ArticleJACS Au2025
Data-Driven Search Algorithm for Discovery of Synthesizable Zeolitic Imidazolate Frameworks.
Article in JACS Au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Hierarchical crystal structure prediction of zeolitic imidazolate frameworks using DFT and machine-learned interatomic potentials.Chemical science · 2026Article
- Data Management and Analysis of Metal-Organic Framework Synthesis Using Data Models.Journal of chemical information and modeling · 2026Article
- Sustainable zeolite synthesis: advances in green strategies and AI-assisted design.Frontiers in chemistry · 2026Review
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Authors and funding
11 authors.
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Abstract
Zeolitic imidazolate frameworks (ZIFs), metal-organic analogues of zeolites, hold great potential for carbon-neutral applications due to their exceptional stability and porosity. However, ZIF discovery has been hindered by the limited topologies resulting from a mismatch between numerous predicted and few synthesized zeolitic networks. To address this, we propose a data-driven search algorithm using structural descriptors of known materials as a screening tool. From over 4 million zeolite structures, we identified potential ZIF candidates based on O-T-O angle differences, vertex symbols, and T-O-T angles. Energy calculations facilitated the ranking of ZIFs by their synthesizability, leading to the successful synthesis of three ZIFs with two novel topologies: UZIF-31 (
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