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).

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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
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article

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

Xiaoyu Wu, Jianwen Jiang, Quan Liu, Rui Zheng
Advanced Functional Materials
Metal-Organic Frameworks: Synthesis and Applications
article

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

Xiaoyu Wu, Jianwen Jiang, Quan Liu, Rui Zheng
article en

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).

Advanced Functional MaterialsVol. 36(14)
National University of Singapore (SG), Anhui University of Science and Technology (CN)
Openalex Percentile: Top 53%
Metal-Organic Frameworks: Synthesis and Applications
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