Advances in catalysis for biodiesel production: Integrating AI-driven optimization and bibliometric insights into renewable energy technologies.

The global pursuit of sustainable and low-emission energy solutions has made biodiesel as a main focus in renewable energy research. This review explores recent advancements in catalysis for biodiesel production, focusing on the integration of artificial intelligence (AI) techniques and bibliometric analysis. This review outlines the fundamental catalytic systems used in transesterification, emphasizing the functions of homogeneous and heterogeneous catalysts, particularly metal oxide catalysts, and elucidating catalytic reaction mechanisms. This review examines emerging strategies for catalyst design, focusing on nanomaterials, biomass-derived catalysts, and green synthesis methods, as well as their application in the valorization of waste oils within a circular economy framework. Additionally, advances in AI and machine learning are discussed as transformative tools for optimizing reaction parameters, predicting catalyst performance, and enabling intelligent process control. Case studies demonstrate the advantages of AI in process scale-up, catalyst reusability, and real-time decision-making. This study presents a bibliometric analysis from 2005 to May 2025, focusing on publication trends, leading journals, authors, affiliations, and global research contributions. Keyword co-occurrence and thematic mapping further reveal the evolution of research priorities and interdisciplinary connections. Despite significant advancements, challenges remain, especially regarding catalyst deactivation, integration with smart energy systems, and improving the predictive reliability of AI models. This review concludes by proposing future research directions focused on data-driven catalyst design, AI-integrated process monitoring, and sustainability innovation. By integrating bibliometric analysis with critical assessment, this review serves as a strategic resource for researchers seeking to enhance biodiesel technology by integrating catalysis with AI and renewable energy systems.