3 papers
physics.comp-ph2020
Materials Graph Transformer predicts the outcomes of inorganic reactions with reliable uncertainties
Shreshth A. Malik, Rhys E. A. Goodall, Alpha A. Lee
A common bottleneck for materials discovery is synthesis. While recent methodological advances have resulted in major improvements in the ability to predicatively design novel mate…
cond-mat.soft2020
Machine learnt approximations to the bridge function yield improved closures for the Ornstein-Zernike equation
Rhys E. A. Goodall, Alpha A. Lee
A key challenge for soft materials design and coarse-graining simulations is determining interaction potentials between components that give rise to desired condensed-phase structu…
physics.comp-ph2019
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry
Rhys E. A. Goodall, Alpha A. Lee
Machine learning has the potential to accelerate materials discovery by accurately predicting materials properties at a low computational cost. However, the model inputs remain a k…