Diffusion Model for Generating Inorganic Materials with Targeted Density of States
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Chakraborty, Chandreyi
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Abstract
Our latest machine learning model revolutionizes materials design by conditionally generating atomic structures based on Density of States. Unlike prior models that produced random structures, ours ensures both feasibility and alignment with specific energy spectra for more control on electronic properties. This conditional generation bridges the gap between theoretical modeling and real-world applications, paving the way for tailored material innovations.
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Undergraduate Research Option Thesis