Unravelling the evolution of nickel-catalyzed C–O bond activation with data-driven strategies
A chemistry platform, GPT-NiCOBot, combines large language models with chemistry-specific tools to facilitate research in the field of nickel-catalyzed C–O activation.
Authors
- Junqing Zhu (ORCID: https://orcid.org/0000-0003-4642-2981)
- Zhiyan Zou
- Haibin Su (ORCID: https://orcid.org/0000-0001-9760-6567)
- Yong Huang (ORCID: https://orcid.org/0000-0001-8377-8923)
- Yizhou Wang (ORCID: https://orcid.org/0000-0002-1318-6225)
- Zhenyang Lin (ORCID: https://orcid.org/0000-0003-4104-8767)
- Shihong Chen (ORCID: https://orcid.org/0000-0001-7101-1223)
- Imanuel Rava
Institutions
- Hong Kong University of Science and Technology (HK)
- University of Hong Kong (HK)
Publication Details
- Journal
- Organic Chemistry Frontiers
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1039/d5qo00947b
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00