182205352-Surface-Contamination-and-Cleaning-pdf.pdf

7/25/2019 182205352-Surface-Contamination-and-Cleaning-pdf.pdf

1/372

Surface Contaminationand Cleaning,

Volume 1

K.L. Mittal,

Editor

VSP


2/372

Surface Contamination and Cleaning, Volume 1


3/372

This page intentionally left blank


4/372

SURFACECONTAMINATION

AND CLEANING

VOLUME 1

Editor:

K.L. Mittal

UTRECHTBOSTON2003


5/372

VSP BV Tel: +31 30 692 5790P.O. Box 346 Fax: +31 30 693 20813700 AH Zeist [email protected] Netherlands www.vsppub.com

VSP BV 2003

First published in 2003

ISBN 90-6764-376-9

All rights reserved. No part of this publication may be reproduced, stored in a retrieval

system, or transmitted in any form or by any means, electronic, mechanical, photocopy-

ing, recording or otherwise, without the prior permission of the copyright owner.

Printed in The Netherlands by Ridderprint bv, Ridderkerk


6/372

Contents

Preface vii

Mapping of surface contaminants by tunable infrared-laser imagingD. Ottesen, S. Sickafoose, H. Johnsen, T. Kulp, K. Armstrong,S. Allendorf and T. Hoffard 1

Monitoring cleanliness and defining acceptable cleanliness levels

M.K. Chawla 23

Tracking surface ionic contamination by ion chromatography

B. Newton 43A new method using MESERAN technique for measuring surfacecontamination after solvent extraction

M.G. Benkovich and J.L. Anderson 49

Methods for pharmaceutical cleaning validationsH.J. Kaiser 75

Influence of cleaning on the surface of model glasses and theirsensitivity to organic contamination

W. Birch, S. Mechken and A. Carr 85

Decontamination of sensitive equipmentR. Kaiser and K. Haraldsen 109

The fundamentals of no-chemistry process cleaningJ.B. Durkee II 129

Development of a technology for generation of ice particlesD.V. Shishkin, E.S. Geskin and B. Goldenberg 137

Cleaning with solid carbon dioxide pellet blastingF.C. Young 151

Development of a generic procedure for modeling of waterjetcleaning

K. Babets and E.S. Geskin 159


7/372

Contentsvi

Experimental and numerical investigation of waterjet derustingtechnology

K. Babets, E.S. Geskin and B. Goldenberg 173

Practical applications of icejet technology in surface processingD.V. Shishkin, E.S. Geskin and B. Goldenberg 193

Correlating cleanliness to electrical performanceT. Munson 213

Qualifying a cleaning system for space flight printed wiring assembliesJ.K. Kirk Bonner and A. Mehta 225

Investigation of modified SC-1 solutions for silicon wafer cleaning

C. Beaudry and S. Verhaverbeke 241

Performance qualification of post-CMP cleaning equipmentin a semiconductor fabrication environment

M.T. Andreas 249

Spatial and temporal scales in wet processing of deep

submicrometer featuresM. Olim 261

Microdenier fabrics for cleanroom wipersJ. Skoufis and D.W. Cooper 267

Fine particle detachment studied by reflectometry and atomicforce microscopy

A. Feiler and J. Ralston 279

Dust removal from solar panels and spacecraft on MarsS. Trigwell, M.K. Mazumder, A.S. Biris, S. Anderson and C.U. Yurteri 293

Laser cleaning of silicon wafers: Prospects and problemsM. Mosbacher, V. Dobler, M. Bertsch, H.-J. Mnzer, J. Boneberg andP. Leiderer 311

Particle removal using resonant laser detachmentK. Kearney and P. Hammond 335

The future of industrial cleaning and related public policy-makingC. LeBlanc 345


8/372

Surface Contamination and Cleaning, Vol. 1, pp. viiviii

Ed. K.L. Mittal

VSP 2003

Preface

This volume chronicles the proceedings of the International Symposium on Sur-fase Contamination and Cleaning held under the aegis of MST Conferences in

Newark, New Jersey, May 2325, 2001.Even a cursory look at the literature will evince that there has been tremendous

interest and R&D activity in the arena of surface contamination and cleaning, sowe decided to organize this symposium. Because of the importance of this topicin many technological areas, tremendous efforts have been devoted to devisenovel and more efficient ways to monitor, analyse and characterize contaminationon surfaces as well as ways to remove such contamination from a wide variety of

surfaces.The ubiquitous nature of surface contamination causes concern to everyone

dealing with surfaces, and the world of surfaces is wide and open-ended. A con-taminant is defined as unwanted matter or energy or material or energy in the

wrong place. Also contaminants can by broadly classified as: film-type, particu-lates; ionic, and biological or microbial. The technological areas where surfacecontamination has always been a bete noireand thus surface cleaning is of cardi-

nal importance are too many and range from aerospace to microelectronics tobiomedical. Here a few eclectic examples will suffice to underscore the impor-tance of surface contamination and cleaning. In the world of ever-shrinking de-

vice dimensions in the microelectronics, the need to remove ever smaller particles(of nanosize dimension) is quite patent. On the other hand, film-type (organic)contamination is of crucial importance in the area of adhesive bonding, as even a

very thin layer of contamination can be very detrimental in attaining good bondstrength. In operation theaters, the concern about microbial contamination is alltoo obvious. So in light of the great concern about surface contamination, peopledealing with surfaces are rightfully afflicted with molysmophobia.*

The technical program for this symposium comprised 45 papers dealing withall kinds of contaminations on a host of surfaces, and many ramifications of sur-face contamination and cleaning were addressed. There were brisk and illuminat-ing (not exothermic) discussions, both formally and informally, throughout the

symposium. Also if comments from the participants are a barometer for the suc-cess of a symposium then this event was quite successful.Now coming to this volume, it contains a total of 24 papers (others are not in-

cluded for a variety of reasons). It must be recorded that all manuscripts were rig-orously peer reviewed and suitably revised (some twice or thrice) before inclusion

in this volume. So this volume is not a mere collection of unreviewed papers


9/372

Prefaceviii

which is generally the case with many symposia proceedings rather it reflectsinformation which has passed peer scrutiny. The topics covered include: mappingof surface contaminants; various techniques for cleaning surfaces; various tech-

niques for monitoring level of cleanliness; acceptable cleanliness levels, ioniccontamination; pharmaceutical cleaning validations; cleaning of glass surfaces;decontamination of sensitive equipment; no-chemistry process cleaning; waterjetcleaning; cleaning with solid carbon dioxide pellet blasting; cleanroom wipers;dust removal from solar panels and spacecraft on Mars; laser cleaning of siliconsurfaces; particle removal; implications of surface contamination and cleaning;and future of industrial cleaning and related public policy-making.

I sincerely hope that this volume addressing many aspects and recent develop-ments in the domain of surface contamination and cleaning will be of interest to a

wide range of people working in many different industries.

Acknowledgements

It is always a pleasure to write this particular segment of a book as it offers the

opportunity to thank those who helped in many ways. First, my sincere thanks areextended to my colleague and friend, Dr. Robert H. Lacombe, for taking care ofthe organizational aspects of this symposium. The comments from the peers are asine qua nonto maintain the highest standard of a publication, so I am most ap-

preciative of the time and efforts of the unsung heroes (reviewers) in providingmany valuable comments. I am profusely thankful to the authors for their interest,enthusiasm and contribution without which this book would not have seen the

light of day. In closing, my thanks go to the staff of VSP (publisher) for givingthis book a body form.

K.L. MittalP.O. Box 1280

Hopewell Jct., NY 12533

*Molysmophobia means fear of dirt or contamination, from Mrs. Byrnes Dictionary of Unusual,

Obscure, and Preposterous Words, University Books, Secaucus, NJ (1974).


10/372

Surface Contamination and Cleaning, Vol. 1, pp. 122

Ed. K.L. Mittal

VSP 2003

Mapping of surface contaminants by tunable

infrared-laser imaging

DAVID OTTESEN, SHANE SICKAFOOSE,HOWARD JOHNSEN,TOM KULP, KARLA ARMSTRONG, SARAH ALLENDORF and

THERESA HOFFARD1

Sandia National Laboratories, P.O. Box 969, MS 9403, Livermore, CA 94551-09691Naval Facilities Engineering Service Center, 1100 23rd Avenue, Port Hueneme, CA 93043-4370

AbstractWe report the development of a new, real-time non-contacting monitor for cleanlinessverification based on tunable infrared-laser methods. New analytical capabilities are required tomaximize the efficiency of cleaning operations at a variety of federal (Department of Defense[DoD] and Department of Energy [DOE]) and industrial facilities. These methods will lead to a re-duction in the generation of waste streams while improving the quality of subsequent processes andthe long-term reliability of manufactured, repaired or refurbished parts.

We have demonstrated the feasibility of tunable infrared-laser imaging for the detection of con-taminant residues common to DoD and DOE components. The approach relies on the technique ofinfrared reflection spectroscopy for the detection of residues.

An optical interface for the laser-imaging method was constructed, and a series of test surfaceswas prepared with known amounts of contaminants. Independent calibration of the laser reflectanceimages was performed with Fourier transform infrared (FTIR) spectroscopy. The performance ofboth optical techniques was evaluated as a function of several variables, including the amount ofcontaminant, surface roughness of the panel, and the presence of possible interfering species (suchas water). FTIR spectra demonstrated that a water film up to 7 m thick would not interfere with theeffectiveness of the laser-imaging instrument. The instrumental detection limit for the laser reflec-tance imager was determined to be on the order of a 10-20 nm thick film of a general hydrocarboncontaminant.

Keywords: Infrared; tunable-laser; imaging; cleaning; surface contamination.

1. INTRODUCTION

Real-time techniques to provide both qualitative and quantitative assessments of

surface cleanliness are needed for a wide variety of governmental and industrialapplications. The range of potential applications include aircraft, shipboard, vehi-cle, and weapon component surfaces to be coated, plated, or bonded. The avail-

To whom all correspondence should be addressed. Phone: (925) 294-3526,

Fax: (925) 294-3410, E-mail: [email protected]


11/372

D. Ottesen et al.2

ability of a convenient analysis technology for on-site, post-cleaning determina-tion of surface contamination will allow more rapid and accurate assessments ofthe efficiency of chosen cleaning techniques. By developing an on-line technique,

processed parts or extracted samples will not have to be sent to a separate labora-tory for analysis, thereby eliminating processing delays. The information providedby the optical method will assist the process operator in distinguishing betweenspecific contaminants and determining subsequent actions to be taken.

In this paper we report the development of an infrared laser-based imaging ap-proach that will reduce the use, emission, and handling of waste-stream materialsin cleaning operations. This work is supported by the separate development of a

hardened, portable Fourier transform infrared (FTIR) reflectance instrument at theNaval Facilities Engineering Service Center (NFESC), Port Hueneme, CA in co-

operation with the Surface Optics Corporation. Simultaneous development of anFTIR instrument is complementary in nature to the laser-imaging technique and isdescribed in detail elsewhere [1]. Both instruments will be used primarily for thereal-time on-line or nearly on-line detection of contaminant residues on reflectivesurfaces. In each case, surface contamination is detected by its absorption of a

grazing-incidence infrared beam reflected from the surface.The instruments differ in the nature of the information they provide. The laser-

based instrument produces images that directly indicate the spatial extent and lo-

cation of infrared-absorbing surface hydrocarbon contaminants. In contrast, FTIRinstrumentation provides a wide-band spectral measurement of the surface reflec-tance averaged over a small area for nearly all organic materials, and many inor-ganic components. Thus, the laser-imaging system allows the rapid determination

of surface cleanliness for organic residues over a large area, while the spectrally-resolved FTIR method is useful in identifying the specific molecular compositionof a surface contaminant at a particular location.

The imaging system under development employs a widely tunable infrared-laser illumination source in conjunction with an infrared camera. This approach

provides an on-line technique for surveying contamination levels over large sur-face areas in a real-time imaging mode. The laser is broadly-tunable over the 1.3-4.5 m wavelength range, thus allowing the detection of many hydrocarbon con-

taminants via absorption bands associated with CH-, OH-, and NH-stretching vi-brations.

Currently, the detection and identification of surface contaminants on reflectivesurfaces is conveniently and rapidly done by FTIR reflectance methods. Thesenon-destructive, non-contacting optical techniques identify the chemical constitu-ents of the contaminants, and can yield quantitative measurements with appropri-ate calibration. Infrared optical methods are particularly useful for cleanliness

verification since the surface is probed under ambient conditions. More sensitivehigh-vacuum electron and ion spectroscopic techniques (X-ray photoelectronspectroscopy, Auger electron spectroscopy, and secondary-ion mass spectrome-try) are not suited for on-line application.


12/372

Tunable IR-laser mapping of surface contaminants 3

Commercial instruments that employ infrared reflectance spectroscopy areavailable for surface analysis and provide both quantitative and qualitative infor-mation on surface coatings. These instruments are limited in their ultimate sensi-

tivity to surface contaminants by the nature of their optical design. Infrared radia-tion is focused onto the surface to be analyzed at a near-normal angle ofincidence, resulting in a compact hand-held apparatus. The infrared light is col-lected as either specularly or diffusely reflected radiation depending on theroughness and scattering properties of the surface [2, 3]. The resulting sensitivityto very thin layers of surface species is limited by poor coupling of the incidentelectromagnetic field with the vibrating dipoles of the surface molecular species

[4-6] in layers less than 0.1 m thick.In order to maximize the sensitivity of infrared reflectance measurements for

absorption bands of thin layers of contaminants on metallic surfaces, theoreticaland experimental studies [7-9] have shown that the angle of incidence of infrared

radiation on the surface should be increased to at least 60from the surface nor-mal. This is also true for many thin-film residues on the surface of non-metals,such as dielectrics and semiconductors (although the detectability of contaminantabsorption bands under these circumstances depends strongly on the optical con-stants of both surface and substrate, and any absorption features intrinsic to thenon-metallic substrate). Additional sensitivity in the reflectance measurement is

obtained by measuring only the component of the reflected infrared radiation po-larized parallel to the plane of incidence. This experimental method is variouslyreferred to as, grazing-angle reflectance spectroscopy or infrared reflection-absorption spectroscopy (IRRAS). We have adapted the technique of grazing-angle reflectance spectroscopy to utilize the newly developed tunable-lasersource.

2. EXPERIMENTAL

The laser-based instrument described in this report offers the capability to rapidlysurvey large surface areas and to determine the location and extent of residual hy-drocarbon contaminants following cleaning operations. In contrast, a spectro-scopic analysis by an FTIR-based infrared reflectance instrument is able to char-acterize a very broad range of organic constituents and many inorganic species.However, a surface-probing FTIR instrument measures a spectrum at only a sin-

gle small area on a sample, thus requiring broad area surveys to be done by se-quentially probing many points. Even at a rate of ~ 10 seconds per measurement

point, this can be a time-consuming process. The rate of measurement by FTIRspectroscopy is constrained by the relatively low spectral brightness (compared toa laser) of the incandescent illumination sources. This makes it necessary to userelatively long integration times to achieve an acceptable signal-to-noise ratio.

The tunable-laser-based instrument overcomes these limitations by illuminatinga broad surface area with a high-brightness infrared laser. This approach allows a


13/372

D. Ottesen et al.4

single-wavelength reflectance measurement over an area of several square centi-meters to be made on a timescale of less than a second. In order to acquire meas-urements at multiple wavelengths, the laser is tuned and an image is collected at

each of the desired wavelengths. While a detailed spectral map of a surface can begenerated over the laser tuning range, the primary use of the system is to providerapid areal surveys at a few key wavelengths that are indicative of hydrocarboncontaminants. The detection sensitivity for several hydrocarbon species at variousillumination wavelengths was evaluated in this work, as well as a method to sup-press image noise due to laser speckle while maintaining high illumination inten-sity.

2.1. Quasi-phasematching tunable infrared laser

The broadly-tunable infrared laser illuminator is based on a technology called

quasi-phasematching (QPM) [10]. This approach has been exploited to increasethe tuning range and power of the infrared light source while reducing its size. Forexample, continuous-wave (cw) optical parametric oscillators (OPOs) that employthe QPM material, periodically-poled lithium niobate (PPLN), are capable of tun-ing over the 1.3-4.5 m spectral region while emitting more than 0.5 W of power.This technique has been used to generate tunable infrared laser light for imagingnatural gas emissions, and developing laser-based spectroscopic gas sensors [10].

In this work we are extending it to the analysis of hydrocarbon residues on mate-rial surfaces.

The limit of the current tuning range of the PPLN-based laser at long wave-lengths is about 4.5 m (2222 cm-1) due to the transmission characteristics of lith-ium niobate. This property restricts the sensitivity of the chemical imaging systemto functional groups containing hydrogen atoms (C-H, N-H, O-H). Extension ofthe laser tuning wavelength range beyond 5 m (2000 cm-1) is desirable to pro-

vide specific identification of hydrocarbon and some inorganic molecular species.

The light source assembled for the IR imaging sensor is an OPO pumped by acontinuous-wave (cw) Nd:YAG laser, as shown in Figure 1 [10]. An electric fieldis induced in the OPOs PPLN crystal by the electric field of the pump laser; thesefields interact to form two new laser beams whose frequencies sum to the fre-quency of the pump laser. The reflectivities of the mirrors in the optical cavity areselected to resonate one of the generated waves, while the other wave is simplygenerated and released from the cavity. The resonated wave is called the signal;

the non-resonated wave is called the idler. The exact frequencies of the signal andthe idler are determined by the phasematching properties of the crystal (described

below), the reflectivity of the cavity, and by any spectrally-selective optics thatmay be added to the laser cavity (e.g. an talon). While either the signal or theidler beam can be used for measurements, only the idler is used in the experi-ments reported here.

As shown in Figure 1, the OPO used in the imaging sensor is of the bowtie-ring design. A diode-pumped, cw, multimode Nd:YAG laser (Lightwave Elec-


14/372


tronics, Mountain View, CA) that is capable of generating at least 6 W of outputpower at a wavelength of 1064 nm is used as the OPO pump source. Two flat mir-rors (M3 and M4) and two curved mirrors (M1 and M2, 50-mm radius of curva-ture), all coated to be highly reflective at the signal and highly transmissive at the

pump and idler wavelengths, form the bow-tie-shaped, single-wavelength reso-nant ring oscillator cavity designed to resonate the signal wave. An anti-reflection-coated lens, positioned between the pump laser and the OPO cavity,serves to image the Gaussian pump beam into the PPLN crystal. In this way, abeam waist (E-field radius) of 70 m is created in the center of the crystal, whichitself is centered between the two curved cavity mirrors. During normal operation,the OPO resonates on a single signal mode for minutes at a time, whereupon ithops to another cavity mode. The idler bandwidth is, however, determined by that

of the pump beam, which is 10-15 GHz.The use of the QPM material, PPLN, makes cw OPO operation more tunable

and efficient than it would be for a conventional birefringently phasematchedcrystal. Simply stated, phasematching is a condition in which all of the interactingwaves (i.e., signal, pump, and idler) maintain a specified relative phase relation-ship as they propagate through a nonlinear medium, and is a necessary conditionfor efficient nonlinear generation. In birefringent materials, phasematching is

Figure 1.Diagram of the PPLN OPO and projection optics.


15/372


16/372


The infrared laser light is incident on the sample surface at an angle of 60from the surface normal, and the specularly reflected component is detected by anInSb focal-plane array (FPA) camera with an infrared macro-lens assembly and

an array size of 256 x 256 pixels. The FPA camera is located approximately 0.3 mfrom the sample surface, and the resulting field of view is 20 x 35 mm.

FTIR instruments at both Sandia and NFESC were used to characterize themid-infrared spectra of contaminated surfaces via optical interfaces for grazing-angle reflectance spectroscopy. The system at NFESC uses a commercially avail-

able sampling accessory that permits a variable angle of incidence from 30 to 80,which is convenient for evaluating detection limits for contaminants on a varietyof surfaces. The optical interface used by the Sandia National Laboratories FTIR

instrument was constructed with a fixed 60angle of incidence with optics exter-nal to the spectrometer. It also differs from the NFESC system in the large solid-angle used both to illuminate the surface and collect reflected light. This feature isparticularly useful in the examination of rougher surfaces that cause significantscattering of the infrared beam, with a consequent degradation in both sig-nal/noise ratio and detection limits. Both systems use infrared polarizers to en-hance the sensitivity of the measurements by restricting the surface illumination

to p-polarization [4]. Unless otherwise noted, all reflectance spectra presented inthis paper are for p-polarized measurements.

2.2. Test sample preparation for calibration

In order to evaluate the usefulness of the laser-imaging technique as a cleaningverification method, we prepared a number of test surfaces with well-characterized levels of contamination. These were used to determine detectionlimits as a function of contaminant species, level of contamination, degree of sur-face roughness, effect of spectral interference, and instrumental parameters suchas angle-of-incidence. Seven candidate materials were chosen as contaminant

species for evaluation as shown in Table 1. These materials have proven to beparticularly difficult to remove during cleaning operations, and are representativeof many other organic contaminants encountered in government and industrialcleaning processes. Detailed measurements on the first four materials have beenmade in the course of this work and preliminary measurements have been madeon the remaining three.

A number of metals were chosen as substrates for the target contaminants,based on usage information obtained from military and contractor facilities. Thesewere Aluminum-7075-T6, Titanium 6Al-4V, Steel Alloy 4340, Stainless Steel

304, and Magnesium AZ31B. The metals were fabricated into 3.8 x 12.7 cm flatcoupons for laboratory testing and method demonstration.

Six surface roughness finishes of the Aluminum 7075-T6 test coupons wereobtained, ranging from 80 to 600 grit (600 grit being the smoothest). A profilome-

ter instrument was used to examine the surface roughness profiles and provideaverage Ravalues. A Ravalue is an arithmetic average of the absolute deviations


17/372

D. Ottesen et al.8

from the mean surface level, in millionths of an inch; therefore, a Ravalue of 1.5

= 0.00000015 inches (3.8 m). Due to the nature of metal-shop finishing proc-

esses, surface roughness values vary considerably across a given surface area.Finishing operations also result in a directional grain parallel to the samplecoupons longitudinal direction. Surface roughness measurements, therefore, ex-

hibit large variations between measurements taken along an orientation longitudi-nal or transverse to the polishing axis. Two surface roughness levels, 600 and 220grit, were obtained for the other metal alloys.

Prior to contaminant application, the aluminum alloy coupons were cleanedwith acetone and underwent sonication with a clean-rinsing aqueous cleaner.

They were then thoroughly rinsed in distilled water and dried in an oven at 50C.Once cooled, they were weighed on a microbalance with a precision of 0.01 mg.Two or three weighings were averaged.

Both drawing agent and lubricant contaminated Al-7075 coupons were pro-duced by two primary deposition methods airbrushing and manual brushing.Several other techniques were attempted, including wire-cator drawing, couponspinning, and manual drop and spread. These techniques were not used to pro-duce test samples for calibration for these particular contaminants due to the supe-rior results obtained from airbrushing and manual brushing. Three levels of draw-

ing agent were applied by airbrushing to three Al test coupons for each of the sixsurface finishes, creating a suite of 18 panels. Varying concentrations of drawingagent in water were prepared for the airbrush solutions. Similarly, four levels oflubricant were applied to four Al test coupons for each of six surface finishes,creating a suite of 24 panels. Manual brushing was used for all but the least con-taminated samples, which were airbrushed. Lubricant solutions for both tech-

Table 1.Contaminant materials used for preparation of test coupon for calibration

Material Description Usage

Drawing Agent White soft solid ester grease Metal drawing, cutting, andlubricating agent

Lubricant Brown liquid paraffin hydrocarbons Rust preventative, cleaner,lubricant, protectant formetals

Silicone Silicone Lubricant

Mold Release 1 Green liquid ethanol homopolymer Mold release agent

Mold Release 2 Clear liquid proprietary polymericresins

Mold release agent

Solder Flux Yellow liquid abietic acid oranhydride

Soldering flux for electricaland electronic applications

Hydraulic Oil

MIL-H-5606A AM2

Blue liquid castor oil base Hydraulic systems, shock andstrut lubricant


18/372


niques were prepared using pentane as the solvent. Similar methods were used inpreparing calibration samples with the mold release, solder flux, and hydraulic oilsamples.

All contaminated coupons were gently heated in an oven at 50C for severaldays to remove both semi-volatile and volatile components. This served to stabi-lize the contaminants, allowing for quantification by weighing. Once the weightsbecame stable, the coupons were cooled and weighed to determine the amount ofcontaminant present on the surface. When not being weighed or examined, thecoupons were kept in a desiccator.

3. RESULTS AND DISCUSSION

Grazing-angle incidence reflectance spectroscopy acts to enhance the detection

sensitivity for thin layers of residue predominantly through improved coupling ofthe electric field intensity of the incident beam with the vibrating dipoles of thesurface contaminant layer perpendicular to the metallic surface. Some additionalenhancement of the infrared absorption spectrum will also occur due to a length-ening of the effective path length through the absorbing thin film layer [4-6].

If the optical properties of both thin film and substrate are known (or can be de-termined), the reflection-absorption spectrum can be calculated as a function offilm thickness and angle of incidence. This capability is particularly useful for in-

terpreting experimental data and designing optical instrumentation. Computercodes written at Sandia [7] performed these calculations for a variety of materials.

3.1. FTIR measurements

FTIR reflectance data for the full drawing-agent sample set were obtained at

NFESC and Sandia using angles of incidence of 75 and 60 for average film

thickness ranging from 0.1 to 1 m, and aluminum substrates with surface finishranging from 600 to 80 grit. Since the surface finishing operation produced ahighly directional roughness, measurements were made both longitudinally andtransversely with respect to the polishing grooves. Ravalues were determined at

NFESC using profilometer measurements, and resulted in surface roughness val-

ues of 0.3 to 1.5 m for the longitudinal direction, and 0.5 to 6 m for the trans-verse direction.

The FTIR reflectance spectra were normalized using the uncoated back of apanel as a clean reference standard, and the intensity data are presented as either

reflectance or log reflectance in the following discussion. The C-H stretching vi-brations near 2900 cm

-1proved to be generally useful in quantifying instrument

response since these frequencies are well isolated from atmospheric interferencedue to water vapor and carbon dioxide. However, the baseline for these reflec-tance data was often non-linear. A simple single-point measurement of intensitywas therefore not sufficient to determine the instrument response function.


19/372

D. Ottesen et al.10

Optical constants (n and k) were derived for the contaminant C-H stretchingvibrations using the Sandia reflectance code and a dispersion model to calculate afit to the experimental data for one of the test coupons [7]. Reflectance-absorption

spectra for the 2800-3000 cm-1

range were calculated for 1-m thick films of aspecific hydrocarbon contaminant on an aluminum surface at either 60 or 75an-gle of incidence. This function was then used as a linear variable in conjunctionwith a second-order polynomial to produce a least-squares fit of the experimentalreflectance data for the test coupons. An example is shown in Figure 2 for the

longitudinal measurements of three thicknesses of drawing-agent contaminant at

Figure 2.Linear least-squares fit of experimental reflectance data for drawing-agent contaminant on

600 grit polished aluminum surfaces. Average film thickness: (Top) 0.9 m, (Middle) 0.4 m, (Bot-

tom) 0.1 m.


20/372


75angle-of-incidence. This procedure produces extremely rapid, robust analyses

of the FTIR reflectance data, even for very thin films in the presence of noise, andaccounts for baseline shifts and curvature due to interference fringes.

Fitting coefficients for the linear spectral function (which are proportional to theintegrated intensity) are plotted against the average calculated film thickness, andthese results are shown in Figures 3 and 4 for longitudinal and transverse reflec-

tance measurements at 75 and 60 angle-of-incidence, respectively. Results for

Figure 3. Integrated reflection-absorption intensity at 60 angle-of-incidence for C-H stretchingbands of drawing-agent films deposited on aluminum test coupons with varying degree of surfaceroughness (longitudinal, top; transverse, bottom).


21/372

D. Ottesen et al.12

the longitudinal, 60 angle-of-incidence follow a linear relationship with film

thickness except for the roughest surface finish (80 grit, Ra= 1.5 m). The instru-ment response functions for transverse measurements at 60angle-of-incidence arealso reasonably linear, with the same average slope as seen in Figure 3.

In contrast, analysis of the FTIR reflectance data at 75angle-of-incidence forboth longitudinal and transverse sample orientations shows a marked departure

from linearity at the highest values of film thickness (Figure 4). The initial slopes

Figure 4. Integrated reflection-absorption intensity at 75 angle-of-incidence for C-H stretchingbands of drawing-agent films deposited on aluminum test coupons with varying degree of surfaceroughness (longitudinal, top; transverse, bottom).


22/372


of the spectral response, the integrated reflection-absorption intensity, of thesesamples are slightly greater than the intensity of the spectral response of the same

samples measured via a 60angle of incidence data (Figure 3). This behavior is

expected due to the increase in reflection-absorption sensitivity with increasingangle of incidence. Here, too, the average initial slope (and hence instrument sen-sitivity) is the same for both transverse and longitudinal orientations.

The pronounced non-linearity in slope for the thickest films at 75 angle-of-incidence was unexpected. An increasingly non-linear response may be observed

for thicker absorbing films, and this effect will become more pronounced as theangle of incidence is also increased. The interpretation of the data implying thatmeasurement of a thicker film, sampled at a steeper angle, generated the observednon-linearity in the data is not substantiated by the calculated spectra for the pre-

sent measurement conditions due to the small change from 60 to 75in the angleof incidence. Furthermore, such a non-linear effect would be most pronounced formeasurements on the smoothest substrate (Figure 4, filled circles) where the ef-fective local orientation of the surface is most constant with respect to the illumi-nation beam. Instead of observing such non-linear behavior the measurements

made on the smoothest surface are by far the most linear sample series for the 75data.

We attribute the pronounced non-linearity of the 75data for the thickest draw-

ing-agent films to the morphological characteristics of the material as depositedon the aluminum test panel surface. As described above, the drawing-agent mate-

rial is highly viscous and forms a visibly heterogeneous white film at 1-m thick-ness. Variations in the deposition process produce relatively thick local areas ofdrawing-agent film and result in accretion of solid residue along the polishinggrooves and ridges of the aluminum substrate. Under these circumstances, illumi-

nation of the surface with the FTIR beam at an angle of 75may result in shadow-ing by contaminant material on ridge structures for all except the smoothest (600grit polish) surface. The 12-mm diameter focal area of the infrared beam is elon-

gated by a factor of four for this angle of incidence. In contrast, reflectance meas-

urements at 60result in only a factor of 2 elongation, and minimize the shadow-ing effect of thick films except for ridges on the roughest (80 grit polish) surfaces.

This interpretation is substantiated by reflectance data for the second test set(lubricant material) as shown in Figure 5. FTIR reflectance measurements have

been made at 75angle-of-incidence for a test series similar to that of the draw-ing-agent set. An analysis of the C-H stretching frequencies shows a strikinglymore linear dependence of instrument response with film thickness (with the ex-

ception of a single point for one of the panels with a 220 grit surface finish). Webelieve that this is due to the more fluid characteristic of the lubricant material,

which allows the deposited film to conform much more closely to the surface to-pography of the test coupons. This behavior may also account for the stronger de-pendence of the integrated intensity slope with surface roughness, when comparedto the nearly constant results for the drawing-agent contaminant examined above.


23/372

D. Ottesen et al.14

Figure 5.Integrated reflection-absorption intensities of C-H stretching bands for lubricant films de-posited on aluminum test coupons with varying degree of surface roughness for longitudinal illumi-nation.

Even though excellent sensitivity was demonstrated for common hydrocarboncontaminants using grazing-angle infrared reflectance spectroscopy, concerns re-

main due to potential interference from other molecular species that may be pre-sent in the measurement environment. Chief among these is water, resulting eitherfrom cleaning operations or the local environment. Water is a very strong infraredabsorber, and its presence on the surface to be measured may cause distortion orobscuration of the characteristic contaminant reflection spectrum.

We performed an evaluation of this interference using lubricant-contaminated

test panels with an average hydrocarbon thickness of 0.7 m on aluminum. A wa-ter film was created on the surface of the test coupon using an airbrush, and re-

flection-absorption measurements were acquired at a 75angle of incidence forseveral conditions. The thickness of the water film was difficult to determine dueto continuous evaporation during the reflectance measurements. We estimated thethickness by measuring coupon weight gain immediately prior to and following

the infrared measurements. Film thickness was calculated based on the averageweight gain.

Reflection-absorption spectra are presented in Figure 6 for three water films onthe lubricant-contaminated test panel. These water films range in thickness from 1

m (not visible to the eye) to 7 m (clearly visible to the eye). Substantial inter-ference is present in the 1700 cm

-1spectral range (not shown) due to the strong H-

O-H bending mode. This strong absorption obscures carbonyl absorption featuresthat may be present in some, but not all, hydrocarbon contaminant species. The


24/372


broad H-OH stretching bands centered near 3400 cm-1

, however, do not obscurethe C-H stretching bands near 2900 cm

-1. This is particularly important for the ef-

fective and accurate use of the tunable infrared-laser imaging instrument, sinceimages are acquired for only a small number of frequencies near 3000 cm-1, incontrast to the broad-band spectral data collected by the FTIR instrument.

3.2. Tunable infrared-laser imaging

Initial images of test panel surfaces were acquired at two frequencies (2915 and3000 cm-1) that correspond to highly absorbing and non-absorbing portions, re-spectively, of the hydrocarbon infrared spectrum (see above, Figures 2 and 6). Weused an acquisition time of 0.5 ms per frame, and averaged a minimum of 20frames for each frequency in order to reduce noise (shot noise and laser specklenoise). Although the InSb FPA camera is square (256 x 256 pixels), the aspect ra-

tio of the surface area scanned by the spectrometer and the resulting images inthis work are elongated by a factor of two due to the trigonometric effects of the

60angle of incidence and reflectance.Images were acquired for illumination transverse to the polishing direction.

They have been corrected for thermal background emission and normalized forsystem spectral response at the measurement frequencies. The normalization fac-

Figure 6.Potential interference effects of water on C-H stretching bands of hydrocarbon lubricant

film (0.7 m) on aluminum. Three thicknesses of water film were examined (1 m, top; 3 m, mid-

dle; and 7 m, bottom).


25/372

D. Ottesen et al.16

tor was determined by the average intensity ratio of a clean surface (the uncon-taminated back surface of the test panel) for the two measurement frequencies.

The ratios of successive images using the PPLN-based laser system showed anoise level of 0.44% for the entire 65,536-pixel image under our current operatingconditions. This noise level corresponds to a hydrocarbon film thickness of ap-proximately 10-20 nm for the species examined in this report, and is the primary

factor in determining the present instrumental detection limit.Gray-scale images at these two frequencies for the hydrocarbon drawing-agent

(thickness of 0.9m on aluminum) are shown in Figure 7. Structure in the imagesis primarily in the form of vertical lines that represent ridges in the aluminumsubstrate formed during surface polishing operations. A darker vertical band nearthe center of the image manifests the presence of an absorbing hydrocarbon in the

Figure 7.Gray-scale on-resonance (2915 cm-1, top) and off-resonance (3000 cm-1, bottom) images

for an aluminum test panel contaminated with hydrocarbon drawing agent of 0.9-m thickness.


26/372


2915 cm1 image. However, it is difficult to differentiate the absorbing organicfilm from the high contrast presented by the surface polishing marks in images ata single wavelength.

The image created from the ratio of the two images, corrected for thermalbackground and normalized for the average image intensity, is a relative reflec-

tance image, as shown in Figure 8 (A), assuming that the reflectance of the sub-strate remains constant at these two frequencies. Unprocessed image ratios suchas these show a periodic grid pattern due to coherent interference effects that tendto obscure the hydrocarbon image, and we have investigated several image en-hancement procedures to reduce noise while maintaining spatial resolution andcontrast in the reflectance ratio images. Weighted Gaussian smoothing in a 7 x 7pixel neighborhood and Fourier filtering have both been successful in suppressingthis noise without significant degradation in spatial resolution, as shown in Figure

8 (B). The image ratios presented in this report have all been Gaussian smoothed.Reflectance intensity profiles along the horizontal line in each image ratio are alsoshown in Figure 8 (C) and (D) to demonstrate the magnitude of laser coherencenoise and the effects of the smoothing procedure.

Figure 8.Reflectance images and line-intensity profiles for an aluminum test panel contaminated

with a hydrocarbon drawing-agent of 0.9-m thickness. Laser coherence noise (A) and results ofGaussian smoothing (C) are illustrated with corresponding intensity profiles (B and D, respectively)sampled along the horizontal lines superimposed on the images.


27/372

D. Ottesen et al.18

Examples of reflectance ratio images for several test surfaces are shown in Fig-ures 9 and 11 in false color. A calibrated color-table (Rainbow) for these false-color images is shown in Figure 10. Images for a series of 600-grit polished alu-

minum substrates contaminated with drawing agent are presented in Figure 9.These are the same specimens whose FTIR spectra are shown in Figure 2. Aver-

age film thicknesses for the three samples are 0.9 m (top, left), 0.4 m (middle,

left), and 0.1 m (bottom, left).The images are presented in false color format with identical dynamic range to

help visualize the location of contaminants. Hydrocarbon material was manuallydeposited along the orientation of the surface polishing grooves, which is oriented

vertically in these images. Heavy deposits of the hydrocarbon residue are easily

Figure 9.False-color reflectance images and thickness profiles for three aluminum test panels con-

taminated with a hydrocarbon drawing agent (thicknesses are: 0.9 m, top-left; 0.4 m, middle-left;

0.1 m, bottom-left). Corresponding line thickness profiles are shown to the right of each false-colorimage.


28/372


visible in the top reflectance image (red and yellow indicating the lowest reflec-tance, hence the thickest deposit, locations), with a particularly thick vertical bandnear the center. Very few areas in this image possess high reflectance values (darkblue) characteristic of low contamination. A horizontal line across the center ofthe image indicates the thickness profile, shown in Figure 9 (top, right) for thissample. Reflectance values have been converted to thickness of the drawing-agent

hydrocarbon contaminant using the FTIR data analysis discussed above. The datashown here indicate the thickness averaging about 0.7 m along the profile line,

with heavier deposits up to 2 m.False color images of the test surfaces contaminated with lower amounts of hy-

drocarbon (Fig. 9, middle and bottom) show much less spatial variation in the dis-tribution of hydrocarbon residue. Hydrocarbon residues are thinner and appear as

predominantly green and light blue in the false-color images while the line pro-files show quantitatively the thickness of lubricant in these images. The averagethickness values of the three profiles presented here are consistent with the weightchange and thickness values determined by FTIR.

The potential value of the infrared-laser imaging method for cleanliness verifi-cation is clearly demonstrated for these test panels. For these samples distributionof the residual hydrocarbon contaminant is quite variable. In the case of the

heaviest contaminated sample, a localized cleaning to effect substantial removalcan be profitably applied to the most heavily contaminated areas.

Figure 10.Color bar for false-color images presented in Figures 9 and 11. Film thickness was cali-brated by weight-gain measurements during sample preparation and by comparison with FTIR re-

flectance data.


29/372

D. Ottesen et al.20

We also acquired reflectance ratio images for test surfaces with rougher fin-

ishes for average hydrocarbon thicknesses of 0.9 m, again using transverse illu-mination. False-color images and corresponding thickness profiles for these two

samples are compared to the 0.9-m thick hydrocarbon residue deposited on the

smoothest, 600-grit polished surface in Figure 11. Average thickness values fromthe three profiles are in reasonable agreement for all three test panels, demonstrat-

ing that large changes in surface roughness (0.5, 2.1, and 6.1 m) do not substan-tially affect the measured thickness of hydrocarbon residue.

We observe a qualitative change in the false-color images in Figure 11. In-creasingly rough test surfaces (middle and bottom) exhibit a grainier image qual-

Figure 11.False-color reflectance images and thickness profiles for three aluminum test panels witha hydrocarbon drawing-agent contaminant (surface polishes are: 600-grit, top-left; 220-grit, middle-left; 80-grit, bottom-left). Corresponding line thickness profiles are shown to the right of each false-color image.


30/372


ity due to the large diversity of surface orientations relative to the infrared laser il-lumination beam. Distribution of the hydrocarbon residue on the 220-grit surface,however, is much more even (Fig. 11, middle, left) than for the smoothest surface

(Fig. 11, top, left). The drawing-agent material shows a strong thickness gradienttoward the right-hand side of the image for the roughest, 80-grit, surface (Fig. 11,bottom, left) that is clearly visible despite the grainy image appearance.

4. CONCLUSIONS

The work presented in this report has shown tunable infrared-laser imaging to bean extremely attractive method for on-line detection of hydrocarbon contaminants

and determination of their spatial distribution for efficient cleaning operations.Calibrated test panels of hydrocarbon contaminants on metallic substrates wereprepared and characterized with FTIR grazing-angle reflectance spectroscopy.Measurements were made over a range of film thicknesses and surface roughness,and the derived instrument sensitivity was quite robust with respect to the degreeof surface roughness and the orientation of the reflectance unit to the direction ofpolishing grooves.

Tunable infrared-laser images were acquired at both absorbing and non-absorbing frequencies for hydrocarbon contaminants on aluminum test panels.The thickness of the contaminant layers calculated from the laser images showedgood agreement with the measured film thickness determined by spatially aver-aged FTIR spectroscopic results. The laser images clearly reveal the heterogene-ous distribution of the contaminant species on the component surfaces for a vari-ety of film thicknesses and degree of surface roughness.

Primarily, the effects of laser-coherence noise determine the current detectionlimits of the laser-imaging method. The noise is introduced when an image ratiois formed from images taken at absorbing and non-absorbing wavelengths. For

typical hydrocarbon species, the detection limit appears to be on the order of 10-20 nm for film thickness. Improvements in the system despeckling and projectionoptics may substantially decrease this noise level with an attendant increase insensitivity.

The configuration of a future prototype imaging system instrument will bestrongly determined by system formats that employ either a pulsed or continuous-wave laser, and staring focal-plane array (FPA) cameras or raster-scanned imag-ers. The design of an imaging system will include a consideration of the ultimateinstrument cost. At the present time, it appears that a continuous-wave system

with a scanned imager offers the system with the lowest cost. However, the per-formance of some newly developed inexpensive infrared microbolometer arrayswill also be evaluated as a possible component of a low-cost pulsed imager. Fu-ture work will enlarge both the laser illumination area and image field of view inorder to develop a prototype instrument capable of rapid large-area surveys duringcleaning verification.


31/372

D. Ottesen et al.22

Acknowledgments

We gratefully acknowledge the financial support for these investigations by theDepartment of Defense through the Strategic Environmental Research and Devel-opment Program.

REFERENCES

1. T.A. Hoffard, C.A. Kodres and D.R. Polly, Technical Memorandum, NFESC-TM-2335-SHR

(2000).2. C.A. Kodres, D.R. Polly and T.A. Hoffard, Technical Report, NFESC-TR-2067-ENV (1997).*3. C.A. Kodres, D.R. Polly and T.A. Hoffard,Metal Finishing95, 48-53 (1997).

4. R.G. Greenler,J. Chem. Phys.44, 310-315 (1966).5. D.L. Allara, in: Characterization of Metal andPolymer Surfaces, L.H. Lee (Ed.), Vol. 2, pp.193-206, Academic Press, New York (1977).

6. W.G. Golden, in:Fourier Transform Infrared Spectroscopy-Applications to Chemical Systems,J.R. Ferraro and L.J. Basile (Eds.), Vol. 4, pp. 315-344, Academic Press, New York (1985).

7. D.K. Ottesen,J. Electrochem. Soc. 132, 2250-2257 (1985).8. D.K. Ottesen, L.R. Thorne and R.W. Bradshaw, Sandia Report, SAND86-8789 (1986).*9. R.W. Bradshaw, D.K. Ottesen, L.R. Thorne, A.L. Newman and L.N. Tallerico, Sandia Report,

SAND87-8241 (1987).*10. P.E. Powers, T.J. Kulp and S.E. Bisson, Optics Letters23, 159-169 (1998).

NFESC technical reports may be ordered from the web at www.dtic.mil. Reports from SandiaNational Laboratories may be ordered by contacting Sandia National Laboratories Technical Li-braries at (505) 845-8287 or the National Technical Information Service (NTIS) at www.ntis.gov.


32/372

Surface Contamination and Cleaning, Vol. 1, pp. 2341

Ed. K.L. Mittal

VSP 2003

Monitoring cleanliness and defining acceptable

cleanliness levels

MANTOSH K. CHAWLA

Photo Emission Tech., Inc., 3255 Grande Vista Drive, Newbury Park, CA 91320

AbstractDefining and maintaining a proper level of surface cleanliness is, at best, subjective.Often the failure of surface preparation processes is not discovered until problems, such as poor ad-hesion, occur down stream. Surface cleanliness is critical for good surface finish or success of sub-sequent operations that depend on surface cleanliness. To assure consistent quality of surfacecleanliness, it is important to: understand the types of contaminants that need to be monitored, mostcommon cleanliness monitoring methods and their strengths and limitations, factors to be consid-ered in choosing appropriate cleanliness monitoring method(s), and cost impact of various cleanli-ness levels.

The selection of a cleanliness monitoring method should take into account several factors, such

as the type of substrate and the types of contaminants to be monitored, etc.

In order to define Acceptable level of cleanliness, a total cost approach is needed. Total cost isdefined as the cost of cleaning added to the cost of non-conformance related to a particular level ofsurface cleanliness. An acceptable level of cleanliness is the one that minimizes or optimizes thistotal cost.

Keywords: Acceptable cleanliness levels; optimum cleanliness level; total cost of cleaning; cleanlinessmonitoring methods.

1. INTRODUCTION

Defining and maintaining the surface preparation at proper levels is the key togood surface finish. However defining a proper level of surface cleanliness is,at best, subjective. For consistent results, it is important to define how clean isclean. Often the inadequacy of surface preparation processes is not discovereduntil problems, such as poor adhesion, occur downstream resulting in non-conformance due to poor surface cleanliness. To assure consistent quality of sur-

face cleanliness, it is important to: understand the types of contaminants to be

monitored; most common cleanliness monitoring techniques and their strengthsand limitations; factors that affect the choice of cleanliness monitoring tech-nique(s); select an appropriate cleanliness monitoring method; specify a desirable

Phone: (805) 499-7667, Fax: (805) 499-6854, E-mail: [email protected]


33/372

M.K. Chawla24

level of surface cleanliness; and monitor the surface cleanliness to an establishedlevel on an on-going basis.

The selection of a cleanliness verification technique, as a minimum, should

take into account the type of substrate and the types of contaminants to be moni-tored, desired level of cleanliness, speed of measurement, operator skill level re-quired, and acquisition and operating costs. In addition, it is very important thatthe cleanliness monitoring technique be quantitative, non-destructive and readilyusable.

For every level of cleanliness, there is a corresponding level of product per-formance (i.e. failure / non-conformance rate). Each level of cleanliness has a cost

associated with achieving that level, just as there is a cost associated with the fail-ure / non-conformance rate corresponding to each level of cleanliness. These two

cost components can be combined to assess total cost of cleaning. A minimumtotal cost can only be achieved by balancing the cost of incremental cleaningwith the reduced cost of corresponding failure / non-conformance rate. The op-timum level of cleanliness is the one that minimizes the total cost. Since allprocesses have some variation, there is bound to be some variation in the level of

cleanliness achieved. An acceptable variation around the optimum level ofcleanliness, where the total cost is minimum, would define the Acceptablecleanliness level. Some suggested approaches to defining acceptable levels of

surface cleanliness are also discussed.

2. TYPES OF CONTAMINATION

A contamination is defined as any undesirable foreign matter that is present on a

surface. Contaminations can be classified into three different categories: 1) Par-ticulate, 2) Thin Film (Both Organic and Inorganic), and 3) Microbial or biologi-cal contamination.

(1) Particulate contaminationcan be defined as any foreign matter present on thesurface as a physical object. Some examples of particulate contaminants aredust, hair, micro-fragments and fibers.

(2) Thin film contamination, also called Molecular contamination, is present onthe surface in the form of a thin film covering the whole surface or some areas

of the surface. This type of contamination can be organic or inorganic. Someexamples of thin film contaminants are skin oil, grease, surfactant/chemicalresidues, oxides and other unwanted films.

(3) Microbial contaminationcan be present on the surface in the form of particlesor thin films or a combination of both and refers to generally unwanted livingorganisms present on the surface. Some examples of microbial contaminantsare spore, bacilli and organic cultures. This type of contamination generally

occurs from the environment or residues from processes.


34/372

Monitoring cleanliness and defining acceptable cleanliness levels 25

3. TYPES OF CLEANLINESS MONITORING METHODS

Cleanliness monitoring methods can also be generally classified into three differ-

ent categories: 1) Indirect Methods, 2) Direct Methods, and 3) Analytical Meth-ods. All of these methods have certain strengths and limitations, which will bediscussed later; hence, it is important to select the method that will be most ap-propriate for a particular application. Most of these methods are appropriate for

thin film or molecular contamination.

(1) Indirect methods Any technique that does not take a measurement on theactual surface or area of interest would be classified as an indirect method.See Table 1 for some of the most common indirect methods along with theirfeatures.

(2) Direct methods Any technique that takes a measurement directly from theactual surface or area of interest but does not directly identify the species ofcontamination present would be classified as a direct method. Some of the

most common direct methods along with their features are listed in Table 1.

(3) Analytical methods Any technique that identifies the species of, and meas-ures the amount of contamination would be classified as an analytical tech-nique. Analytical techniques can be direct or indirect; however all of themusually determine the amount of and the species of contamination. Some of

the most common analytical methods along with their features are listed inTable 2.

4. MOST COMMON VERIFICATION / MEASUREMENT METHODS

Some of the most common indirect, direct and analytical methods, with a briefdiscussion of their principles of operation, are presented below.

4.1. Indirect methods

4.1.1. Determination of non-volatile residue (NVR) [1]Also known as gravimetric measurement. This method requires a highly sensitivescale that can weigh parts to an accuracy of plus or minus one milligram, or bet-

ter. A container is weighed before collecting fluid that flushes the part of interest.After the collected fluid has evaporated, the container is weighed again. The dif-ference in the weight of the container before and after flushing and evaporation isthe weight of the contamination removed by flushing.

4.1.2. Ultraviolet (UV) spectroscopyIt involves the use of a spectrometer to analyze solvent extract from the parts ofinterest. Only contaminants that have an absorption wavelength in the UV region

can be detected and analyzed. Calibration curves, utilizing samples with knownconcentration of contamination, can be developed and used to determine actualamount of contamination.


35/372


36/372


37/372


38/372


39/372

M.K. Chawla30

4.1.3. Use of an optical particle counter (OPC)As the name implies, this method is used for detecting particulate contamination.Typically the part or surface of interest is flushed with some fluid. The fluid is

then analyzed using a particle counter. OPC gives both the count and size of par-ticles in the suspension measured.

4.2. Direct methods

4.2.1. Magnified visual inspectionIt is a step above visual inspection with the naked eye. Using some means of mag-nification, gross contamination that may not be visible to the naked eye can beobserved. Due to its nature it is only effective with smaller parts that can be han-

dled by an operator. The method also limits the surface area that can be checked.

4.2.2. Black lightUsing a black-light, i.e., UV light it is possible to visually detect gross level ofcontamination. For this technique to work, however, the contaminant of interestmust fluoresce under black light. This method is somewhat similar to magnified

visual inspection, except that since the contaminants fluoresce, if present, they areeasier to see. Typically the level of contamination that can be detected with this

method is too high for most precision cleaning applications. Experiments haveshown that a skilled operator can, at best, detect 1 mg/cm2[2].

4.2.3. Water break testThis technique utilizes the difference in surface tension of water and organic con-taminants to detect contamination. This test will detect the presence of hydropho-bic films on surfaces. When water is applied to the surface to be checked for con-tamination, water covers the areas of the surface that are clean. The presence oforganic contamination on the surface prevents water from forming a film over it.This test can be used for checking small parts as well as large surfaces. It is very

cost effective and will enable detection of molecular layers of hydrophobic or-ganic contaminants. The sensitivity of the test may be questionable for rough orporous surfaces.

4.2.4. Contact angleA drop of water resting on a solid surface forms a shape that is influenced by thesolid surface tension. The shape is influenced by presence of organic contami-nants on the surface. If a tangent is drawn from the droplet to the solid surface,

the angle formed is called Contact Angle. Contact angle measurements can be

used to detect organic films, coatings or contaminants on the surface. A con-taminated metal part would have a high contact angle, such as 90 or more. Someparts, such as plastics, have positive contact angles even when clean so themethod is not typically used for cleanliness analysis for these materials. While anumber is obtained from this test, the test is still non-quantitative in terms of thecontaminants on the part [3]. Because of its simplicity, contact angle measure-


40/372


ments have been broadly accepted for material surface analysis related to wetting,adhesion, and absorption.

4.2.5. Optically stimulated electron emission (OSEE) [4]A probe illuminates the surface to be tested with ultraviolet light of a particularwavelength. This illumination stimulates the emission of electrons from the metal

surface. The emitted electrons are collected and measured as currentby the in-strument. Contamination reduces the electron emission and, therefore, the currentmeasured. The equipment may be connected to a computerized scanning systemthat can scan a flat or cylindrical surface for cleanliness. The results can be pre-sented as a color map or 3-D map. The user can define the level of cleanlinesseach color represents in the graphic presentation of the results. This feature makes

it easy to compare before and after effect of a cleaning process or side-by-side comparison of two pieces cleaned in alternative cleaners. OSEE is simple tooperate, fast, and relatively inexpensive. In addition, it is quantitative, non-destructive, and non-contact. This technique detects both organic and inorganiccontamination, such as oxides, and can be used on any shape of parts as long asthe geometry of the part is presented to the sensor in a consistent manner. Thissystem lends itself to scan small parts or large surface areas very quickly. Thistest can be used in the production line as well as for on-line real time measure-ment of surface cleanliness. The surface of interest must emit electrons for the

technique to work. Nearly all materials of engineering importance emit electronswhen exposed to UV light.

4.2.6. MESERAN surface analyzer (measurement and evaluation of surfaces byevaporative rate analysis) [5]

A measurement begins by depositing onto the test surface a small volume of testsolution. A thin- end-window Geiger Mller detector is positioned above thedroplet and a metered flow of gaseous nitrogen is passed between the detector andthe test surface. To sense the volatile compound, organic compounds are used in

which one or more of the carbon atoms are Carbon-14. The -particles given offby the C-14 molecules at the surface are counted. Specifically measurements aremade of how many molecules there are, how many are evaporating away, howfast they are evaporating away and, how many remain retained on the surface.Measuring molecules provides a high degree of sensitivity and the opportunity toanalyze surfaces on a molecular scale with observations and results available inonly a few minutes. The choice of volatile chemical compounds determines

whether they react with the surface material, evaporate, or are retained by thevarious physical/chemical molecular forces acting at the surface.

Chemical compounds can be found which tend to both volatilize (evaporate)and yet tend to be retained by the surface upon which they are placed. The bal-ance of these tendencies determines just how long the volatile compound remainson the surface, or just how much remains. In fact, it is possible to choose a com-pound that reacts with specific properties of the surface, or a compound where the

evaporation and/or retention are affected by certain characteristics of the surface


41/372

M.K. Chawla32

material. By using only a monolayer equivalent of the radiochemical, the ob-served rate of evaporation becomes a function of the residual concentration of thenon-evaporated molecules of radiochemical compound.

4.2.7. Total organic carbon (TOC) analysis [6]This method uses oxygen gas in a combustion chamber at a set temperature to

combust carbon-based contaminants into carbon dioxide which is then detectedby CO2 coulometer. Coulometer detection uses electricity to electrochemicallymeasure the weight of carbon combusted in the combustion chamber. The methodis very sensitive and can detect as little as one microgram of carbon. The TOCmethod works on a variety of materials and is surface-geometry independent. Themethod works only on small parts or pieces of larger parts. Due to the high tem-

perature in the combustion chamber (more than 400C) the method is not suitableto parts sensitive to high temperature. In addition, the TOC method detects onlycarbon-based contaminants, although this is generally not an issue since the ma-

jority of contaminants encountered in a manufacturing environment are carbonbased. The TOC method can be used in a laboratory but is adaptable to productionenvironment. It is a technique that works by oxidizing the sample to convert thecarbon into carbon dioxide, and detecting and measuring carbon dioxide. The de-tection of carbon implies that there was some contamination that had carbon as itsconstituent. The level of TOC detected determines the level of cleanliness of a

part. Since a TOC Analyzer detects only carbon, the compound of interest mustcontain some carbon in a detectable quantity, in order for the analysis to be car-ried out.

4.3. Analytical methods

Any technique that identifies the species of, and measures the amount of contami-nation would be classified as an analytical technique. Analytical techniques canbe direct or indirect; however all of them usually determine the amount of and the

species of contamination. All of the analytical techniques involve Probing thesurface, near-surface region, or interior of a material with electrons, ions, or pho-tons produced radiation that has been altered depending on the number, energy, ortype of particles emitted. Changes can also occur in the frequency or absorbanceof the radiation transmitted through or reflected from the material. Each type ofanalytical instrument looks at these emissions in a different way to provide infor-mation about certain aspects of the sample, such as structure, composition, or

chemistry, and electronic or optical properties [9]. Most of the analytical tech-niques test the specimen in vacuum, are expensive and require high skill level to

operate and interpret the results. Testing takes time and rarely provides real-timeinformation. Because of the cost of analytical testing, it is recommended that itsuse be limited to applications where identification of the species of contaminationis required to enhance or improve the process.

Analytical techniques can be divided into two groups; 1) Chemical/elementalsurface analysis, and 2) bulk analysis techniques. There are many techniques that


42/372


are capable of performing these analyses, some of the most common analyticaltechniques are summarized below. For a more complete list of most common ana-lytical techniques, visit www.cea.com/table/htm, website of Charles Evans & As-

sociates. For a more comprehensive list of analytical techniques visit the websiteof ESCA users group in England www.ukesca.org/tech/list/html.

4.3.1. Chemical/elemental surface analysis techniques4.3.1.1. Auger electron spectroscopy (AES)/scanning Auger microscopy (SAM)[79]They are used to obtain elemental composition information (and some chemicalinformation) from the top two to five atomic layers of a material; identify thecomposition of very small features and particulates on surfaces; and provide depth

composition profiles of thin films, metals, and alloys. Micro-beam AES is alsoused to study grain boundaries in high temperature alloys, and to examine fracturesurfaces to determine composition and extent of damage. The Auger electrons,named after the discoverer of the process, are produced (among other emissions)with discrete energies, which are specific to each element, when the surface is ir-radiated by a finely focused electron beam. Auger electrons are collected andmeasured. Auger electrons have discrete kinetic energies that are characteristic ofthe emitting atoms, making this technique particularly useful for identifying ele-mental composition. The energy level of Auger electrons is specific to a species

of contamination. The escape depth of Auger electrons (15 nm) makes this tech-nique very surface sensitive.

4.3.1.2. Electron spectroscopy for chemical analysis (ESCA) [79]Also known as X-ray Photoelectron Spectroscopy, or XPS, is a surface analysistechnique that provides information on both elemental identity and chemicalbonding. This information can be used to identify functional groups and molecu-lar types. This method uses special equipment to bombard the surface of interestwith X-rays under vacuum conditions, causing electrons to be ejected from the

surface. The actual elemental composition can be quantified by measuring the en-ergy level of ejected electrons, since each element ejects electrons at a unique en-ergy. Its application is limited to mostly research and development, but it can beused to calibrate and evaluate other, less sophisticated measurement methods.

4.3.1.3. Secondary ion mass spectrometry (SIMS static) [79]A surface analysis technique used for identifying molecules on a surface, as well

as for depth profiling for tracking very low concentrations of contaminants or ion-implanted species. SIMS technique includes static SIMS (SSIMS), dynamic

SIMS, and time-of flight SIMS (TOF SIMS). SSIMS can identify organic and in-organic species. TOF SIMS is an ultra-precise and accurate technique for measur-ing the mass of molecules in the near-surface layers of material. A pulsed primaryion beam is used to sputter material from the surface of the sample. Secondaryions are collected and focused into a reflection time-of-flight (TOF) mass spec-trometer, where they are mass analyzed. Analysis involves measuring the length


43/372

M.K. Chawla34

of time it takes the secondary ions to reach the detector. The lighter the ion, theless time it takes to reach the detector. From the arrival time the masses of thespecies can be identified. High sensitivity depth profiling is a key feature.

4.3.1.4. Secondary ion mass spectrometry (SIMS dynamic) [79]

It uses a much higher intensity bombarding beam than Static SIMS, and is a par-

ticularly sensitive (less than part-per-billion level) method for depth profiling ofdopants and trace elements in semiconductors. It can also map the X-Y distribu-tion of atomic species with sub-micrometer spatial resolution. An energetic pri-mary ion beam is used to sputter atoms from the sample surface. Secondary ionsemitted are mass analyzed. It is inherently a profiling technique. It uses O2or Csions to bombard a surface in high vacuum. High sensitivity depth profiling is a

key feature.4.3.1.5. Variable-angle spectroscopic ellipsometry (VASE) [7, 8]It is a noninvasive technique that offers information about surface composition,layer thickness, and optical properties. Its applications include examining opticalsurfaces and crystals, and measuring and analyzing band gaps in semiconductors,optical devices, thin films, and carbon coatings on computer hard disks.

4.3.1.6. Energy dispersive X-ray (EDX) and wavelength dispersive X-ray (WDX)analyses [7, 8]

They are often combined with a scanning electron microscope or electron micro-probe. EDX provides simultaneous multi-element analysis and elemental mappingcapabilities for a region up to a few micrometers deep. WDX analyzes traceamounts of one element at a time and is more quantitative than EDX. An exampleof EDX application is identifying silicon nitride and titanium carbide inclusions instainless steel.

4.3.2. Bulk analysis techniquesThe following are several analytical techniques that typically are used for chemi-

cal or elemental analysis of bulk materials, but these can also be adapted for thecharacterization of surfaces and thin films. Many times these techniques are usedin industry for characterizing surfaces, sometimes without full knowledge of thestrengths and limitations of these techniques. It is hoped that information abouthow these techniques work, their strengths and limitations would help the readerin determining their usefulness and limitations for their applications.

4.3.2.1. Fourier transform infrared (FTIR) spectroscopy [7, 8]It provides information about the chemical bonding and molecular structure of or-

ganics and some inorganic solids, liquids, gases and films. This technique is espe-cially good for identifying unknowns when reference IR spectra are available.When an infrared beam impinges on a surface, the molecular constituents vibratein the infrared regime. The identities, surrounding environments, and concentra-tions of these oscillating chemical bonds can be determined. FTIR is a powerfulanalytical tool for characterizing and identifying organic molecules. The IR spec-trum of an organic compound serves as its fingerprint and provides information


44/372


about chemical bonding and molecular structure. This information can be used todetect the types of organic materials present on the surface.

4.3.2.2. Raman spectroscopy (RS) [7, 8]It is used to examine the energy levels of molecules that cannot be well character-ized via infrared spectroscopy. The two techniques, however, are complimentary.

In the RS, a sample is irradiated with a strong monochromatic light source (usu-ally a laser). Most of the radiation will scatter or reflect off the sample at thesame energy as the incoming laser radiation. However, a small amount will scat-ter from the sample at a wavelength slightly shifted from the original wavelength.It is possible to study the molecular structure or determine the chemical identityof the sample. It is quite straightforward to identify compounds by spectral library

search. Due to extensive library spectral information, the unique spectral finger-print of every compound, and the ease with which such analyses can be per-formed, the RS is a very useful technique for various applications. An importantapplication of the RS is the rapid, nondestructive characterization of diamond,diamond-like, and amorphous-carbon films.

4.3.2.3. Scanning electron microscopy (SEM) /energy dispersive X-ray analysis(EDX) [7, 8]TheSEM produces detailed photographs that provide important information about

the surface structure and morphology of almost any kind of sample. Image analy-sis is often the first and most important step in problem solving and failure analy-sis. With SEM, a focused beam of high-energy electrons is scanned over the sur-face of a material, causing a variety of signals, secondary electrons, X-rays,photons, etc. each of which may be used to characterize the material with re-spect to specific properties. The signals are used to modulate the brightness on aCRT display, thereby providing a high-resolution map of the selected materialproperty. It is a surface imaging technique, but with Energy Dispersive X-ray(EDX) it can identify elements in the near-surface region. This technique is most

useful for imaging particles.

4.3.2.4. X-ray fluorescence (XRF) [7, 8]Incident X-rays are used to excite surface atoms. The atoms relax through theemission of an X-ray with energy characteristic of the parent atoms and the inten-sity proportional to the amount of the element present. It is a bulk or total mate-rials characterization technique for rapid, simultaneous, and nondestructive

analysis of elements having an atomic number higher than that of boron. Tradi-tional bulk analysis applications include identifying metals and alloys, detecting

trace elements in liquids, and identifying residues and deposits.4.3.2.5. Total-reflection X-ray fluorescence (TXRF) [7, 8]It is a special XRF technique that provides extremely sensitive measures of theelements present in a materials outer surface. Applications include searching formetal contamination in thin films on silicon wafers and detecting picogram-levelsof arsenic, lead, mercury and cadmium on hazardous, chemical fume hoods.


45/372

M.K. Chawla36

5. CONSIDERATIONS FOR SELECTING A CLEANLINESS MONITORING

METHOD [10]

There are several factors that should be considered in selecting a method formonitoring surface cleanliness. The factors discussed here are the ones that aremost important but by no means represent a complete list of factors that should beconsidered. There may be other factors that are pertinent to a particular applica-tion that should be considered.

(1) Type of contaminant One of the first factors that should be considered in se-

lecting a cleanliness monitoring method is the type of contaminant that needto be monitored. Is the contaminant particulate or thin film type? If thin filmcontamination, is it organic or inorganic or both? Does the technique under

consideration monitor the type of contaminants that need to be monitored?

(2) Types of substrates What type of substrate is going to be monitored? Arethe techniques under consideration capable of monitoring this type of sub-strates? Are the techniques likely to damage the substrate to be monitored?

(3) Level of cleanliness to be monitored It is important that the level of contami-

nation that is expected or tolerable can be monitored by the technique underconsideration. It is recommended that samples with different levels of contami-nation be monitored with the technique(s) under consideration. In evaluating

the technique for suitability, prepared samples should have levels of contamina-tion spanning a range from 0% (i.e. clean surfaces) to maybe 200% of the ex-pected level of contamination on the surface. The technique(s) should not haveany problem in distinguishing between different levels of contamination.

(4) Features of monitoring method It is important to consider various featuresof the method under consideration. For example, is the technique non-contactand/or non-destructive? Does the technique require deposit of some mediumon the surface? For example, the contact angle measurement requires that a

droplet of water be placed on the surface of interest. How large an area canthe technique measure? Is it sensitive to surface roughness? Can the techniquecheck parts of different geometries? Can the technique be used on-line? Is thetechnique suitable for the environment it is going to be used in? Does the

technique cause any permanent changes to the surface? All of these questionsshould be considered to determine the most appropriate monitoring techniquefor a particular application.

(5) Measurement speed Is the measurement speed critical for the applicationunder consideration? If so, how fast can the technique make a measurement?

Is the speed sufficient to keep up with the production flow?

(6) Acquisition and operating cost How does the acquisition cost compare

among the techniques that meet other requirements for the application? Arethere any expendable items that would have to be purchased for continued useof the equipment? How much does that add to the operating cost? What arethe maintenance and calibration requirements and how much these require-


46/372


ments will add to the operating cost? All these questions should be answeredto truly compare the total cost of any cleanliness monitoring system.

(7) Skill level required The operator skill level can be a key factor in the use of

some techniques, particularly the analytical techniques. Some techniques mayinvolve interpretation of the data to determine the quality of surface cleanliness.

These factors should also be considered in the selection of a cleanliness measur-ing technique. A high operator skill level will result in higher operating cost. Inthe event of personnel turnover, higher training costs may also be incurred.

6. COST OF CLEANLING [10]

For every level of cleanliness, there is a cost to achieve that level of cleanliness.There is corresponding level of failure/non-conformance for each cleanlinesslevel, hence cost of failures/non-conformance. Total Cost of achieving a certainlevel of cleanliness is the sum of these two costs.

As the achieved level of surface cleanliness increases, the cost of cleaning alsoincreases. Eventually the incremental cost of cleaning rises exponentially. Hence

the cost of surface cleaning is directly proportional to the surface cleanliness level.Intuitively, we know that the higher the cleanliness level the lower the fail-

ure/non-conformance rate, hence cost, due to surface cleanliness. The incrementaldrop in costs due to lower failure/non-conformance also exhibits exponential rela-tionship. Hence the cost of failures/non-conformance is inversely proportional tothe surface cleanliness level. If both of these costs were plotted on a graph, thetypical result would be like the one shown in Figure 1.

Figure 1.Total cost vs. cleanliness level.


47/372

M.K. Chawla38

An optimum level of cleanliness is the one that minimizes the total cost. Even-tually one can arrive at a cleanliness level where the savings in the failure/non-conformance costs will not be offset by incremental cost of achieving cleanliness

beyond the optimum level. A small range around the optimu

Documents

182205352-Surface-Contamination-and-Cleaning-pdf.pdf