7 citations · 8 across the 3 of their papers we have counts for
5 papers
Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations
Dylan Bayerl, Christopher M. Andolina, Shyam Dwaraknath +1
Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional…
A representation-independent electronic charge density database for crystalline materials
Jimmy-Xuan Shen, Jason M. Munro, Matthew K. Horton +3
In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge…
Selectivity in yttrium manganese oxide synthesis via local chemical potentials in hyperdimensional phase space
Paul K. Todd, Matthew J. McDermott, Christopher L. Rom +6
In sharp contrast to molecular synthesis, materials synthesis is generally presumed to lack selectivity. The few known methods of designing selectivity in solid-state reactions hav…
OPTIMADE, an API for exchanging materials data
Casper W. Andersen, Rickard Armiento, Evgeny Blokhin +53
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible an…
Pawpyseed: Perturbation-extrapolation band shifting corrections for point defect calculations
Kyle Bystrom, Danny Broberg, Shyam Dwaraknath +2
Significant progress has been made recently in the automation and standardization of ab initio point defect calculations. However, the task of developing, implementing, and benchma…