Researchers have mapped three decades of technological progress in proton exchange membrane fuel cell systems by analyzing citation networks across the Web of Science Core Collection. The study identified 1,209 journal articles published between 1995 and 2025, then applied Main Path Analysis to reveal how knowledge has flowed through the hydrogen fuel cell research community.
The analysis uncovered four major technological transitions. The field began with foundational work on PEMFC design, materials science, and manufacturing processes in the late 1990s and early 2000s. Research then shifted toward solving durability challenges and enabling high-temperature operation—critical barriers for commercial deployment. By the early 2010s, the focus expanded to hybrid fuel cell-electric vehicle (FCHEV) architectures, reflecting industry interest in transportation applications.
Most recently, a fourth wave has emerged: artificial intelligence and machine learning applied to energy management and real-time operational control of fuel cell systems. This shift signals maturation from single-component optimization toward holistic, intelligent energy platforms capable of dynamic response in grid and vehicular settings.
The main path analysis used Search Path Link Count methodology to identify dominant knowledge diffusion routes—essentially tracing which research breakthroughs most influenced subsequent work. This approach reveals not just what was published, but which ideas shaped the field's direction.
The implications are substantial. Energy professionals and hydrogen infrastructure planners should recognize that competitive advantages increasingly depend on system-level integration and software sophistication, not component performance alone. However, researchers acknowledge methodological limitations: the analysis relies exclusively on Web of Science data, and citation lag may underrepresent cutting-edge trends emerging in the past 1–2 years. Emerging research in advanced materials or novel manufacturing may not yet appear prominently in citation networks. Nevertheless, this evidence-based evolution map provides valuable guidance for strategic research planning and technology investment decisions.
