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.
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.