4 papers
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…
A Multi-Level Monte Carlo Tree Search Method for Configuration Generation in Crystalline Systems
Xiaoxu Li, Ge Xu, Huajie Chen +2
In this paper, we study the construction of structural models for the description of substitutional defects in crystalline materials. Predicting and designing the atomic structures…
Extend the random-walk shielding-potential viscosity model to hot temperature regime
Yuqing Cheng, Xingyu Gao, Qiong Li +3
The transport properties of matter have been widely investigated. In particular, shear viscosity over a wide parameter space is crucial for various applications, such as designing…
Projected gradient descent algorithm for crystal structure relaxation under a fixed unit cell volume
Yukuan Hu, Junlei Yin, Xingyu Gao +2
This paper is concerned with crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and form…