Emerging analytical frontiers in microplastic detection: From spectroscopy to smart sensor technologies

Abstract

Microplastics (MPs) and nanoplastics (NPs), defined as synthetic polymeric particles smaller than 5 mm and 1 μm, respectively, have emerged as pervasive and persistent pollutants across aquatic, terrestrial, and atmospheric environments, as well as within biological systems. Their heterogeneous physicochemical nature spanning diverse polymer compositions, morphologies, and surface chemistries complicates detection, especially in complex matrices at environmentally relevant concentrations. This review critically examines the recent advances in analytical methodologies for the detection, identification, and quantification of MPs and NPs, with a focus on interdisciplinary innovations spanning vibrational spectroscopy (µ-FTIR, µ-Raman, SRS), thermal decomposition-mass spectrometry (Py-GC–MS, TED-GC–MS, TOF-SIMS), and emerging electrochemical sensing strategies (EIS, PEC, and voltammetric sensors). Particular attention is given to electrochemical platforms that exploit polymer–electrode interfacial interactions, enabling label-free, sensitive, and real-time detection with potential for miniaturization and in-field deployment. Additionally, the integration of artificial intelligence and machine learning algorithms with high-dimensional spectral and electrochemical datasets is discussed as a transformative approach for enhancing classification accuracy, reducing analysis time, and facilitating automated detection. The review also highlights recent demonstrations of point-of-care devices, smartphone-integrated sensors, and microfluidic-based capture systems capable of detecting MPs/NPs in environmental and biological matrices. Finally, key challenges, including nanoplastic traceability, spectral overlap, lack of standardization, and the absence of certified reference materials, are evaluated, and future directions are proposed for the development of unified, high-throughput, and regulatory-compliant detection frameworks.