Molecularly imprinted dual-mode sensing of emerging contaminants in complex water matrices: A review

Emerging and priority organic contaminants, including per- and polyfluoroalkyl substances (PFAS), pharmaceuticals and personal care products, endocrine-disrupting compounds, pesticides, and phenolic pollutants, are often present in natural and engineered water systems at trace or ultratrace levels. Their detection is affected by matrix components, including natural organic matter, inorganic ions, suspended particles, structurally related compounds, and background optical or electrochemical signals. These interferences hinder conventional single-mode sensors from providing stable and reliable responses in real water samples. Molecularly imprinted polymers (MIPs), with tailor-made recognition sites, chemical robustness, and compatibility with enrichment and sensing interfaces, provide a platform for improving selectivity in complex matrices. When integrated with dual-mode readout, MIP-based sensors can improve analytical reliability through signal cross-validation, internal correction, or coupled amplification. This review summarizes recent advances in molecularly imprinted dual-mode sensors for water pollutant detection, emphasizing their adaptation to complex water matrices. After outlining research trends through bibliometric analysis, we discuss MIP-based pretreatment and recognition interfaces, recognition-induced signal transduction, and the synergistic logic of representative dual-mode systems. The applications of these systems to PFAS, phenolic and halogenated phenolic compounds, pesticides and herbicides, and antibiotics are compared in terms of analytical demands, real-sample validation, signal division, and application boundaries. Finally, we discuss challenges related to interfacial antifouling, long-term recognition stability, dual-signal cross-talk, standardized evaluation, green preparation, portable devices, and intelligent data analysis. This perspective highlights reliability-oriented evaluation as a central criterion for developing MIP-based dual-mode sensors in complex water matrices, with particular attention to pollutant-specific recognition chemistry, matrix-induced signal bias, and regulatory-oriented validation.