Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning (Adv. Funct. Mater. 14/2026)
Synthesizable Metal–Organic Frameworks In a futuristic MOF factory, an AI scientist inspects frameworks flowing along a production line. Floating blueprints and free-energy maps represent a molecular-dynamics-informed TabPFN model, which screens vast hypothetical MOF libraries and highlights synthesizable, experimentally actionable candidates. More information can be found in the Research Article by Jianwen Jiang and co-workers (10.1002/adfm.202519565).
Authors
- Xiaoyu Wu (ORCID: https://orcid.org/0009-0002-1287-9799)
- Jianwen Jiang (ORCID: https://orcid.org/0000-0002-8449-6992)
- Quan Liu
- Rui Zheng
Institutions
- National University of Singapore (SG)
- Anhui University of Science and Technology (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1002/adfm.74277
- Primary Topic
- Metal-Organic Frameworks: Synthesis and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00