Publications

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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.