Artificial Intelligence in Sustainable and Green Chemistry Education: A Bibliometric Analysis

The integration of Artificial Intelligence (AI) into sustainable and green chemistry education represents a growing interdisciplinary research area that addresses technological advancements and environmental responsibility. This study provides a comprehensive bibliometric analysis of global research trends on AI applications in sustainable and green chemistry education from 2013 to 2025. A total of 56 relevant documents were retrieved from the Scopus database and analyzed using VOSviewer and Biblioshiny. The analysis revealed several prominent research themes: the application of technology and innovation to address sustainability and industrial challenges; the development of AI-based modeling, prediction, and data-driven applications in chemical and environmental processes; the growing attention to researcher roles and the implementation of AI in educational contexts; and critical reflections on the limitations and challenges faced in applying AI to green chemistry education. Co-authorship and keyword co-occurrence networks indicated an emerging, yet still fragmented, collaboration landscape across different countries and institutions. Highly cited articles emphasized the role of AI in enhancing students’ conceptual understanding of sustainable chemical practices. These findings suggest that while significant progress has been made in technological integration and environmental modeling, greater efforts are needed to strengthen real-world implementation and to address existing barriers. This study offers valuable insights for researchers, educators, and policymakers seeking to advance sustainable practices in chemistry education through AI innovation.