13 citations · 13 across the 2 of their papers we have counts for
3 papers
Validation Workflow for Machine Learning Interatomic Potentials for Complex Ceramics
Kimia Ghaffari, Salil Bavdekar, Douglas E. Spearot +1
The number of published Machine Learning Interatomic Potentials (MLIPs) has increased significantly in recent years. These new data-driven potential energy approximations often lac…
A Genetic Algorithm Trained Machine-Learned Interatomic Potential for the Silicon-Carbon System
Michael MacIsaac, Salil Bavdekar, Douglas Spearot +1
A linear regression-based machine learned interatomic potential (MLIP) was developed for the silicon-carbon system. The MLIP was predominantly trained on structures discovered thro…
Fluid-mediated impact of soft solids
Jacopo Bilotto, John Martin Kolinski, Brice Lecampion +3
A viscous, lubrication-like response can be triggered in a thin film of fluid squeezed between a rigid and flat surface and the tip of an incoming projectile. We develop a comprehe…