Abstract
Material design and optimization of properties of known compounds strongly depends on understanding the structural parameters and atomic arrangements of the underlying crystal structures and their interfaces. In this work, we propose a novel approach to characterize the morphology and orientation of polycrystalline and complex micro-structured material systems. Based on a lattice reduction algorithm, we are able to discover the fundamental lattice type, orientation, and boundaries of each polycrystalline region. Our algorithm identifies the Bravais lattice types of all crystalline regions in any given sample, within certain size limits. Our method can be applied to characterize materials with ideal crystals, structures with imperfections and amorphous fractions, and material interfaces with complex grain morphologies. We foresee applications of our methodology, based on computational crystallography, to areas of materials design research in nanoscale transistors and other functional devices, where crystallography and morphology from both experiments and simulations need to be characterized.
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Acknowledgements
We would like to acknowledge the Institute for Pure and Applied Mathematics for hosting us during the RIPS 2013 program, the Intel Corporation, and the NSF for funding (Grant no. 0931852). We would also like to thank Michael Haverty from Intel (currently in Applied Materials) and Dr. Vladimir Bochenkov from Moscow State University for providing materials with complex micro-structures.
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Toomey, B., Han, X., Dan Dong, C., Edward, V., Kaminski, J.W., Shankar, S. (2021). Characterization of Phases and Orientations of Micro-structured Materials Using Computational Crystallography. In: Shankar, S., Muller, R., Dunning, T., Chen, G.H. (eds) Computational Materials, Chemistry, and Biochemistry: From Bold Initiatives to the Last Mile. Springer Series in Materials Science, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-030-18778-1_11
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DOI: https://doi.org/10.1007/978-3-030-18778-1_11
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