3 papers
cond-mat.stat-mech2024
Thermodynamic Fidelity of Generative Models for Ising System
Brian H. Lee, Kat Nykiel, Ava E. Hallberg +2
Machine learning has become a central technique for modeling in science and engineering, either complementing or as surrogates to physics-based models. Significant efforts have rec…
cond-mat.mtrl-sci2024
Accelerating active learning materials discovery with FAIR data and workflows: a case study for alloy melting temperatures
Mohnish Harwani, Juan C. Verduzco, Brian H. Lee +1
Active learning (AL) is a powerful sequential optimization approach that has shown great promise in the discovery of new materials. However, a major challenge remains the acquisiti…
cond-mat.mes-hall2024
Graph neural network coarse-grain force field for the molecular crystal RDX
Brian H. Lee, James P. Larentzos, John K. Brennan +1
Condense phase molecular systems organize in wide range of distinct molecular configurations, including amorphous melt and glass as well as crystals often exhibiting polymorphism,…