6 citations · 6 across the 3 of their papers we have counts for
4 papers · 1 filter
Accurately Generalizing Deep-Learning Hamiltonian Methods to Plane-Wave Density Functional Theory
Chuntian Wu, Jiaxiang Li, Qiang Xu +4
Deep neural networks that predict density functional theory (DFT) Hamiltonians from material structures offer a route to efficient electronic-structure calculations. However, exten…
ARES: a plane-wave density-functional-theory code in Rust
Zehan Liu, Qian Wang, Xiangyu Zheng +7
ARES (Ab initio atomic mateRial modEling Software at JLU) is a plane-wave density-functional-theory (DFT) code written entirely in Rust as a layered 22-crate workspace. It supports…
Self-Optimizing Machine Learning Potential Assisted Automated Workflow for Highly Efficient Complex Systems Material Design
Jiaxiang Li, Junwei Feng, Jie Luo +9
Machine learning interatomic potentials have revolutionized complex materials design by enabling rapid exploration of material configurational spaces via crystal structure predicti…
Electron--phonon matrix elements from eigenvalue projection within the projector augmented-wave method
Qian Wang, Jiaxiang Li, Yanming Ma +1
We present a finite-displacement approach to electron--phonon matrix elements that requires only eigenvalues and wave functions from the displaced calculations, for both norm-conse…