2 papers
cond-mat.mtrl-sci2026
Equivariant graph neural network surrogates for predicting the properties of relaxed atomic configurations
Jamie Holber, Siddhartha Srivastava, Krishna Garikipati
Density functional theory (DFT) calculations determine the relaxed atomic positions and lattice parameters that minimize the formation energy of a structure. We present an equivari…
physics.comp-ph2025
Physics- and data-driven Active Learning of neural network representations for free energy functions of materials from statistical mechanics
Jamie Holber, Krishna Garikipati
Accurate free energy representations are crucial for understanding phase dynamics in materials. We employ a scale-bridging approach to incorporate atomistic information into our fr…