3 papers
cond-mat.mtrl-sci2026
Multi-Fidelity Predictive Model for Shock Response of Energetic Materials Using Conditional U-Net
Brian H. Lee, Chunyu Li, Aidan Pantoya +3
Mapping microstructure to properties is central to materials science. Perhaps most famously, the Hall-Petch relationship relates average grain size to strength. More challenging ha…
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…