Research on the Application Status of Artificial Intelligence in Covalent Organic Frameworks

Abstract In recent years, the popularity of artificial intelligence (AI) has been rising, and its application fields have been expanding. In the field of covalent organic frameworks (COFs), AI can efficiently and quickly assist the screening, prediction, design, and optimization of COFs, thus expanding the application field of COFs. This paper systematically reviews the research progress in the application of AI in COFs in recent 5 years (2021–2025), and focuses on how machine learning (ML) and other algorithms can empower the structural design, performance prediction, and function optimization of COFs, so as to efficiently prepare target materials. And focus on its cross‐disciplinary applications in life and health, food, environment, energy and so on. In the end, the research trend of AI technology in COFs is prospected, and the core challenges faced by this cross‐field research (such as the shortage of interdisciplinary talents) are analyzed, so as to provide some reference for related research.

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Publication Details

Journal
ChemistrySelect
Published
2025-11-01
DOI
https://doi.org/10.1002/slct.202504991
Primary Topic
Covalent Organic Framework Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on the Application Status of Artificial Intelligence in Covalent Organic Frameworks

Shaoxiang Yang, Yuhan Zhao
ChemistrySelect
Covalent Organic Framework Applications
article

Research on the Application Status of Artificial Intelligence in Covalent Organic Frameworks

Shaoxiang Yang, Yuhan Zhao
article en

Abstract

Abstract In recent years, the popularity of artificial intelligence (AI) has been rising, and its application fields have been expanding. In the field of covalent organic frameworks (COFs), AI can efficiently and quickly assist the screening, prediction, design, and optimization of COFs, thus expanding the application field of COFs. This paper systematically reviews the research progress in the application of AI in COFs in recent 5 years (2021–2025), and focuses on how machine learning (ML) and other algorithms can empower the structural design, performance prediction, and function optimization of COFs, so as to efficiently prepare target materials. And focus on its cross‐disciplinary applications in life and health, food, environment, energy and so on. In the end, the research trend of AI technology in COFs is prospected, and the core challenges faced by this cross‐field research (such as the shortage of interdisciplinary talents) are analyzed, so as to provide some reference for related research.

ChemistrySelectVol. 10(43)
Beijing Technology and Business University (CN)
Openalex Percentile: Top 72%
Covalent Organic Framework Applications
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