Artificial Intelligence in Metal–Organic Frameworks from 2013 to 2024: A Bibliometric Analysis

Abstract

The purpose of this work is to analyze the development direction and prospects in the field of artificial intelligence (AI) in metal–organic frameworks (MOFs) and to provide reference information for related research and industry personnel. The scientific papers on AI in MOFs published in Web of Science database from 2013 to mid-2024 were collected. Bibliometric methods and knowledge mapping visualization software were used to analyze the papers. Both quantitative statistics and qualitative comparative analysis of global scientific papers were done in terms of annual paper trends, papers by major countries, authors, institutions, journals and research topics, respectively. The results showed that the number of published papers has increased in recent years. The top three productive countries are China, the USA and Germany, respectively. The top three productive institutions are Guangzhou University, Northwestern University and Chinese Academy of Sciences, respectively. Reference co-citation analysis classifies references into four clusters, and keyword co-occurrence analysis divides keywords into six clusters. Bibliometric and network analyses were utilized to examine the distribution of research outcomes, enabling scholars to discern the prevailing trends and focal points within the domain of AI-MOFs.