1 citations · 1 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2026
Melt-Quench Failures and Practical Solutions for Universal Machine-Learning Interatomic Potentials in Amorphous Structure Generation
Shuwei Li, Yuqi An, Xingyu Guo +2
Generating experimentally relevant amorphous structures via melt-quench molecular dynamics is prohibitively expensive at the first-principles level. Universal machine-learning inte…
cond-mat.mtrl-sci2025★ 1 cited
Machine Learning Reveals Composition Dependent Thermal Stability in Halide Perovskites
Abigail R. Hering, Mansha Dubey, Elahe Hosseini +5
Halide perovskites exhibit unpredictable properties in response to environmental stressors, due to several composition-dependent degradation mechanisms. In this work, we apply data…