Density Functional Theory (DFT) is the standard algorithm for many electronic structure calculations.  Like many methods, DFT sacrifices some scalability for accuracy.  This makes DFT levels of accuracy difficult to achieve for large systems like those in multilayer 2D heterostructures.  We have obtained DFT accuracy by training atomic cluster expansions (ACE) on multilayer graphene.

About the speaker: Drake Clark is a fourth-year Ph.D. student in Mathematics at the University of Minnesota. His research focuses on computational methods for simulating layered 2D materials such as twisted bilayer graphene and stacked TMDs.