36 citations · 83 across the 10 of their papers we have counts for
3 papers · 1 filter
A Recipe for Charge Density Prediction
Xiang Fu, Andrew Rosen, Kyle Bystrom +5
In density functional theory, charge density is the core attribute of atomic systems from which all chemical properties can be derived. Machine learning methods are promising in si…
Addressing the Band Gap Problem with a Machine-Learned Exchange Functional
Kyle Bystrom, Stefano Falletta, Boris Kozinsky
The systematic underestimation of band gaps is one of the most fundamental challenges in semilocal density functional theory (DFT). In addition to hindering the application of DFT…
Transferability and Accuracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic Potentials
Zachary A. H. Goodwin, Malia B. Wenny, Julia H. Yang +11
Ionic liquids (ILs) are an exciting class of electrolytes finding applications in many areas from energy storage to solvents, where they have been touted as ``designer solvents'' a…