibility to chloride stress corrosion cracking, J. Nucl.
Mater. 403 (2010) 62–67.
[8] G.Hinds, L.Wickström, K.Mingard, A.Turnbull, Impact of surface condition on sulphide
stress corrosion cracking of 316L stainless steel, Corros. Sci. 71 (2013) 43–52.
[9] P.G.Benardos, G.C.Vosniakos, Predicting surface roughness in machining: a review, Int.
J. Mach. Tools Manuf. 43 (2003) 833–844.
[10] S.Ghosh, V.P.S.Rana, V. Kain, V. Mittal, S.K. Baveja, Role of residual stresses induced
by industrial fabrication on stress corrosion cracking susceptibility of austenitic stainless
steel, Mater. Des. 32 (2011) 3823–3831.
[11] Y.K.Chou, Surface hardening of AISI 4340 steel by machining: a preliminary
investigation, J. Mater. Process. Technol. 124 (2002) 171–177.
157
[12] J.Kuniya, I.Masaoka, R.Sasaki, S. Kirihara, Effects of surface finishing on stress corrosion
cracking of austenitic stainless steels in high temperature water, J.Mater.energy.Syst. 1
(1980) 30–40.
[13] S.Jeelani, J.A.Bailey, Residual Stress Distribution in Machining Annealed 18 Percent
Nickel Maraging Steel, J. Eng. Mater. Technol. 108 (1986) 93–98.
[14] D.Y.Jang, T.R.Watkins, K.J.Kozaczek, C.R.Hubbard, O.B.Cavin, Surface residual stresses
in machined austenitic stainless steel, Wear. 194 (1996) 168–173.
[15] V.García Navas, O.Gonzalo, I.Bengoetxea, Effect of cutting parameters in the surface
residual stresses generated by turning in AISI 4340 steel, Int. J. Mach. Tools Manuf. 61
(2012) 48–57.
[16] M.C.Shaw, Metal Cutting Principles, second ed, Oxford University Press, New York,
2005.
[17] Z.Wang, M.Rahman, High speed machining, in: M.S.J. Hashmi (Ed.), Compr. Mater.
Process., Elsevier, Ireland, 2014: pp. 221–253.
[18] H.J.Engell, Stability and breakdown phenomena of passivating films, Electrochim. Acta.
22 (1977) 987–993.
[19] K.E.Heusler, Growth and dissolution of passivating films, Corros. Sci. 31 (1990) 597–
606.
[20] H.A.Sonawane, S.S.Joshi, Analytical modeling of chip geometry and cutting forces in
helical ball end milling of superalloy Inconel 718, CIRP J. Manuf. Sci. Technol. 3 (2010)
204–217.
[21] D.Whitehouse, Surfaces and Their Measurement, first ed, Hermes Penton Science,
London, 2002.
[22] I.C.Noyan, Effect of gradients in multi-axial stress states on residual stress measurements
with x-rays, Metall. Trans. A. 14 (1983) 249–258.
[23] D.Kohli, R.Rakesh, V.P.Sinha, G.J.Prasad, I. Samajdar, Fabrication of simulated plate fuel
elements: Defining role of out-of-plane residual shear stress, J. Nucl. Mater. 445 (2014)
200–208.
[24] B.D.Cullity, S.R.Stock, Elements of X-ray Diffraction, third ed, Prentice Hall, 2001.
[25] W.G.Golden, Fourier Transform Infrared Reflection–Absorption Spectroscopy, Academic
Press INC, 1985.
158
[26] M.Lin, A.B.Rasco, A.G.Cavinato, M.A.Holy, Infrared spectroscopy for food quality
analysis and control, in: D.W. Sun (Ed.), Infrared Spectrosc. Food Qual. Anal. Control,
Elsevier Inc., USA, 2009: pp. 119–143.
[27] J.S.Gaffney, N.A.Marley, D.E.Jones, Fourier transform infrared (FTIR) spectrscopy, in:
E.N. Kaufmann (Ed.), Charact. Mater., John Wiley & Sons, Ltd., 2012: pp. 1104–1135.
[28] N.T.McDevitt, W.L.Baun, Infrared absorption study of metal oxides in the low frequency
region (700-240 cm−1), Spectrochim. Acta. 20 (1964) 799–808.
[29] S.F.Corbin, D.M.Turriff, Thermal diffusivity by the laser flash technique, in: E.N.
Kaufmann (Ed.), Charact. Mater., second ed, John Wiley & Sons, Ltd., 2012: pp. 510–
517.
[30] M.Boutinguiza, F.Lusquiños, J.Pou, R.Soto, F.Quintero, R.Comesaña, Thermal properties
measurement of slate using laser flash method, Opt. Lasers Eng. 50 (2012) 727–730.
[31] R.A.Schwarzer, D.P.Field, B.L.Adams, M.Kumar, A.J. Schwartz, Present state of electron
backscatter diffraction and prospective developments, in: A.J.Schwartz, M.Kumar, B.L.
Adams, D.P. Field (Eds.), Electron Backscatter Diffr. Mater. Sci., Springer Science +
Business media, New York, 2009: pp. 1–20.
[32] S.Wright, B.Adams, Automatic analysis of electron backscatter diffraction patterns,
Metall. Trans. A. 23 (1992) 759–767.
[33] S.I.Wright, M.M.Nowell, D.P.Field, A review of strain analysis using electron backscatter
diffraction, Microsc.Microanal. 17 (2011) 316–329.
[34] L.Saraf, Kernel average misorientation confidence index correlation from FIB sliced Ni-
Fe-Cr alloy surface, Microsc Microanal. 17 (2011) 424–425.
[35] N.Srinivasan, V.Kain, N.Birbilis, B.Sunilkumar, M.N.Gandhi, P.V.Sivaprasad, G.Chai,
A.Lodh, P.M.Ahmedabadi, I.Samajdar, Plastic deformation and corrosion in austenitic
stainless Steel: a novel approach through microtexture and infrared spectroscopy, (2016)
In Press, Corr.Sci.
[36] K.A.Al-Ghamdi, A.Iqbal, A sustainability comparison between conventional and high-
speed machining, J. Clean. Prod. 108 (2015) 192–206.
[37] G.T.Burstein, S.P.Mattin, The nucleation of corrosion pits on stainless steel, Philos. Mag.
Lett. 66 (1992) 127–131.
[38] G.T.Burstein, C.Liu, R.M.Souto, S.P.Vines, Origins of pitting corrosion, Corros. Eng. Sci.
Technol. 39 (2004) 25–30.
159
[39] K.N.Lyon, T.J.Marrow, S.B.Lyon, Influence of milling on the development of stress
corrosion cracks in austenitic stainless steel, J. Mater. Process. Technol. 218 (2015) 32–
37.
[40] P.E.Manning, D.J.Duquette, W.F.Savage, The effect of test method and surface condition
on pitting potential of single and duplex phase 304L stainless steel, (1979) 151–157.
[41] D.Kuhlmann-Wilsdorf, N.Hansen, Geometrically necessary, incidental and subgrain
boundaries, Scr. Metall. Mater. 25 (1991) 1557–1562.
[42] D.A.Hughes, N.Hansen, D.J.Bammann, Geometrically necessary boundaries, incidental
dislocation boundaries and geometrically necessary dislocations, Scr. Mater. 48 (2003)
147–153.
[43] B.Verlinden, J.Driver, I.Samajdar, R.D.Doherty, Thermo Mechanical Processing of
Metallic Materials, first ed., Pergamon Materials Series, Great Briton, 2007.
[44] W.Pantleon, Resolving the geometrically necessary dislocation content by conventional
electron backscattering diffraction, Scr. Mater. 58 (2008) 994–997.
[45] S.K.Shekhawat, R.Chakrabarty, V.Basavaraj, V.D.Hiwarkar, K.V. Mani, P.J.Guruprasad,
A.A.Benzerga, K.G.Suresh, I.Samajdar, Orientation-dependent plastic deformation in
transformer steel: Experiments and dislocation dynamics simulations, Acta Mater. 84
(2015) 256–264.
[46] C.G.Rhodes, A.W.Thompson, The composition dependence of stacking fault energy in
austenitic stainless steels, Metall. Trans. A. 8 (1977) 1901–1906.
160
CHAPTER 6
Concluding Remarks
This thesis started with the objective of relating “plastic deformation and localized corrosion in
austenitic stainless steels”. This was achieved through three independent chapters (chapters 3-5),
which are also stand-alone journal publications. Three different grades (Sanicro 28TM
, AISI
(American iron and steel institute) 316L and AISI 304L) were selected in this study. Sanicro TM
28 is a product sold and marketed by Sandvik . The product is sold under the trademark
SanicroTM
28 and has been referred to as alloy A in this thesis.
It was shown earlier [1,2] that low or high plastic deformation followed by annealing shows
improved resistance to sensitization. This has been related to the so-called effective grain
boundary energy [1,3] high concentration of low CSL or random boundaries were shown to
improve resistance to sensitization. It was argued [4] that at higher plastic deformation
recrystallization is dominated by nucleation from shear bands, with a corresponding increase in
random boundary concentration. Low strain plastic deformation and recovery, on the other hand,
was speculated to increase low CSL (or low energy) boundary concentration: the classical
‘boundary tension’ model [5]. Though the classical study [2] supports such a speculation, it does
not rule out the role of remnant plastic deformation.
This was the basis for the third chapter. It was shown than barring significant deformation-
induced grain fragmentation, remnant plastic deformation always improved resistance to
sensitization. A combination of microtexture plus profilometry (from WLI or white light
interferometry) related orientation gradients in individual grains with post-sensitization depth of
attack. Plastic deformation of poly-crystalline material leads to near boundary mesoscopic shear
(NBMS) [6]. It is important to note that magnitude of this shear can be even two orders of
magnitude over the imposed real strain. For example, it was shown [6] that poly-crystalline
Zirconium under 1% plane strain compression showed an NBMS of 1.3. The NBMS leads to
near boundary gradients in orientation/misorientation: the so-called near boundary gradient zone
(NBGZ) [7–9]. Chapter 3 shows that the relative dimensions of the NBGZ determined the
161
average depth of post-sensitization attack. This chapter thus provides an alternate (and novel)
technique: resistance to sensitization through controlled plastic deformation.
Plastic deformation, in general, is expected to affect the passivation behavior in austenitic SS.
Local corrosion, which is of critical importance, depends of the relative presence of Cr2O3
passive film. As shown in chapter 4, such films are of 2-4 nm thicknesses. The relative thickness
may vary with imposed plastic strain and/or alloy chemistry, and the relative presence of Cr2O3
film is expected to determine the local corrosion performance. However, quantifying the Cr2O3
presence with respect to substrate microstructure appears daunting. This was achieved in chapter
4: combined tools of EBSD and FTIR-imaging. Chapter 4 not only establishes this novel route
for electrochemical studies, it also uses it to resolve an engineering question. It was observed,
through bulk electrochemistry, that maximum degradation in corrosion performance happened in
alloy A. This plus the fact that alloy A did not have strain induced martensite formation (SIMF)
raises questions on the conventional wisdom that SIMF is detrimental to corrosion performance.
EBSD plus FTIR-imaging brought definitive answer. It was shown, large statistic of direct
observations, that (i) strain localizations had lower presence/retention of Cr2O3 film while (ii)
regions with SIMF had stronger Cr2O3 presence
The third part (chapter 5) dealt with the changes in microstructure and in the relative presence of
Cr2O3 in sub-surface of machined specimens. Clear correlations were established with machining
speed and temperature dependent thermal conductivity. Though standard anodic
potentiodynamic polarization failed to quantify the sub-surface damage, the latter was estimated
from local developments in misorientations and residual stresses and from the relative presence
of Cr2O3 films. Surface roughness as well as the sub-surface damage were shown to reduce with
machining speed or imposed strain rate. This effect was most significant in alloy A, which is
explainable from experimental observations on temperature dependent thermal conductivity
values of the respective grades. This thesis thus offers certain novelty. Its niche is in adopting
different techniques (EBSD+WLI or EBSD+FTIR-imaging) and then employing them for
solving actual engineering problems (resistance to sensitization and local passivation). The
potential of such studies raises excitement. This thesis makes a beginning in the effective
correlation of localized corrosion and substrate microstructure.
162
References
[1] D.N.Wasnik, V.Kain, I.Samajdar, B.Verlinden, P.K.De, Resistance to sensitization and
intergranular corrosion through extreme randomization of grain boundaries, Acta. Mater.
50 (2002) 4587–4601.
[2] M.Shimada, H.Kokawa, Z.J.Wang, Y.S.Sato, I.Karibe, Optimization of grain boundary
character distribution for intergranular corrosion resistant 304 stainless steel by twin-
induced grain boundary engineering, Acta. Mater. 50 (2002) 2331–2341.
[3] N.Parvathavarthini, S.Mulki, R.K.Dayal, I.Samajdar, K.V.Mani, B.Raj, Sensitization
control in AISI 316L(N) austenitic stainless steel: defining the role of the nature of grain
boundary, Corros. Sci. 51 (2009) 2144–2150.
[4] D.N.Wasnik, Grain boundary nature and localized corrosion in austenitic stainless steels,
IIT Bombay PhD Thesis. (2004).
[5] M.H.F.J.Humphreys, Recrystallization and related nnealing phenomena , Second Ed.
Elsevier. (2004).
[6] N.Keskar, S.Mukherjee, K.V.M.Krishna, D.Srivastava, G.K.Dey, P.Pant, R.D.Doherty,
I.Samajdar, Quantifying the mesoscopic shear strains in plane strain compressed
polycrystalline zirconium, Acta. Mater. 69 (2014) 265–274.
[7] D.Raabe, Z.Zhao, S.J.Park, F.Roters, Theory of orientation gradients in plastically
strained crystals, Acta. Mater. 50 (2002) 421–440.
[8] S.K.Mishra, P.Pant, K.Narasimhan, A.D.Rollet, I.Samajdar, On the widths of orientation
gradient zones adjacent to grain boundaries, Scripta. Mater. 61 (2009) 273–276.
[9] S.Raveendra, A.K.Kanjarala, H.Paranjape, S.K.Mishra, S.Mishra, L.Delannay,I.Samajdar,
P.VanHoutte, Strain mode dependence of deformation texture developments:
microstructural origin, Metall.Mater.Transcations A. 42A (2011) 2011-2113.
163
List of Publications
1. N.Srinivasan, V.Kain, N.Birbilis, K.V.Mani Krishna, S.Shekhawat, I.Samajdar, Near boundary
gradient zone and sensitization control in austenitic stainless steel, Corrosion Science 100 (2015)
544-555.
2. N.Srinivasan, V.Kain, N.Birbilis, B.Sunil Kumar, P.M.Ahmedabadi, M.N.Gandhi, P.V.
Sivaprasad, G.Chai, A.Lodh, I.Samajdar, Plastic deformation and corrosion in austenitic stainless
steel:A novel approach through microtexture and infrared spectroscopy, In Press Corrosion
Science.
3. N.Srinivasan, V.Kain, N.Birbilis, S.S. Joshi, P.V. Sivaprasad G. Chai, S. Bhattacharya, A.
Durgaprasad, I. Samajdar, Defining the post-machined sub-surface in austenitic stainless steel,
submitted to Corrosion Science.
4. N.Srinivasan, A.K.Revelly, V.Kain, I.Samajdar, C.R.Hutchinson, P.Sivaprasad, Anodic
polarization of behavior of cold worked austenitic stainless steel, Advanced Materials Research
794 (2013) 632-642.
5. N.Srinivasan, V.Kain, I.Samajdar, M.N Gandhi, Anodic polarization behaviour of cold worked
austenitic stainless steels: A novel approach, APCCC 17, Asian Pacific Corrosion Control
Conference 17, IIT Bombay, Mumbai, India 27-30 Jan 2016.
6. N.Srinivasan, V.Kain, M.N Gandhi, I.Samajdar, Passivation behavior and chromium oxide
(Cr2O3) studies of austenitic stainless steels, CORSYM 2015, International Corrosion Prevention
Symposium for Research Scholars 2015, IIT Madras, Chennai, India 31July -1Aug 2015.
7. N.Srinivasan, V.Kain, I.Samajdar, K.Narasimhan, C.R.Hutchinson, Effect of heat treatment on
sensitization behavior of cold rolled AISI 304L stainless steel, International corrosion conference
expo, CORCON 2012, Goa, 26-29 Sep 2012.
