Neural Network-Driven Atomistic Simulations for Predicting Chiroptical Properties in Ligand Induced Chiral Semiconductor Nanocrystals
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Eran Rabani of the University of California, Berkeley, is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop advanced computational models that predict the optical properties of chiral semiconductor nanocrystals. These materials, which are essential components in…
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