Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery

Li, Chunhua; Bao, Luqian; Ji, Yixin; Tian, Zhehang; Cui, Mengyao; Shi, Yubo; Zhao, Zhilei; Wang, Xianyou

doi:10.1016/j.ccr.2024.215888

Coordination Chemistry Reviews

2024

DOI: 10.1016/j.ccr.2024.215888

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Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery

Chunhua Li,

Luqian Bao,

Yixin Ji

et al.

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2024

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Cited by 2 publications

References 148 publications

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Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Naik,

Jagtap

2024

Nano TransMed

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Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Naik,

Jagtap

2024

Nano TransMed

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Organic and Metal–Organic Polymer-Based Catalysts—Enfant Terrible Companions or Good Assistants?

Králik,

Koóš,

Markovič

et al. 2024

Molecules

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This overview provides insights into organic and metal–organic polymer (OMOP) catalysts aimed at processes carried out in the liquid phase. Various types of polymers are discussed, including vinyl (various functional poly(styrene-co-divinylbenzene) and perfluorinated functionalized hydrocarbons, e.g., Nafion), condensation (polyesters, -amides, -anilines, -imides), and additional (polyurethanes, and polyureas, polybenzimidazoles, polyporphyrins), prepared from organometal monomers. Covalent organic frameworks (COFs), metal–organic frameworks (MOFs), and their composites represent a significant class of OMOP catalysts. Following this, the preparation, characterization, and application of dispersed metal catalysts are discussed. Key catalytic processes such as alkylation—used in large-scale applications like the production of alkyl-tert-butyl ether and bisphenol A—as well as reduction, oxidation, and other reactions, are highlighted. The versatile properties of COFs and MOFs, including well-defined nanometer-scale pores, large surface areas, and excellent chemisorption capabilities, make them highly promising for chemical, electrochemical, and photocatalytic applications. Particular emphasis is placed on their potential for CO2 treatment. However, a notable drawback of COF- and MOF-based catalysts is their relatively low stability in both alkaline and acidic environments, as well as their high cost. A special part is devoted to deactivation and the disposal of the used/deactivated catalysts, emphasizing the importance of separating heavy metals from catalysts. The conclusion provides guidance on selecting and developing OMOP-based catalysts.

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Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery

Cited by 2 publications

References 148 publications

Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology

Organic and Metal–Organic Polymer-Based Catalysts—Enfant Terrible Companions or Good Assistants?

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