Integrating artificial intelligence and molecular simulation in food chemical research: A bibliometric landscape of two decades (2006–2025)

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The convergence of artificial intelligence (AI) and molecular simulation is reshaping food chemical research, yet its evolution and structural patterns remain underexplored. This study conducts a bibliometric analysis of 4943 publications from the Web of Science and Scopus (2006∼2025) to map research trends, collaboration networks, and thematic structures. The results reveal exponential growth from 12 papers in 2006 to 1482 in 2025 with 64.0% published between 2023 and 2025, signaling a rapidly expanding field. China leads global contribution (42.1%), followed by India and Saudi Arabia, suggesting that AI-enhanced molecular simulation offers an accessible pathway for resource limited regions. Co-citation analysis identifies four clusters molecular simulation tools, structural bioinformatics, AI methodologies, and experimental validation. AlphaFold (Nature, 2021) emerges as a transformative yet incompletely integrated AI paradigm. A hierarchical link pattern shows molecular simulation bridging AI and food chemistry (MD–Food weight 93; AI–Food ≤ 8). Emerging hotspots such as network pharmacology, umami peptides, and network toxicology highlight a shift toward AI driven toxicity prediction and mechanism-based inquiry. This work provides a bibliometric roadmap of AI simulation integration, offering a strategic foundation for future food informatics and generative AI research.