Work

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning (Adv. Funct. Mater. 14/2026)

Year: 2026

Type: article

Abstract: 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).

Source: Advanced Functional Materials

DOI: 10.1002/adfm.74277

Authors: Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang

Institutions: National University of Singapore, Anhui University of Science and Technology

Language: English

Topic: Metal-Organic Frameworks: Synthesis and Applications

Subfield: Inorganic Chemistry

Field: Chemistry

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W7129422454

FWCI: 1.352

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Cited by: 1

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