6. Pollak - EOARD Materials

EOARD Materials & NanotechAFOSR Spring Review

18 March 2011

Lt Col Randall ‘Ty’ Pollak

Program Manager

AFOSR/EOARD

Air Force Office of Scientific Research

AFOSR

Distribution A: Approved for public release; distribution is unlimited. 88ABW-2011-0796

2

Discussion

• My background

• Broad portfolio overview

• Challenges & opportunities of interest

• Selected projects

Distribution A: Approved for public release; distribution is unlimited. 88 ABW Case Number XXXXXX

3

Materials BackgroundMy Road to London

• PhD, MS&E, AFIT 2005

Gigacycle fatigue test methods

• AFRL/RX, Oct 05–Jul 06

Metallic thermal protection system roadmap

Electronic and optical materials (line mgmt)

• Naval Postgraduate School, Jul 07–Sep 10

Modeling Lamb waves for crack detection (SHM)

Carbon nanotubes (CNTs) for crack detection,

strengthened joints, and heat xfer nanofluidsClustered network of CNTs

Bily/Kwon/Pollak, Appl Compos Mater 17 (2010)

CNTs functionalized with carboxyl side groups

Burkholder/Kwon/Pollak, J Mater Sci (2011)

CNT nanofluid

Maximum likelihood analysis of Ti-6Al-4V data

Pollak/Palazotto, Probabilist Eng Mech 24 (2009)


4

EOARD Portfolio Overview

NAME: Lt Col Pollak

BRIEF DESCRIPTION OF PORTFOLIO:

Find, fund, and/or facilitate Materials S&T in Europe, Middle East, former

Soviet Union, and Africa for future air, space, cyberspace applications

LIST SUB-AREAS IN PORTFOLIO:

Structural & extreme

environment materials

Electronic, optical, &

magnetic materials

Materials for energy

applications

Materials development

& modeling tools


5

2010 Active Efforts

Russia

High-temp superconductors

Ukraine

Tribology & coatings

Super/magneto-elastic alloys

Ceramic composites

Ultrasonic sensing

UK

Morphing skin materials

High strain rate analysis

Romania

Functionalized DNA

Israel

Silicon-air batteries

Belgium

2-D conjugated polymers

The Netherlands

Hybrid superconductors

Atomic clusters

Austria & Czech Republic

High-temp nanocoatings

France

Multiscale modeling

Organic EO polymers

Portugal

Liquid crystals

Spain

Nano shape memory alloys

Germany

High-throughput experimentation

Italy

Catalytic nanostructures

Ultra high-temp ceramics

Switzerland

High-thruput tribology

Morocco & Egypt

CSP only


6

Electronic, optical, magnetic materials

Structural / extreme environment materials

Materials tools

Materials for energy

Which Way to Go?


7

Evolution of Materials ScienceShaping Challenges & Opportunities Ahead

Processing

Structure

Properties

Performance

YESTERDAY / TODAY TODAY / TOMORROW

Design / analysis at

micro-level Design / analysis at

nano & atomic-level

Properties

as outputIntegrated and

inverse design

1 test 1 data point

High-throughput methods

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

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1.0

Pt [a

t.%]P

d [at.%

]

Fe [at.%]

Descriptive modeling Predictive modeling

Destructive / post-

mortem imaging

Non-invasive / near

real-time imaging

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Broad Scientific Challenges…and Transformational Opportunities

• Predicting compositions and micro/nanostructures of interest for

structural, high temperature, and other materials

Ab initio methods, multi-scale methods, improving computational efficiency

• Rapid screening for mechanical and environmental properties

Bulk properties vs. micro/nano-scale properties, methods of accelerating

degradation, novel rapid fabrication techniques

• Utilizing more available data from conventional tests

Volumetric imaging, quantification of features, novel test techniques

• Consideration to actual state & its evolution in predictive models

Get ―enough but no more‖ data to characterize state, correlate / validate

SHM/NDE techniques, appropriate inputs to damage models

• Other emerging capabilities of AFRL interest?

Enabling future capabilities…

-- Tailor the material systems and structures for the application

-- Efficiently screen and test to validate models and optimize parameters

-- Predict residual properties based on actual state of component

9

Selected Projects

• High-throughput experimentation

• Nanopillar shape memory alloys

• Morphing skin materials

• High strain rate simulation

• X-ray tomography for composites fatigue

10

High-Throughput ExperimentationOptical Screening for Amorphous Materials

Prof Alfred Ludwig, Ruhr Univ Bochum (Germany), Sep 2010 – Aug 2011

EOARD funded (Materials & Space Tech)

Tech POC: Dr Dan Miracle, RXB

Images: Ludwig and RUB Dept of Micro & Nano Materials website

Unique combinatorial sputtering system

Challenge: Metallic glasses are of interest due to remarkable

properties (strength, ductility, corrosion resistance)… but time

consuming and expensive to wade through solution space

Objective: Rapidly develop materials libraries of metallic

glasses which exhibit high crystallization temps and superior

corrosion resistance in O2 environment Alloy gradient compositions using

up to 5 targets on 4-inch wafers

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High-Throughput Experimentation(continued)

300 400 500 600 700 800 9000.0010

0.0015

0.0020

0.0025

0.0030

0.0035

717 K

[

Ohm

*m

]

T [K]

689 K

Ramp rate: 1.7 K/s

Approach:

1. Deposit amorphous thin films

2. Determine compositions through automated EDX

3. Characterize structure through automated XRD

and high-throughput resistivity tests as f(T)

4. Develop optical screening method based on

change in reflectivity upon phase change

5. Use reflectivity changes to characterize corrosion

resistance for alloys with high crystallization temp

Automated x-ray diffraction of wafers

(capability -100ºC to 900ºC)

Images: Ludwig and RUB Dept of Micro & Nano Materials website

Resistivity changes indicate crystallization

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

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1.0

Pt [a

t.%]P

d [at.%

]

Fe [at.%]

-1.000

0.3667

1.733

3.100

4.467

5.833

7.200

8.567

9.933

11.30

12.67

14.03

15.40

16.77

18.13

19.50

20.87

22.23

23.60

24.97

26.33

27.70

29.07

30.43

31.80

33.17

34.53

35.90

37.27

38.63

40.00

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

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1.0

Pt [a

t.%]P

d [at.%

]

Fe [at.%]0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

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Pt [a

t.%]P

d [at.%

]

Fe [at.%]

40°C

190°C

210°C

Color code:

Intensity change

proportional to

oxidation

First results of parallel optical screening

of oxidation in air for Fe-Pt-Pd system

(Amorphous Ni-Ti-

based alloy)

12

Nanopillar Shape Memory AlloysNanostructures for Ultra High Damping

Prof Jose San Juan, Univ of Basque Country (Spain), Jul 2010 – Jul 2011

EOARD funded 1st year AFOSR planning 2nd year (Dr Les Lee)

Images: San Juan and San Juan/Nó/Shuh, Nat Nanotechnol 4 (2009)

Challenge: Materials with significant energy absorption / damping

capability needed for blast mitigation and vibration suppression

Objective: Develop large area micro/nano pillars of Cu-Al-Ni shape

memory alloy (SMA) exhibiting high damping (Phase 2—multilayers)

Damping comparison

Damping proportional

to area enclosed

FIB milling

13

Nanopillar Shape Memory Alloys(continued)

Approach (Phase 1):

1. Produce single crystal Cu-Al-Ni slides

2. Produce micro-pillar arrays by optical microlithography (design/optimize process)

3. Characterize microstructure and martensitic transformation (SEM/SPM)

4. Nano-indentation & nano-compression of individual pillars – compare to FIB samples

5. Design new micro-compression test for multi-pillar array

I. Elastic deformation

of the Austenite Pillar

II. At a critical stress cMartensite is induced

II to III Martensite variants compatible

with the applied stress are induced

III. All the Austenite could be

transformed to Martensite

IV. The transformation is

reversible during unloading

Recovery when the stress is withdrawn

SMA transformation

Micro/nanopillar testing has shown

100s of cycles w/o residual strain

Images: San Juan and San Juan/Nó/Shuh, Adv Mater 20 (2008)

14

Development of Morphing SkinsExample of a Transition Success

Challenge: Morphing skin materials must

allow large area change yet remain strong

Woven/cross-ply reduces area in shear,

but not extensional deformation; while

knitted fabrics have limited elongation

range, less strength, harder to manufacture

Dr Prasad Potluri, Univ of Manchester (UK), Sep 2008 – Nov 2010

EOARD seed funds AFRL/RX funding

Tech POC: Dr Jeff Baur, RXBC

Objective: Develop hyper-elastic yarns for use in woven/cross-ply fabrics

Images: Potluri, AFRL-AFOSR-UK-TR-2010-0003

Tunable by altering

parametersLow modulus

High modulus

Knee point

15

Development of Morphing Skins(continued)


Biaxial braid set-up

Creating a biaxial braided sample

Triaxial braided yarn

Relaxed vs. stretched(larger extensions in triaxial)

16



Results: Experimental testing & analytical

modeling of yarns in tension skin material

then manufactured, tested, and modeled

Triaxial yarns with

silicone matrix

Influence of matrix

modulus (E) Added: Development and shipment

of 3-D weaving machine for AFRL/RX

(next slide)

17


Possibilities for use and further collaboration:

• Design/manufacture 3D woven preforms with

various fibers (carbon, glass, ceramic, hybrids)

• Geometrical and meso-mechanical modeling of

textile composites

• Modeling of 3D woven preforms subjected to

forming forces (compaction, in-plane shear,

biaxial tension and bending)

• Addition of smart sensors/actuators in 3D weaves

• Development of novel morphing skins

Image: Potluri, development as of Jan 2010

To be shipped to AFRL/RX after training at

Univ of Manchester (Spring 2011)

18

High Strain Rate AnalysisUsing Low Strain Rate Analogue

Dr Clive Siviour, Univ of Oxford (UK), Sep 2009 – Sep 2013

AFRL/RW funding, Tech POC: Dr Jennifer Jordan, RWME

Images: Moser/Nau (Fraunhofer EMI), from High Resolution Damage Diagnostics & Predictive Modeling Workshop (2010)

Challenge: Mechanical response and damage at high strain rates is of key importance to

design more tolerant and functional materials, but timescales of real-time diagnostics and

imaging techniques are generally inadequate at high strain rates

Objective: Develop analogue techniques using low strain rate tests at different temperatures

to mimic high strain rate behavior

Polymers (e.g., rubbers in

plastic bonded explosives)

are particularly difficult to

characterize at high rates

• Project will study PVC w/ plasticizer

Funding 3-year PhD student

(extension to 4 years due to

delay in matriculation)

• WOS to Eglin planned for Jun 11

19

Growing Interest in 3-DCharacterization Methods

0

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* ISI Web of Science search: ―x-ray‖ + ―tomography‖ (for subject areas which include ―materials science‖)

DARPA/ONR Dynamic 3-D Digital

Structure Program (FY05-10)

Public

ations*

Snapshots of growing grain using x-ray topotomography

Ludwig et al, Mat Sci Eng A-Strut 524 (2009)

Jun 2010 – ONRG Workshop I

Mar 2011 – ONRG/EOARD Workshop II

20

3-D Characterization ExampleFatigue of Low-Cost Composites using XCT

First of its kind void analysis and

comparison with fatigue performance

Only possible thru non-invasive CT

Images: Lambert/Chambers/Sinclair/Spearing , Univ of Southampton (publication in preparation, used with permission)

Micro XCT imaging

Reconstructed microstructure of glass/epoxy specimen

21

3-D Characterization Example (continued)

Specimen Cycles to

failure

()

Number of

voids in

analysis

volume

Void

content

(%)

Average

void

volume

(mm3)

Volume of

the largest

single void

(mm3)

Total

volume of

largest 1%

of voids

(mm3)

C9 21,649 9,831 3.22 0.0119 2.48 42.29

C14 32,003 10,598 2.95 0.0115 2.10 40.18

C10 59,697 14,255 2.75 0.007 1.62 40.33

C13 60,710 10,583 3.27 0.0115 1.79 40.11

C20 107,725 10,827 2.52 0.0087 0.89 31.70

0

20,000

40,000

60,000

80,000

100,000

120,000

0 0.5 1 1.5 2 2.5 3

Largest Void Volume (mm3)

Life

(cycle

s)

Inner ply delamination reduced

global buckling load by 87%

Data for compressive failures under fully-reversed loading:

Data and Micrographs: Lambert/Chambers/Sinclair/Spearing , Univ of Southampton (publication in preparation, used with permission)

22

Understanding Fatigue Damage inComposites through Microtomography

Images: Sinclair/Spearing

Challenge: Accurate modeling / prediction of damage processes in composites requires

identification, quantification, and understanding of key internal microscale features

Objective: Use high-res XCT to investigate fatigue of fiber-reinforced aerospace composite

– identify critical features, develop detection techniques, statistically quantify, link to models

Expected Payoffs: Insights, inputs, and validation for AFRL composite materials damage

modeling, jumping point for future investigations exploiting tomography data

In situ XCT of carbon/epoxy composite damage

Transverse (90º) cracking

Longitudinal (0º) cracking

Delamination

0º fiber breaks

Prof Ian Sinclair and Prof Mark Spearing, IN DEVELOPMENT FOR 2011

EOARD (w/ ONRG contribution) to fund 3-yr PhD student

23

Theme for Way Ahead

Needs Background

Opportunities

• Failure of structural materials

• Nanotech for structural,

thermal, & health monitoring

• Probabilistics / T&E / Sys Eng

• Better / more predictive modeling

• Optimizing parameters at nanoscale

• Reduce materials development cycle

• European excellence in hybrids and composites

• High-throughput experimental and predictive technologies

• High-resolution imaging capabilities

• DoD interest and activity in non-invasive characterization

Reduce development cycle by

developing novel data-rich

methods to predict, develop, test,

& monitor aerospace materials

24

Wrap Up

• Portfolio spans materials

spectrum supporting AFRL

• Looking for technologies with

relatively broad impact to reduce

materials development cycle

• Emphasis on structural and

environmental, but not exclusive

Lt Col Randall ‗Ty‘ Pollak

EOARD

Unit 4515

APO, AE 09421-0014

DSN 314-235-6115

Comm +44 1895-616115

[email protected]

([email protected])

25

AFRL Technical Links

Munitions

Dr Bill Cooper (blast effects & energetics)

Dr Jennifer Jordan (energetic materials)

Materials & Manufacturing

AFOSR

Dr Michael Berman

Dr Hugh DeLong

Dr Fariba Fahroo

Dr Charles Lee

Dr Les Lee

Dr Mark Maurice

Dr Ali Sayir

Dr David Stargel

RXL – Metals, Ceramics, NDE

Dr Mike Cinibulk (ceramics)

Dr Dennis Dimiduk (computational MS&E)

Dr Jim Larsen (behavior & life prediction)

Dr Eric Lindgren (non-destructive evaluation)

Dr Pat Martin (metals)

Dr Lee Semiatin (processing)

Dr Mike Uchic (microscale testing)

RXB – Nonmetallic Materials

Mr Max Alexander (EM hardening materials)

Dr Jeff Baur (hybrids, composites)

Dr Rick Hall (computational methods)

Dr Benji Maruyama (carbon nanotubes)

Dr Dan Miracle (nanotech, amorphous)

Dr David Mollenhauer (composites)

Dr Rajesh Naik (nanomaterials)

Dr Ajit Roy (thermal transport materials)

Dr Andrey Voevodin (high temp materials)

RXP – Survivability & Sensor Materials

Dr Jim Grote (organic polymer photonics)

Dr Ruth Pachter (materials modeling)

Dr Augustine Urbas (metamaterials)

Air Vehicles

Dr Ed Forster (hybrid materials)

Dr Nelson Forster (engine materials)

Dr Lewis Rosado (engine materials)

Dr Larry Scanlon (solid state ionics)

Propulsion

Continue to develop based on needs and opportunities…


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6. Pollak - EOARD Materials