R. Bruce van Dover

A wavelet transform algorithm for peak detection and application to powder x-ray diffraction data

Peak detection is ubiquitous in the analysis of spectral data. While many noise-filtering algorithms and peak identification algorithms have been developed, recent work [P. Du, W. Kibbe, and S. Lin, Bioinformatics 22, 2059 (2006); A. Wee, D. Grayden, Y. Zhu, K. Petkovic-Duran, and D. Smith, Electrophoresis 29, 4215 (2008)] has demonstrated that both of these tasks are efficiently performed through analysis of the wavelet transform of the data. In this paper, we present a wavelet-based peak detection algorithm with user-defined parameters that can be readily applied to the application of any spectral data. Particular attention is given to the algorithms resolution of overlapping peaks. The algorithm is implemented for the analysis of powder diffraction data, and successful detection of Bragg peaks is demonstrated for both low signal-to-noise data from theta-theta diffraction of nanoparticles and combinatorial x-ray diffraction data from a composition spread thin film. These datasets have different types of background signals which are effectively removed in the wavelet-based method, and the results demonstrate that the algorithm provides a robust method for automated peak detection.

High mobility single crystalline ScN and single-orientation epitaxial YN on sapphire via magnetron sputtering

The mechanical, chemical, and electronic properties of the lanthanoid nitrides give this class of materials many potential applications. While ScN research activity has sharply increased recently, investigations of growth methods for optimizing structural and, more importantly, electronic properties are still needed. YN has received some theoretical but very little experimental attention. We present results of x-ray diffraction and atomic force microscopy analyses of film structure as well as Hall effect measurements of electronic properties for sputter-deposited ScN and YN. Films are deposited at select values of sputter gas stoichiometry, gas pressure, and substrate temperature, and optimal values are suggested. Additionally, the role of deposition geometry is investigated. Grown under optimal conditions, ScN films are single crystalline and YN films are singly oriented with both nitrides exhibiting the same epitaxial relation to α-Al2O3(11¯02) substrates. Our films also exhibit the highest documented e...

High energy x-ray diffraction/x-ray fluorescence spectroscopy for high-throughput analysis of composition spread thin films

High-throughput crystallography is an important tool in materials research, particularly for the rapid assessment of structure-property relationships. We present a technique for simultaneous acquisition of diffraction images and fluorescence spectra on a continuous composition spread thin film using a 60 keV x-ray source. Subsequent noninteractive data processing provides maps of the diffraction profiles, thin film fiber texture, and composition. Even for highly textured films, our diffraction technique provides detection of diffraction from each family of Bragg reflections, which affords direct comparison of the measured profiles with powder patterns of known phases. These techniques are important for high throughput combinatorial studies as they provide structure and composition maps which may be correlated with performance trends within an inorganic library.

Constraint reasoning and Kernel clustering for pattern decomposition with scaling

Motivated by an important and challenging task encountered in material discovery, we consider the problem of finding K basis patterns of numbers that jointly compose N observed patterns while enforcing additional spatial and scaling constraints. We propose a Constraint Programming (CP) model which captures the exact problem structure yet fails to scale in the presence of noisy data about the patterns. We alleviate this issue by employing Machine Learning (ML) techniques, namely kernel methods and clustering, to decompose the problem into smaller ones based on a global data-driven view, and then stitch the partial solutions together using a global CP model. Combining the complementary strengths of CP and ML techniques yields a more accurate and scalable method than the few found in the literature for this complex problem.

SMT-aided combinatorial materials discovery

In combinatorial materials discovery, one searches for new materials with desirable properties by obtaining measurements on hundreds of samples in a single high-throughput batch experiment. As manual data analysis is becoming more and more impractical, there is a growing need to develop new techniques to automatically analyze and interpret such data. We describe a novel approach to the phase map identification problem where we integrate domain-specific scientific background knowledge about the physical and chemical properties of the materials into an SMT reasoning framework. We evaluate the performance of our method on realistic synthetic measurements, and we show that it provides accurate and physically meaningful interpretations of the data, even in the presence of artificially added noise.

High-throughput combinatorial study of local stress in thin film composition spreads

We investigate the stresses in thin films with sub-millimeter lateral spatial resolution using a dense array of prefabricated cantilever beams prepared by microelectromechanical-system techniques. Stress induced deflection of the cantilever is interrogated by an optical (laser/position sensitive detector) measurement system. Composition spread films are deposited on the cantilever array using a three gun on-axis magnetron cosputtering system. The position dependent composition is inferred using rate calibrations and verified by electron microprobe/energy dispersive spectroscopy. We demonstrate the function of this system using an Fe-Ni-Al composition spread with approximately 1 at. % resolution. This approach allows for measurement of the composition dependence of other electromechanical properties such as the martensitic phase transition temperature of traditional and ferromagnetic shape-memory alloys, as well as the properties of hydrogen storage materials and the magnetic response of magnetostrictive materials.

Cosputtered composition-spread reproducibility established by high-throughput x-ray fluorescence

We describe the characterization of sputtered yttria-zirconia composition spread thin films by x-ray fluorescence (XRF). We also discuss our automated analysis of the XRF data, which was collected in a high throughput experiment at the Cornell High Energy Synchrotron Source. The results indicate that both the composition reproducibility of the library deposition and the composition measurements have a precision of better than 1 atomic percent.