TripK <sub> <i>a</i> </sub> : Accurate and Scalable Acid–Base Dissociation Property Prediction via Triplet Interaction Networks and Physical Knowledge
Authors
- Dahao Xu
- Jiahua Rao (ORCID: https://orcid.org/0000-0002-6840-8198)
- Ye Lu (ORCID: https://orcid.org/0000-0002-4967-5557)
- Jiancong Xie (ORCID: https://orcid.org/0000-0001-9030-0709)
- Yuxuan Wang (ORCID: https://orcid.org/0000-0002-1649-6974)
- Bai Xue
- X.-F Sun (ORCID: https://orcid.org/0009-0001-8653-9327)
- Wentao Wei
- Mingjun Yang (ORCID: https://orcid.org/0000-0003-0928-8541)
- Yuedong Yang (ORCID: https://orcid.org/0000-0002-6782-2813)
Institutions
- Sun Yat-sen University (CN)
- Peng Cheng Laboratory (CN)
Publication Details
- Journal
- Journal of Chemical Information and Modeling
- Published
- 2026-04-13
- DOI
- https://doi.org/10.1021/acs.jcim.6c00330
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- China Postdoctoral Science Foundation
- Guangdong Science and Technology Department