CSENG Mathematics, School of
College of Science & Engineering
Twin Cities
College of Science & Engineering
Twin Cities
Project Title:
Deep Neural Networks to Predict Electronic Properties of Bilayer Materials
This project focuses on using deep neural networks to predict electronic properties of bilayer material. Specifically, the researchers are trying to develop a formalism to use deep neural networks to approximate a twist operator for local density of state of untwisted bilayer material. As a good indicator for the appearance of flat band, the local density of state for twisted bilayer material enables people to explore the existence of flat band without knowing atomistic parameters which are derived from expensive density functional theory computation.
Project Investigators
Drake Clark
Michael Hott
Tianyu Kong
Diyi Liu
Professor Mitchell Luskin
Matthias Maier
Alexander Watson
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