Physics-Aware Representation Learning on Electronic Charge Density for Materials Property Prediction
= 0.89). This work establishes electronic charge density as a transferable, physics-grounded descriptor for materials property prediction, requiring ≈1/25 of the computational resources of full-fledged DFT calculations.
Authors
- Somnath Bhowmick (ORCID: https://orcid.org/0000-0003-4094-5204)
- Albert Linda
- Shubham Kumar Maurya
- Kammampati Sai Kumar
Institutions
- Indian Institute of Technology Kanpur (IN)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2026-05-29
- DOI
- https://doi.org/10.1021/acs.jcim.6c00235
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00