Review discusses the integration of carbon-based materials in microfluidic systems for improved water monitoring technologies.
Carbon-based materials, including graphene, carbon nanotubes, laser-induced graphene, and pyrolyzed glassy carbon, are widely used in sensing applications due to their high conductivity, large surface area, and tunable surface chemistry. Meanwhile, microfluidic systems enable precise fluid handling, reduced sample consumption, and enhanced analytical performance through improved mass transport and device miniaturization. The integration of carbon-based materials with microfluidic platforms has enabled the development of compact, portable, and highly sensitive devices for water monitoring. This review summarizes recent advances in carbon-based microfluidic sensors for water monitoring applications. Key carbon materials and their sensing mechanisms, particularly electrochemical transduction, are discussed. Various microfluidic integration strategies, including paper-based devices, polymer-based devices, MEMS-based systems, and flexible platforms, are highlighted, with emphasis on mass transport enhancement and overall system performance. Representative recent advances in carbon-based microfluidic sensors for water monitoring, including the detection of heavy metal ions, nutrients, and emerging contaminants, are reviewed. Finally, challenges related to scalable manufacturing, long-term operational stability, biofouling/surface fouling, and reproducible system integration are discussed, together with future perspectives on intelligent carbon-based microfluidic platforms featuring AI-assisted analytics, sense-response functionality, and self-healing and dynamic antifouling capabilities for water monitoring. These advances are expected to enable real-time, low-cost, and field-deployable water monitoring systems for environmental protection and public health management. Overall, this review highlights the critical role of integrating carbon-based sensing materials with microfluidic engineering in advancing next-generation water monitoring technologies.
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Li et al. (2026) studied this question.
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