activity
20232025
most citedA Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2025

ABACUS: An Electronic Structure Analysis Package for the AI Era

Weiqing Zhou, Daye Zheng, Qianrui Liu +55

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It…

cond-mat.soft2024

GMXPolymer: a generated polymerization algorithm based on GROMACS

Jianchuan Liu, Haiyan Lin, Xun Li

This work introduces a method for generating generalized structures of amorphous polymers using simulated polymerization and molecular dynamics equilibration, with a particular foc…

physics.chem-ph2023

DPA-2: a large atomic model as a multi-task learner

Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…

cond-mat.mtrl-sci2023

Machine-Learning-Based Interatomic Potentials for Group IIB to VIA Semiconductors: Towards a Universal Model

Jianchuan Liu, Xingchen Zhang, Tao Chen +4

Rapid advancements in machine-learning methods have led to the emergence of machine-learning-based interatomic potentials as a new cutting-edge tool for simulating large systems wi…

cond-mat.mtrl-sci20232 cited

A Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials

Taiping Hu, Teng Yang, Jianchuan Liu +9

Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dyna…