2 papers
cond-mat.mtrl-sci2025
Machine learning-driven elasticity prediction in advanced inorganic materials via convolutional neural networks
Yujie Liu, Zhenyu Wang, Hang Lei +6
Inorganic crystal materials have broad application potential due to excellent physical and chemical properties, with elastic properties (shear modulus, bulk modulus) crucial for pr…
cond-mat.mtrl-sci2025
ProME: An Integrated Computational Platform for Material Properties at Extremes and Its Application in Multicomponent Alloy Design
Xingyu Gao, William Yi Wang, Xin Chen +8
We have built an integrated computational platform for material properties at extreme conditions, ProME (Professional Materials at Extremes) v1.0, which enables integrated calculat…