Machine Learning Magnetic Properties of Van der Waals Heterostructures

PI Trevor David Rhone, Rensselaer Polytechnic Institute
Co-PI Efthimios Kaxiras, Harvard University
Rhone-ADSP2020

Twisted bilayer graphene with twist angle 2.5 degrees. The bilayer structure has a single Li intercalant near the AA region of the Moiré pattern. The carbon atoms of the upper (lower) layer are shown in grey (brown), and the Li atom is green. Credit: Trevor David Rhone

The discovery of two-dimensional ferromagnetic materials in 2017 ushered in a new era of studies of magnetic order. Using a data-driven approach, this project combines machine learning and high-throughput density functional theory calculations to study van der Waals materials and predict their magnetic and thermodynamic properties. This non-traditional approach facilitates the rapid identification of new functional materials that will have broad impacts for science and industry.

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