Materials Intelligence Research
The Materials Intelligence Research (MIR) group at Harvard University develops and uses computational methods combining quantum physics & chemistry and statistical mechanics with machine learning to understand and design complex materials.
Our goal is to create efficient algorithms and accurate atomistic models to be able to describe systems of surfaces, liquids, solids, and molecules for applications in energy storage and conversion.
Deep equivariant neural networks, Bayesian force fields, active learning, exascale reactive MD
Solid-state, ionic liquid, polymer electrolytes, correlated transport