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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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sensing, to improve worker/operator safety. This project will focus on using density functional theory calculations and ab initio molecular dynamics simulations. The project is a collaboration with Dr
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for the new green steels compositions, including impurities and tramp elements. These models should enable density-functional-theory (DFT) accurate large scale atomistic simulations of defects including
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effects in magnets, this project will develop Density Functional Theory methodology for multicomponent lanthanide materials. We will study, for example, how application of pressure causes the f-electrons in