Publications

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The biocompatibility and possible toxicological consequences of engineered nanomaterials, including quantum dots (QDs) due to their unique suitability for biomedical applications, remain intense areas of interest. We utilized advanced imaging approaches to characterize the interactions of CdSe QDs of various sizes and shapes with live immune cells. Particle diffusion and partitioning within the plasma membrane, cellular uptake kinetics, and sorting of particles into lysosomes were all independantly characterized. Using high-speed total internal reflectance fluorescence (TIRF) microscopy, we show that QDs with an average aspect ratio of 2.0 (i.e., rod-shaped) diffuse nearly an order of magnitude slower in the plasma membrane than more spherical particles with aspect ratios of 1.2 and 1.6, respectively. Moreover, more rod-shaped QDs were shown to be internalized into the cell 2-3 fold more slowly. Hyperspectral confocal fluorescence microscopy demonstrates that QDs tend to partition within the cell membrane into regions containing a single particle type. Furthermore, data examining QD sorting mechanisms indicate that endocytosis and lysosomal sorting increases with particle size. Together, these observations suggest that both size and aspect ratio of a nanoparticle are important characteristics that significantly impact interactions with the plasma membrane, uptake into the cell, and localization within intracellular vesicles. Thus, rather than simply characterizing nanoparticle uptake into cells, we show that utilization of advanced imaging approaches permits a more nuanced and complete examination of the multiple aspects of cell-nanoparticle interactions that can ultimately aid understanding possible mechanisms of toxicity, resulting in safer nanomaterial designs. Using hyperspectral confocal fluorescence (HCF) microscopy, it is shown that quantum dots of various sizes and shapes partition themselves into distinct regions within the cell membrane of RBL-2H3 rat mast cells. HCF microscopy allows for deconvolving the signal from multiple, overlapping fluorophores in the sample in order to reveal precise concentrations and distributions of nanoparticles in the cell. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Subsurface containment of CO2 is predicated on effective caprock sealing. Many previous studies have relied on macroscopic measurements of capillary breakthrough pressure and other petrophysical properties without direct examination of solid phases that line pore networks and directly contact fluids. However, pore-lining phases strongly contribute to sealing behavior through interfacial interactions among CO2, brine, and the mineral or non-mineral phases. Our high resolution (i.e., sub-micron) examination of the composition of pore-lining phases of several continental and marine mudstones indicates that sealing efficiency (i.e., breakthrough pressure) is governed by pore shapes and pore-lining phases that are not identifiable except through direct characterization of pores. Bulk X-ray diffraction data does not indicate which phases line the pores and may be especially lacking for mudstones with organic material. Organics can line pores and may represent once-mobile phases that modify the wettability of an originally clay-lined pore network. For shallow formations (i.e., < {approx}800 m depth), interfacial tension and contact angles result in breakthrough pressures that may be as high as those needed to fracture the rock - thus, in the absence of fractures, capillary sealing efficiency is indicated. Deeper seals have poorer capillary sealing if mica-like wetting dominates the wettability. We thank the U.S. Department of Energy's National Energy Technology Laboratory and the Office of Basic Energy Sciences, and the Southeast and Southwest Carbon Sequestration Partnerships for supporting this work.

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Metallic materials in sliding contact typically undergo dislocation-mediated plasticity, which results in stick-slip frictional behavior associated with high coefficients of friction ({mu} > 0.8). Our recent work on two electroplated nanocrystalline Ni alloys reveal that under combined conditions of low stress and low sliding velocity, these metals have very low friction ({mu} < 0.3). The observed frictional behavior is consistent with the transition from dislocation-mediated plasticity to an alternative mechanism such as grain boundary sliding. Focused ion beam cross-sections viewed in the TEM reveal the formation of a subsurface tribological bilayer at the contact surface, where the parent nanocrystalline material has evolved in structure to accommodate the frictional contact. Grain growth at a critical distance below the contact surface appears to promote a shear-accomodation layer. We will discuss these results in the context of a grain-size dependent transition from conventional microcrystalline wear behavior to this unusual wear behavior in nanocrystalline FCC metals.

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We will present a study of the structure-property relations in Reststrahlen materials that possess a band of negative permittivities in the infrared. It will be shown that sub-micron defects strongly affect the optical response, resulting in significantly diminished permittivities. This work has implications on the use of ionic materials in IR-metamaterials.

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that vary as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.

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Subsurface containment of CO2 is predicated on effective caprock sealing. Many previous studies have relied on macroscopic measurements of capillary breakthrough pressure and other petrophysical properties without direct examination of solid phases that line pore networks and directly contact fluids. However, pore-lining phases strongly contribute to sealing behavior through interfacial interactions among CO2, brine, and the mineral or non-mineral phases. Our high resolution (i.e., sub-micron) examination of the composition of pore-lining phases of several continental and marine mudstones indicates that sealing efficiency (i.e., breakthrough pressure) is governed by pore shapes and pore-lining phases that are not identifiable except through direct characterization of pores. Bulk X-ray diffraction data does not indicate which phases line the pores and may be especially lacking for mudstones with organic material. Organics can line pores and may represent once-mobile phases that modify the wettability of an originally clay-lined pore network. For shallow formations (i.e., < {approx}800 m depth), interfacial tension and contact angles result in breakthrough pressures that may be as high as those needed to fracture the rock - thus, in the absence of fractures, capillary sealing efficiency is indicated. Deeper seals have poorer capillary sealing if mica-like wetting dominates the wettability.

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The role of crystal coherence length on the infrared optical response of MgO thin films was investigated with regard to Reststrahlen band photon-phonon coupling. Preferentially (001)-oriented sputtered and evaporated ion-beam assisted deposited thin films were prepared on silicon and annealed to vary film microstructure. Film crystalline coherence was characterized by x-ray diffraction line broadening and transmission electron microscopy. The infrared dielectric response revealed a strong dependence of dielectric resonance magnitude on crystalline coherence. Shifts to lower transverse optical phonon frequencies were observed with increased crystalline coherence. Increased optical phonon damping is attributed to increasing granularity and intergrain misorientation.

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In ductile metals, sliding contact is often accompanied by severe plastic deformation localized to a small volume of material adjacent to the wear surface. During the initial run-in period, hardness, grain structure and crystallographic texture of the surfaces that come into sliding contact undergo significant changes, culminating in the evolution of subsurface layers with their own characteristic features. Here, a brief overview of our ongoing research on the fundamental phenomena governing the friction-induced recrystallization in single crystal metals, and how these recrystallized structures with nanometer-size grains would in turn influence metallic friction will be presented. We have employed a novel combination of experimental tools (FIB, EBSD and TEM) and an analysis of the critical resolved shear stress (RSS) on the twelve slip systems of the FCC lattice to understand the evolution of these friction-induced structures in single crystal nickel. The later part of the talk deals with the mechanisms of friction in nanocrystalline Ni films. Analyses of friction-induced subsurfaces seem to confirm that the formation of stable ultrafine nanocrystalline layers with 2-10 nm grains changes the deformation mechanism from the traditional dislocation mediated one to that is predominantly controlled by grain boundaries, resulting in significant reductions in the coefficient friction.

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2-Chloroethyl phenyl sulfide (CEPS), a surrogate compound of the chemical warfare agent sulfur mustard, was examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a novel method of producing multiway data using a stepped thermal desorption. Various multivariate analysis schemes were employed to analyze the data. These methods may be able to discern different sources of CEPS. In addition, CEPS was applied to cotton, nylon, polyester, and silk swatches. These swatches were placed in controlled humidity chambers maintained at 23%, 56%, and 85% relative humidity. At regular intervals, samples were removed from each test swatch, and the samples analyzed using TD/GC-MS. The results were compared across fabric substrate and humidity.

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The major focus of this study was to examine the feasibility of applying diamond-like nanocomposite (DLN) coatings on the sidewalls of Ni alloy parts fabricated using lithographie, galvanoformung and abformung (LIGA: a German acronym that means lithography, electroforming, and molding) for friction and wear control. Planar test coupons were employed to understand the friction mechanisms in regimes relevant to LIGA microsytems. Friction tests were conducted on planar test coupons as well as between LIGA-fabricated test structures in planar-sidewall and sidewall-sidewall configurations. Measurements were made in dry nitrogen and air with 50% relative humidity by enclosing the friction tester in an environmental chamber. In contrast to bare metal-metal contacts, minimal wear was exhibited for the DLN-coated LIGA NiMn alloy parts and test coupons. The low friction behavior of DLN was attributed to its ability to transfer to the rubbing counterface providing low interfacial shear at the sliding contact. The coating coverage and chemistry on the sidewalls and the substrate-coating interface integrity were examined by transmission electron microscopy, Automated eXpert Spectral Image Analysis, and electron backscatter diffraction on cross sections prepared by focused ion beam microscopy. The role of novel characterization techniques to evaluate the surface coatings for LIGA microsystems technology is highlighted. © 2009 IEEE.

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Erbium is used as a storage medium for tritium. Microstructural study of helium bubble generation from tritium decay in erbium tritide can provide an unusual example of bubble development with negligible radiation damage. Aged erbium tritide film specimens were found to contain five distinctly different microstructural features. The general structure was of large columnar grains of ErT2. But on a fine scale, precipitates believed to be erbium oxy-tritides and helium bubbles could be identified. The precipitate size was in the range of ∼10 nm and the bubbles were of an unusual planar shape on {111} planes with an invariant thickness of ∼1 nm and a diameter on the order of 10 nm. Also, an outer layer containing no fine precipitate structure and only a few helium bubbles were present on the films. This layer is best described as a denuded zone which probably grew during aging in air. Finally, large embedded Er2O3 particles were found at low density and nonuniformly distributed, but sometimes extending through the thickness of the film. A failure mechanism allowing the helium to escape is suggested by observed cracking between bubbles closer to end of life. Copyright © 2007 by ASTM International.

Er(D,T){sub 2-x} {sup 3}He{sub x}, erbium di-tritide, films of thicknesses 500 nm, 400 nm, 300 nm, 200 nm, and 100 nm were grown and analyzed by Transmission Electron Microscopy, X-Ray Diffraction, and Ion Beam Analysis to determine variations in film microstructure as a function of film thickness and age, due to the time-dependent build-up of {sup 3}He in the film from the radioactive decay of tritium. Several interesting features were observed: One, the amount of helium released as a function of film thickness is relatively constant. This suggests that the helium is being released only from the near surface region and that the helium is not diffusing to the surface from the bulk of the film. Two, lenticular helium bubbles are observed as a result of the radioactive decay of tritium into {sup 3}He. These bubbles grow along the [111] crystallographic direction. Three, a helium bubble free zone, or 'denuded zone' is observed near the surface. The size of this region is independent of film thickness. Four, an analysis of secondary diffraction spots in the Transmission Electron Microscopy study indicate that small erbium oxide precipitates, 5-10 nm in size, exist throughout the film. Further, all of the films had large erbium oxide inclusions, in many cases these inclusions span the depth of the film.

Three-spatial-dimension (3D) time-of-flight-secondary ion mass spectrometry (TOF-SIMS) analysis can be performed if an X-Y image is saved at each depth of a depth profile. In this paper, we will show how images reconstructed from specified depths, depth profiles generated from specific X-Y coordinates, as well as three-spatial-dimensional rendering provide for a better understanding of the sample than traditional depth profiling where only a single spectrum is collected at each depth. We will also demonstrate, for the first time, that multivariate statistical analysis (MVSA) tools can be used to perform a rapid, unbiased analysis of the entire 3D data set. In the example shown here, retrospective analysis and MVSA revealed a more complete picture of the 3D chemical distribution of the sample than did the as-measured depth profiling alone. Color overlays of the MVSA components as well as animated movies allowing for visualization (in 3D) from various angles will be provided. © 2007 American Chemical Society.

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Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media.

Spectrum imaging combined with multivariate statistics is an approach to microanalysis that makes the maximum use of the large amount of data potentially collected in forensics analysis. Here, this study examines the efficacy of using spectrum imaging-enabled microscopies to identify chemical signatures in simulated bioagent materials. This approach allowed for the ready discrimination between all samples in the test. In particular, the spectrum imaging approach allowed for the identification of particles with trace elements that would have been missed with a more traditional approach to forensic microanalysis. Finally, the importance of combining signals from multiple length scales and analytical sensitivities is discussed.

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Automated, nonbiased, multivariate statistical analysis techniques are useful for converting very large amounts of data into a smaller, more manageable number of chemical components (spectra and images) that are needed to describe the measurement. We report the first use of the multivariate spectral analysis program AXSIA (Automated eXpert Spectral Image Analysis) developed at Sandia National Laboratories to quantitatively analyze micro-PIXE data maps. AXSIA implements a multivariate curve resolution technique that reduces the spectral image data sets into a limited number of physically realizable and easily interpretable components (including both spectra and images). We show that the principal component spectra can be further analyzed using conventional PIXE programs to convert the weighting images into quantitative concentration maps. A common elemental data set has been analyzed using three different PIXE analysis codes and the results compared to the cases when each of these codes is used to separately analyze the associated AXSIA principal component spectral data. We find that these comparisons are in good quantitative agreement with each other. © 2006 Elsevier B.V. All rights reserved.

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HfB{sub 2} and ZrB{sub 2} are of interest for thermal protection materials because of favorable thermal stability, mechanical properties, and oxidation resistance. We have made dense diboride ceramics with 2 to 20 % SiC by hot pressing at 2000 C and 5000 psi. High-resolution transmission electron microscopy (TEM) shows very thin grain boundary phases that suggest liquid phase sintering. Fracture toughness measurements give RT values of 4 to 6 MPam{sup 1/2}. Four-pt flexure strengths measured in air up to 1450 C were as high as 450-500 MPa. Thermal diffusivities were measured to 2000 C for ZrB{sub 2} and HfB{sub 2} ceramics with SiC contents from 2 to 20%. Thermal conductivities were calculated from thermal diffusivities and measured heat capacities. Thermal diffusivities were modeled using different two-phase composite models. These materials exhibit excellent high temperature properties and are attractive for further development for thermal protection systems.

High-purity AlPt thin films prepared by self-propagating, high temperature combustion synthesis show evidence for a new rhombohedral phase. Sputter deposited Al/Pt multilayers of various designs are reacted at different rates in air and in vacuum, and each form a new trigonal/hexagonal aluminide phase with unit cell parameters a = 15.571(8) {angstrom}, c = 5.304(1) {angstrom}, space group R-3 (148), and Z, the number of formula units within a unit cell, = 39. The lattice is isostructural to that of the AlPd R-3 lattice as reported by Matkovic and Schubert (Matkovic, 1977). Reacted films have a random in-plane crystallographic texture, a modest out-of-plane (001) texture, and equiaxed grains with dimensions on the order of film thickness.

The ability to integrate metal and semiconductor micro-systems to perform highly complex functions, such as RF-MEMS, will depend on developing freestanding metal structures that offer improved conductivity, reflectivity, and mechanical properties. Three issues have prevented the proliferation of these systems: (1) warpage of active components due to through-thickness stress gradients, (2) limited component lifetimes due to fatigue, and (3) low yield strength. To address these issues, we focus on developing and implementing techniques to enable the direct study of the stress and microstructural evolution during electrodeposition and mechanical loading. The study of stress during electrodeposition of metal thin films is being accomplished by integrating a multi-beam optical stress sensor into an electrodeposition chamber. By coupling the in-situ stress information with ex-situ microstructural analysis, a scientific understanding of the sources of stress during electrodeposition will be obtained. These results are providing a foundation upon which to develop a stress-gradient-free thin film directly applicable to the production of freestanding metal structures. The issues of fatigue and yield strength are being addressed by developing novel surface micromachined tensile and bend testers, by interferometry, and by TEM analysis. The MEMS tensile tester has a ''Bosch'' etched hole to allow for direct viewing of the microstructure in a TEM before, during, and after loading. This approach allows for the quantitative measurements of stress-strain relations while imaging dislocation motion, and determination of fracture nucleation in samples with well-known fatigue/strain histories. This technique facilitates the determination of the limits for classical deformation mechanisms and helps to formulate a new understanding of the mechanical response as the grain sizes are refined to a nanometer scale. Together, these studies will result in a science-based infrastructure to enhance the production of integrated metal--semiconductor systems and will directly impact RF MEMS and LIGA technologies at Sandia.

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Electron backscattered diffraction (EBSD) is a widely used technique for both identifying the crystallographic phase and for mapping the orientation of crystalline materials on the micron length scale. Often the operating conditions necessary for phase identification are not suitable for orientation mapping and vice versa. In an effort to optimize the speed involved in the mapping technique, pattern quality is sacrificed and the wealth of information present in an EBSD pattern is compressed to basically 4 values: a matched phase and three Euler angles. However, ab initio identification of phases from EBSD patterns requires high quality patterns and fairly intense computation. Spectrum imaging is an analytical approach that may offer some solutions to the aforementioned problems. Spectrum imaging consists of collecting a whole spectrum at each pixel in a mapping style measurement. This large set of data is then analyzed using multivariate statistical analysis (MSA) techniques such as principle components analysis, multivariate curve resolution, or other least squares based techniques. The result of these calculations is a set of component spectral shapes with corresponding abundances that allow the analyst to extract the greatest amount of physically relevant information from an otherwise enormous data set. Spectrum imaging has been used successfully in EDX microanalysis (both in the SEM and TEM), TOF-SIMS, WDS, and EELS. To examine the potential benefits of the spectrum imaging approach for EBSD data, a series of basic experiments and calculations were run. Test data sets (20 x 20 patterns in .jpeg format) on polycrystalline Al and on the directionally solidified eutectic oxide, CoO/ZrO{sub 2}(CaO), were collected using the HKL Channel 5 system with a Nordlys detector under normal mapping conditions. The data was collected on a FEI dual beam FIB (model DB235) and a Zeiss (Supra 55 VP) SEM at 20keV for Al and CoO/ZrO{sub 2}(CaO), respectively. The data sets were analyzed according to the schematic shown in Figure 1. Each EBSD pattern was hough transformed, unzipped into a 1-D vector of channels with intensities ranging from 0-255, and then added to an overall data matrix. A range of treatments (edge/no edge detection, spatial simplicity/spectral simplicity, etc.) were examined to determine the optimal way of treating the data. The multivariate analyses were performed using the AXSIA code developed at Sandia National Laboratories. The MSA techniques were able to correctly identify individual grains in the Al sample and individual phases in the CoO/ZrO{sub 2}(CaO) sample. For each component EBSD pattern identified from the Al data, a corresponding color map of abundance can be seen which clearly corresponds to a single grain (Figure 2). The success in the CoO/ZrO{sub 2}(CaO) sample is particularly notable due to both phases sharing the Fm-3m space group which would confuse most autoindexing routines. The range of analytical treatments identified two extremes in results: a minimal number of components (patterns) with only kikuchi line positions present or a larger number of components with full intensity information present. The further application of these results to phase mapping will be discussed.

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Time-of-flight secondary ion mass spectrometry (TOF-SIMS) instruments are capable of saving an entire mass spectrum at each pixel of an image, allowing for retrospective analysis of masses that were not selected for analysis during data collection. These TOF-SIMS spectral images contain a wealth of information, but few tools are available to assist the analyst in visualizing the entire raw data set and as a result, most of the data are not analyzed. Automated, nonbiased, multivariate statistical analysis (MVSA) techniques are useful for converting the massive amount of data into a smaller number of chemical components (spectra and images) that are needed to fully describe the TOF-SIMS measurement. Many samples require two back-to-back TOF-SIMS measurements in order to fully characterize the sample, one measurement of the fraction of positively charged secondary ions (positive ion fraction) and one measurement of the fraction of negatively charged secondary ions (negative ion fraction). Each measurement then needs to be individually evaluated. In this paper, we report the first MVSA analysis of a concatenated TOF-SIMS date set comprising positive ion and negative ion spectral images collected on the same region of a sample. MVSA of concatenated data sets provides results that are intuitive and fully describe the sample. The analytical insight provided by MVSA of the concatenated data set was not obtained when either polarity data set was analyzed separately. © 2005 American Chemical Society.

Boron sub-arsenide, B{sub 12}As{sub 2}, is based on twelve-atom clusters of boron atoms and two-atom As-As chains. By contrast, SiC is a tetrahedrally bonded covalent semiconductor. Despite these fundamental differences, the basal plane hexagonal lattice constant of boron sub-arsenide is twice that of SiC. This coincidence suggests the possibility of heteroepitaxial growth of boron sub-arsenide films on properly aligned SiC. However, there are a variety of incommensurate alignments by which heteroepitaxial growth of B{sub 12}As{sub 2} on (0001) 6H-SiC can occur. In this study, we first used geometrical crystallographic considerations to describe the possible arrangements of B{sub 12}As{sub 2} on (0001) 6H-SiC. We identified four translational and two rotational variants. We then analyzed electron backscattered diffraction and transmission electron microscopy images for evidence of distinct domains of such structural variants. Micron-scale regions with each of the two possible rotational alignments of B{sub 12}As{sub 2} icosahedra with the SiC surface were seen. On a finer length scale (100-300 nm) within these regions, boron-rich boundaries were found, consistent with those between pairs of the four equivalent translational variants associated with a two-to-one lattice match. Boron-carbide reaction layers were also observed at interfaces between SiC and B{sub 12}As{sub 2}.

Metallic Phases in extraterrestrial materials are composed of Fe-Ni with minor amounts of Co, P, Si, Cr, etc. Electron microscopy techniques (SEM, TEM, EPMA, AEM) have been used for almost 50 years to study micron and submicron microscopic features in the metal phases (Fig. 1) such as clear taenite, cloudy zone, plessite, etc [1,2]. However lack of instrumentation to prepare TEM thin foils in specific sample locations and to obtain micro-scale crystallographic data have limited these investigations. New techniques such as the focused ion beam (FIB) and the electron backscatter electron diffraction (EBSD) techniques have overcome these limitations. The application of the FIB instrument has allowed us to prepare {approx}10 um long by {approx} 5um deep TEM thin sections of metal phases from specific regions of metal particles, in chondrites, irons and stony iron meteorites, identified by optical and SEM observation. Using a FEI dual beam FIB we were able to study very small metal particles in samples of CH chondrites [3] and zoneless plessite (ZP) in ordinary chondrites. Fig. 2 shows a SEM photomicrograph of a {approx}40 um ZP particle in Kernouve, a H6 chondrite. Fig. 3a,b shows a TEM photograph of a section of the FIB prepared TEM foil of the ZP particle and a Ni trace through a tetrataenite/kamacite region of the particle. It has been proposed that the Widmanstatten pattern in low P iron meteorites forms by martensite decomposition, via the reaction {gamma} {yields} {alpha}{sub 2} + {gamma} {yields} {alpha} + {gamma} in which {alpha}{sub 2}, martensite, decomposes to the equilibrium {alpha} and {gamma} phases during the cooling process [4]. In order to show if this mechanism for Widmanstatten pattern formation is correct, crystallographic information is needed from the {gamma} or taenite phases throughout a given meteorite. The EBSD technique was employed in this study to obtain the orientation of the taenite surrounding the initial martensite phase and the kamacite which forms as {alpha}{sub 2} or as Widmanstatten plates in a series of IVB irons. Fig. 4a,b shows EBSD orientation maps of taenite and kamacite from the Tawallah Valley IVB iron. We observe that the orientation of the taenite in the IVB meteorites is the same throughout the sample consistent with the orientation of the high temperature single phase taenite before formation of the Widmanstatten pattern.

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Spectral imaging where a complete spectrum is collected from each of a series of spatial locations (1D lines, 2D images or 3D volumes) is now available on a wide range of analytical tools - from electron and x-ray to ion beam instruments. With this capability to collect extremely large spectral images comes the need for automated data analysis tools that can rapidly and without bias reduce a large number of raw spectra to a compact, chemically relevant, and easily interpreted representation. It is clear that manual interrogation of individual spectra is impractical even for very small spectral images (< 5000 spectra). More typical spectral images can contain tens of thousands to millions of spectra, which given the constraint of acquisition time may contain between 5 and 300 counts per 1000-channel spectrum. Conventional manual approaches to spectral image analysis such as summing spectra from regions or constructing x-ray maps are prone to bias and possibly error. One way to comprehensively analyze spectral image data, which has been automated, is to utilize an unsupervised self-modeling multivariate statistical analysis method such as multivariate curve resolution (MCR). This approach has proven capable of solving a wide range of analytical problems based upon the counting of x-rays (SEM/STEM-EDX, XRF, PIXE), electrons (EELS, XPS) and ions (TOF-SIMS). As an example of the MCR approach, a STEM x-ray spectral image from a ZrB2-SiC composite was acquired and analyzed. The data were generated in a FEI Tecnai F30-ST TEM/STEM operated at 300kV, equipped with an EDAX SUTW x-ray detector. The spectral image was acquired with the TIA software on the STEM at 128 by 128 pixels (12nm/pixel) for 100msec dwell per pixel (total acquisition time was 30 minutes) with a probe of approximately the same size as each pixel. Each spectrum in the image had, on average, 500 counts. The calculation took 5 seconds on a PC workstation with dual 2.4GHz PentiumIV Xeon processors and 2Gbytes of RAM and resulted in four chemically relevant components, which are shown in Figure 1. The analysis region was at a triple junction of three ZrB2 grains that contained zirconium oxide, aluminum oxide and a glass phase. The power of unbiased statistical methods, such as MCR as applied here, is that no a priori knowledge of the material's chemistry is required. The algorithms, in this case, effectively reduced over 16,000 2000-channel spectra (64Mbytes) to four images and four spectral shapes (72kbytes), which in this case represent chemical phases. This three order of magnitude compression is achieved rapidly with no loss of chemical information. There is also the potential to correlate multiple analytical techniques like, for example, EELS and EDS in the STEM adding sensitivity to light elements as well as bonding information for EELS to the more comprehensive spectral coverage of EDS.

Microanalysis is typically performed to analyze the near surface of materials. There are many instances where chemical information about the third spatial dimension is essential to the solution of materials analyses. The majority of 3D analyses however focus on limited spectral acquisition and/or analysis. For truly comprehensive 3D chemical characterization, 4D spectral images (a complete spectrum from each volume element of a region of a specimen) are needed. Furthermore, a robust statistical method is needed to extract the maximum amount of chemical information from that extremely large amount of data. In this paper, an example of the acquisition and multivariate statistical analysis of 4D (3-spatial and 1-spectral dimension) x-ray spectral images is described. The method of utilizing a single- or dual-beam FIB (w/o or w/SEM) to get at 3D chemistry has been described by others with respect to secondary-ion mass spectrometry. The basic methodology described in those works has been modified for comprehensive x-ray microanalysis in a dual-beam FIB/SEM (FEI Co. DB-235). In brief, the FIB is used to serially section a site-specific region of a sample and then the electron beam is rastered over the exposed surfaces with x-ray spectral images being acquired at each section. All this is performed without rotating or tilting the specimen between FIB cutting and SEM imaging/x-ray spectral image acquisition. The resultant 4D spectral image is then unfolded (number of volume elements by number of channels) and subjected to the same multivariate curve resolution (MCR) approach that has proven successful for the analysis of lower-dimension x-ray spectral images. The TSI data sets can be in excess of 4Gbytes. This problem has been overcome (for now) and images up to 6Gbytes have been analyzed in this work. The method for analyzing such large spectral images will be described in this presentation. A comprehensive 3D chemical analysis was performed on several corrosion specimens of Cu electroplated with various metals. Figure 1A shows the top view of the localized corrosion region prepared for FIB sectioning. The TSI region has been coated with Pt and a trench has been milled along the bottom edge of the region, exposing it to the electron beam as seen in Figure 1B. The TSI consisted of 25 sections and was approximately 6Gbytes. Figure 1C shows several of the components rendered in 3D: Green is Cu; blue is Pb; cyan represents one of the corrosion products that contains Cu, Zn, O, S, and C; and orange represents the other corrosion product with Zn, O, S and C. Figure 1 D shows all of the component spectral shapes from the analysis. There is severe pathological overlap of the spectra from Ni, Cu and Zn as well as Pb and S. in spite of this clean spectral shapes have been extracted from the TSI. This powerful TSI technique could be applied to other sectioning methods well.

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Sandia and Rontec have developed an annular, 12-element, 60 mm{sup 2}, Peltier-cooled, translatable, silicon drift detector called the SDD-12. The body of the SDD-12 is only 22.8 mm in total thickness and easily fits between the sample and the upstream wall of the Sandia microbeam chamber. At a working distance of 1 mm, the solid angle is 1.09 sr. The energy resolution is 170 eV at count rates <40 kcps and 200 eV for rates of 1 Mcps. X-ray count rates must be maintained below 50 kcps when protons are allowed to strike the full area of the SDD. Another innovation with this new {mu}PIXE system is that the data are analyzed using Sandia's Automated eXpert Spectral Image Analysis (AXSIA).

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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.