140 citations · 226 across the 16 of their papers we have counts for
9 papers · 1 filter
Pseudopotentials for Orbital-Free DFT: Capturing Nonlocality and Correcting Functional Approximants
Valeria Rios-Vargas, Ezekiel Oyeniyi, Xuecheng Shao +4
Developing reliable pseudopotentials for orbital-free density functional theory (OF-DFT), especially for transition metals, remains a significant challenge. In this study, we provi…
CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
Xiaoshan Luo, Zhenyu Wang, Qingchang Wang +4
Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approac…
Nonlocal vs Local Pseudopotentials Affect Kinetic Energy Kernels in Orbital-Free DFT
Zhandos A. Moldabekov, Xuecheng Shao, Michele Pavanello +2
The kinetic energy (KE) kernel, which is defined as the second order functional derivative of the KE functional with respect to density, is the key ingredient to the construction o…
Accelerating Structural Optimization through Fingerprinting Space Integration on the Potential Energy Surface
Shuo Tao, Xuecheng Shao, Li Zhu
Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique in particular. In this stu…
Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory
Lenz Fiedler, Zhandos A. Moldabekov, Xuecheng Shao +4
We introduce a practical hybrid approach that combines orbital-free density functional theory (DFT) with Kohn-Sham DFT for speeding up first-principles molecular dynamics simulatio…
A Symmetry-orientated Divide-and-Conquer Method for Crystal Structure Prediction
Xuecheng Shao, Jian Lv, Peng Liu +5
Crystal structure prediction has been a subject of topical interest, but remains a substantial challenge, especially for complex structures as it deals with the global minimization…