ABACUS: An electronic structure analysis package for the AI era

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 mainly features density functional theory (DFT) and molecular dynamics functions and is compatible with both plane wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as deep potential with attention models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several artificial intelligence-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, HamGNN, etc.

Authors

Institutions

Publication Details

Journal
The Journal of Chemical Physics
Published
2025-11-20
DOI
https://doi.org/10.1063/5.0297563
Citations
5
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
2.59
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ABACUS: An electronic structure analysis package for the AI era

Tongqi Wen, Fu‐Zhi Dai, Denghui Lu, Yang Zhong et al.
5 citations
The Journal of Chemical Physics
Machine Learning in Materials Science
2.59
article

ABACUS: An electronic structure analysis package for the AI era

Tongqi Wen, Fu‐Zhi Dai, Denghui Lu, Yang Zhong, Peize Lin, Zhao‐Qing Liu, Yong Xu, Haochong Zhang, Yiwei Fu, Wenhui Duan, Zhuoyuan Li, J. Gan, Shenzhen Xu, Yuyang Ji, Qiangqiang Gu, Lixin He, Qianrui Liu, Renxi Liu, Qijing Zheng, Daye Zheng, Jie Bao, Zheng Shen, Xinguo Ren, Weiqing Zhou, Jianchuan Liu, Yike Huang, Zechen Tang, Zuxin Jin, Ben Xu, Qi Ou, Mohan Chen, Hong Jiang, Hongjun Xiang, Xing‐Liang Peng, Jin Zhao, Xinyuan Liang, Maochang Liu, Xiaoyang Wang, Tao Liu, Yu Liu, Xiaohui Liu, Li Yuanbo, Shi Liu, Yuzhi Zhang, Linfeng Zhang, Ming Sun, Xiaoyang Zhang, Tao Chen, Chun Cai, Jing Wu, Haozhi Han, Z. Y. Deng, Yu Cao, Tiantian Bao, Hongxu Ren, Nuo Chen, Xingao Gong, Liang Sun
article en
5 citations

Abstract

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 mainly features density functional theory (DFT) and molecular dynamics functions and is compatible with both plane wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as deep potential with attention models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several artificial intelligence-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, HamGNN, etc.

The Journal of Chemical PhysicsVol. 163(19)
Xihua University (CN), Sinopec (China) (CN), University of Science and Technology of China (CN), Institute of Applied Physics (UA), Hefei University of Technology (CN), Wuhan University of Technology (CN), Peking University (CN), Fudan University (CN), China Academy of Engineering Physics (CN), Westlake University (CN), Wuhan University (CN), Beijing University of Technology (CN), Institute for History of Natural Sciences (CN), CAS Key Laboratory of Urban Pollutant Conversion (CN), RIKEN Center for Emergent Matter Science (JP), Quantum Design (Germany) (DE), National Science Centre (PL), Institute for Advanced Study (DE), Institute of Applied Physics and Computational Mathematics (CN), Beijing Academy of Quantum Information Sciences (CN), Collaborative Innovation Center of Chemistry for Energy Materials (CN), Institute of Physics (CN), Center for Life Sciences (CN), Quantum Technologies (Sweden) (SE), State Key Laboratory of Low-Dimensional Quantum Physics, Wuhan University of Science and Technology (CN), Xi’an Jiaotong-Liverpool University (CN), Xi'an Jiaotong University (CN), University of Hong Kong (HK), University of Science and Technology Beijing (CN), Tsinghua University (CN)
Openalex Percentile: Top 9%
Machine Learning in Materials Science
2.59
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.