Publications

Analytical instrumentation such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides a tremendous quantity of data since an entire mass spectrum is saved at each pixel in an ion image. The analyst often selects only a few species for detailed analysis; the majority of the data are not utilized. Researchers at Sandia National Laboratory (SNL) have developed a powerful multivariate statistical analysis (MVSA) toolkit named AXSIA (Automated eXpert Spectrum Image Analysis) that looks for trends in complete datasets (e.g., analyzes the entire mass spectrum at each pixel). A unique feature of the AXSIA toolkit is the generation of intuitive results (e.g., negative peaks are not allowed in the spectral response). The robust statistical process is able to unambiguously identify all of the spectral features uniquely associated with each distinct component throughout the dataset. General Electric and Sandia used AXSIA to analyze raw data files generated on an Ion Tof IV ToF-SIMS instrument. Here, we will show that the MVSA toolkit identified metallic contaminants within a defect in a polymer sample. These metallic contaminants were not identifiable using standard data analysis protocol. © 2004 Elsevier B.V. All rights reserved.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is capable of generating huge volumes of data. TOF-SIMS spectrum-images, comprising complete mass spectra at each point in a spatial array, are easily acquired with modern instrumentation. With the addition of depth profiling, spectra can be collected from up to three spatial dimensions leading to data sets that are seemingly unlimited in size. Multivariate statistical techniques such as principal component analysis, multivariate curve resolution and other factor analysis methods are being used to meet the challenge of turning that mountain of data into analytically useful knowledge. These methods work by extracting the essential chemical information embedded in the high dimensional data into a limited number of factors that describe the spectrally active pure components present in the sample. A review of the recent literature shows that the mass spectral data are often scaled prior to multivariate analysis. Common preprocessing steps include normalization of the pixel intensities, and auto- or variance-scaling of the mass spectra. In this paper, we will demonstrate that these pretreatments can lead to less than satisfactory results and, in fact, can be counterproductive. By taking the Poisson nature of the data into consideration, however, a scaling method can be devised that is optimal in a maximum likelihood sense. Using a simple and intuitive example, we will demonstrate the superiority of the optimal scaling approach for estimating the number of pure components, for segregating the chemical information into as few components as possible, and for discriminating small features from noise. © 2004 Elsevier B.V. All rights reserved.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) by its parallel nature, generates complex and very large datasets quickly and easily. An example of such a large dataset is a spectral image where a complete spectrum is collected for each pixel. Unfortunately, the large size of the data matrix involved makes it difficult to extract the chemical information from the data using traditional techniques. Because time constraints prevent an analysis of every peak, prior knowledge is used to select the most probable and significant peaks for evaluation. However, this approach may lead to a misinterpretation of the system under analysis. Ideally, the complete spectral image would be used to provide a comprehensive, unbiased materials characterization based on full spectral signatures. Automated eXpert spectral image analysis (AXSIA) software developed at Sandia National Laboratories implements a multivariate curve resolution technique that was originally developed for energy dispersive X-ray spectroscopy (EDS) [Microsci. Microanal. 9 (2003) 1]. This paper will demonstrate the application of the method to TOF-SIMS. AXSIA distills complex and very large spectral image datasets into a limited number of physically realizable and easily interpretable chemical components, including both spectra and concentrations. The number of components derived during the analysis represents the minimum number of components needed to completely describe the chemical information in the original dataset. Since full spectral signatures are used to determine each component, an enhanced signal-to-noise is realized. The efficient statistical aggregation of chemical information enables small and unexpected features to be automatically found without user intervention. © 2004 Elsevier B.V. All rights reserved.

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Nanometer scale morphological changes in the passive oxide on aluminum have been tracked as a function of polarization in an aqueous, moderate chloride electrolyte. Nanoscale void formation has been detected and characterized in the passive oxide on both single crystal Al and nanocrystalline Al thin films. Void nucleation occurs at the metal/oxide interface and growth proceeds into the oxide. This void formation process correlates with the faradaic charge density produced due to Al oxidation indicating that the voids result from point defect saturation at the Al/oxide interface. The shape factors for the voids are inconsistent with two leading pit initiation models where stable pitting is argued to result from disruption of the remnant oxide over a void or void-like structures. Several experimental observations and measurements suggest this predominant structural feature is not sufficient alone in determining the stability of the passive oxide toward stable pitting. An experiment is proposed and conducted to clearly establish causality between voids and stable pitting, however, the results are inclusive.

Stress evolution during deposition of amorphous Si and Ge thin films is remarkably similar to that observed for polycrystalline films. Amorphous semiconductors were used as model materials to study the origins of deposition stresses in continuous films, where suppression of both strain relaxation and epitaxial strain inheritance provides considerable simplification. Our data show that bulk compression is established by surface stress, while a subsequent return to tensile stress arises from elastic coalescence processes occurring on the kinetically roughened surface. © 2003 The American Physical Society.

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Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue.

The purpose of the report is to summarize discussions from a Ceramic/Metal Brazing: From Fundamentals to Applications Workshop that was held at Sandia National Laboratories in Albuquerque, NM on April 4, 2001. Brazing experts and users who bridge common areas of research, design, and manufacturing participated in the exercise. External perspectives on the general state of the science and technology for ceramics and metal brazing were given. Other discussions highlighted and critiqued Sandia's brazing research and engineering programs, including the latest advances in braze modeling and materials characterization. The workshop concluded with a facilitated dialogue that identified critical brazing research needs and opportunities.

This document summarizes research of reactively deposited metal hydride thin films and their properties. Reactive deposition processes are of interest, because desired stoichiometric phases are created in a one-step process. In general, this allows for better control of film stress compared with two-step processes that react hydrogen with pre-deposited metal films. Films grown by reactive methods potentially have improved mechanical integrity, performance and aging characteristics. The two reactive deposition techniques described in this report are reactive sputter deposition and reactive deposition involving electron-beam evaporation. Erbium hydride thin films are the main focus of this work. ErH{sub x} films are grown by ion beam sputtering erbium in the presence of hydrogen. Substrates include a Al{sub 2}O{sub 3} {l_brace}0001{r_brace}, a Al{sub 2}O{sub 3} {l_brace}1120{r_brace}, Si{l_brace}001{r_brace} having a native oxide, and polycrystalline molybdenum substrates. Scandium dideuteride films are also studied. ScD{sub x} is grown by evaporating scandium in the presence of molecular deuterium. Substrates used for scandium deuteride growth include single crystal sapphire and molybdenum-alumina cermet. Ultra-high vacuum methods are employed in all experiments to ensure the growth of high purity films, because both erbium and scandium have a strong affinity for oxygen. Film microstructure, phase, composition and stress are evaluated using a number of thin film and surface analytical techniques. In particular, we present evidence for a new erbium hydride phase, cubic erbium trihydride. This phase develops in films having a large in-plane compressive stress independent of substrate material. Erbium hydride thin films form with a strong <111> out-of-plane texture on all substrate materials. A moderate in-plane texture is also found; this crystallographic alignment forms as a result of the substrate/target geometry and not epitaxy. Multi-beam optical sensors (MOSS) are used for in-situ analysis of erbium hydride and scandium hydride film stress. These instruments probe the evolution of film stress during all stages of deposition and cooldown. Erbium hydride thin film stress is investigated for different growth conditions including temperature and sputter gas, and properties such as thermal expansion coefficient are measured. The in-situ stress measurement technique is further developed to make it suitable for manufacturing systems. New features added to this technique include the ability to monitor multiple substrates during a single deposition and a rapidly switched, tiltable mirror that accounts for small differences in sample alignment on a platen.

Real-time measurements of stress evolution during the deposition of Volmer-Weber thin films reveal a complex interplay between mechanisms for stress generation and stress relaxation. We observed a generic stress evolution from compressive to tensile, then back to compressive stress as the film thickened, in amorphous and polycrystalline Ge and Si, as well as in polycrystalline Ag, Al, and Ti. Direct measurements of stress relaxation during growth interrupts demonstrate that the generic behavior occurs even in the absence of stress relaxation. When relaxation did occur, the mechanism depended sensitively on whether the film was continuous or discontinuous, on the process conditions, and on the film/substrate interfacial strength. For Ag films, interfacial shear dominated the early relaxation behavior, whereas this mechanism was negligible in Al films due to the much stronger bonding at the Al/SiO2 interface. For amorphous Ge, selective relaxation of tensile stress was observed only at elevated temperatures, consistent with surface-diffusion-based mechanisms. In all the films studied here, stress relaxation was suppressed after the films became continuous. © 2001 American Institute of Physics.

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Failure analysis (FA) tools have been applied to analyze tungsten coated polysilicon microengines. These devices were stressed under accelerated conditions at ambient temperatures and pressure. Preliminary results illustrating the failure modes of microengines operated under variable humidity and ultra-high drive frequency will also be shown. Analysis of tungsten coated microengines revealed the absence of wear debris in microengines operated under ambient conditions. Plan view imaging of these microengines using scanning electron microscopy (SEM) revealed no accumulation of wear debris on the surface of the gears or ground plane on microengines operated under standard laboratory conditions. Friction bearing surfaces were exposed and analyzed using the focused ion beam (FIB). These cross sections revealed no accumulation of debris along friction bearing surfaces. By using transmission electron microscopy (TEM) in conjunction with electron energy loss spectroscopy (EELS), we were able to identify the thickness, elemental analysis, and crystallographic properties of tungsten coated MEMS devices. Atomic force microscopy was also utilized to analyze the surface roughness of friction bearing surfaces.

Energy dispersive x-ray (EDX) spectrum imaging has been performed in a scanning electron microscope (SEM) on a metal/ceramic braze to characterize the elemental distribution near the interface. Statistical methods were utilized to extract the relevant information (i.e., chemical phases and their distributions) from the spectrum image data set in a robust and unbiased way. The raw spectrum image was over 15 Mbytes (7500 spectra) while the statistical analysis resulted in five spectra and five images which describe the phases resolved above the noise level and their distribution in the microstructure.