Combining DeepH with HONPAS for accurate and efficient hybrid functional electronic structure calculations with ten thousand atoms
This work develops a DeepH + HONPAS interface for efficient large-scale electronic structure predictions. The method enables accurate and efficient simulations for systems with over 10 000 atoms.
Authors
- Xinming Qin (ORCID: https://orcid.org/0000-0001-6641-1003)
- Yifan Ke (ORCID: https://orcid.org/0000-0002-4443-5116)
- Jinlong Yang (ORCID: https://orcid.org/0000-0002-5651-5340)
- Wei Hu (ORCID: https://orcid.org/0000-0003-1384-8337)
Institutions
- University of Science and Technology of China (CN)
- Hefei National Center for Physical Sciences at Nanoscale (CN)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00128e
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities