Artificial Intelligence in Hydrogen Energy: A Comprehensive Bibliometric Analysis

Abstract

Energy is essential to almost every aspect of daily life, powering everything from basic human needs to advanced activities like transportation, communication, and industrial production. With the global population steadily increasing, the demand for energy continues to rise year after year. Fossil fuels remain the dominant energy source worldwide, forming the foundation of global energy consumption. However, their extensive use has significant drawbacks, including harmful impacts on human health and the environment. As a result, transitioning to renewable energy has become a pressing priority to address these challenges. Among renewable energy sources, hydrogen stands out as a promising energy carrier with vast potential. At the same time, Artificial Intelligence (AI) has emerged as a transformative tool across many industries, including the energy sector. AI techniques are increasingly being used to optimize various aspects of hydrogen and battery technologies, such as enhancing production efficiency, improving storage methods, and ensuring safety. In this context, this study investigates the role of AI in hydrogen research through a comprehensive bibliometric analysis. A dataset of 7,548 papers published between 2000 and 2024 was retrieved using an automated search on the Scopus digital library. These studies were analyzed using five key bibliometric indicators: descriptive statistics, author productivity, source productivity, scientific collaboration, and keyword analysis.