Abstract
<title>Abstract</title> <p>The field of Renewable Energies, Sustainability, and Environment Research (RESER), as represented in Scopus subject category ASJC 2105, has expanded substantially over the past two decades, reaching nearly 780,000 publications indexed in Scopus between 2000 and 2022. Yet its internal cognitive structure, how research fronts emerge, consolidate, and evolve over time, remains insufficiently mapped at a global scale. This study addresses that gap by applying a systematic and replicable co-word analysis protocol to a large Scopus-defined corpus. The approach combines a thesaurus of 25,728 descriptors, VOSviewer-based network clustering, sensitivity analysis of clustering parameters, and a second-derivative method for data-driven temporal segmentation. The analysis produces a large-scale cognitive map of the RESER field comprising five major research fronts: Biofuel Generation, Renewable Energy Storage, Solar Power Generation, Sustainability Policy, and Renewable Energy Structure. This five-front structure is subsequently projected onto three independently analyzed time periods (2000–2012, 2013–2019, and 2020–2022). Independent sensitivity analyses confirm the five-front structure in the first two periods and identify a sixth emerging front centered on artificial intelligence and renewable energy applications in the most recent period. The findings provide a comprehensive and empirically grounded cognitive map of how a large, interdisciplinary and institutionally defined research field reorganizes its knowledge base over time. Beyond the empirical case, the study contributes a transparent, reproducible, and applicable protocol for large-scale longitudinal cognitive mapping that can support comparative analysis of other large-scale research fields, offering a practical tool for research managers, funding agencies, and science policy analysts.</p>