FTIR-based quantification of microplastics: Scopus-based bibliometric analysis and forecasting of research trajectories with Artificial Intelligence (AI)

Microplastics are environmentally persistent pollutants with increasing ecological and human health concerns, making accurate quantification essential for environmental monitoring, risk assessment, and mitigation. Although FTIR spectroscopy is one of the most widely used techniques for microplastic characterization and quantification, existing reviews have largely focused on analytical methodologies or conventional bibliometric analyses, providing limited insight into the thematic evolution and future research trajectories of this field. To address this gap, this review integrates bibliometric analysis with machine-learning-based semantic analysis and forecasting to comprehensively evaluate FTIR-based microplastic quantification using 198 Scopus-indexed research articles published between 2015 and 2024. Bibliometric analyses were performed using VOSviewer and Biblioshiny, while SciBERT embeddings, UMAP dimensionality reduction, and KMeans clustering were employed to identify conceptual research domains. Research evolution was further explored using Prophet and exponential smoothing models. The analysis revealed rapid growth in FTIR-related microplastic research since 2018, accompanied by strong international collaboration and four major thematic domains: analytical techniques, environmental distribution, ecotoxicological effects, and wastewater treatment. The review further highlights key methodological challenges, including analytical standardization, quality assurance, particle-size detection, and spectral library development, while forecasting indicates continued growth across these research domains. Overall, this review provides a comprehensive synthesis of the intellectual landscape, methodological challenges, and future research directions in FTIR-based microplastic quantification.