AI-Driven Flexible Electrochemical Microsystems for Real-Time and Multiplex Monitoring of Emerging Pharmaceutical Contaminants

The rapid occurrence of pharmaceutical residues in aquatic environments has created an increasing need for compact, sensitive, and intelligent monitoring technologies. Conventional analytical approaches often require centralized laboratories, sophisticated instrumentation, and extensive sample preparation. Flexible electrochemical sensor systems offer an alternative by enabling miniaturized, low-power, and potentially portable platforms for real-time contaminant monitoring. Recent advances in nanostructured materials, flexible electrodes, microfluidics, wearable electronics, and artificial intelligence are creating new opportunities for developing intelligent sensing systems. In particular, nanostructured ZnO–carbon platforms can provide high electroactive surface area, improved charge transfer, and mechanical flexibility. Integration with machine-learning algorithms can further improve signal interpretation, analyte classification, calibration, interference correction, and prediction of contaminant concentrations.This Research Topic will focus on the engineering, fabrication, characterization, optimization, and intelligent operation of flexible and miniaturized sensor systems for pharmaceutical and emerging-contaminant monitoring. Contributions addressing sensor architecture, nanomaterial–electrode interfaces, flexible substrates, microfluidic integration, signal processing, AI-assisted sensing, multiplex detection, portable instrumentation, and real-time environmental monitoring are particularly encouraged.The increasing occurrence of pharmaceutical residues and emerging contaminants in aquatic environments poses a significant challenge to environmental safety and public health. Conventional analytical methods, although highly accurate, often require centralized laboratories, expensive instrumentation, skilled personnel, and complex sample preparation, limiting their application for rapid and continuous field monitoring. This Research Topic aims to address these limitations by advancing flexible, miniaturized, and intelligent electrochemical sensor platforms capable of sensitive, selective, and real-time detection of pharmaceutical contaminants. Recent advances in nanostructured materials (particularly ZnO–carbon nanocomposites), flexible electrodes, microfluidics, and wearable electronics provide opportunities to enhance electroactive surface area, charge-transfer kinetics, mechanical flexibility, and sensing performance. Furthermore, integration of artificial intelligence and machine-learning algorithms can improve signal processing, analyte classification, interference correction, calibration, and concentration prediction. Combining these technologies with multiplexed sensing, portable instrumentation, wireless connectivity, and real-time data analysis can enable compact and intelligent monitoring systems suitable for environmental applications. The Research Topic therefore seeks innovative approaches toward scalable, reliable, low-power, and field-deployable sensing technologies for next-generation water-quality monitoring.- Flexible ZnO, carbon, graphene, MXene, and metal-oxide electrodes- Nanoengineered electrochemical sensing interfaces- Flexible and wearable electrochemical devices- MEMS/NEMS-based contaminant sensors- Microfluidic-integrated sensing systems- AI and machine learning for electrochemical signal interpretation- Multiplex detection of pharmaceuticals and personal-care products- Real-time and continuous environmental monitoring- Portable and low-power sensor instrumentation- Sensor calibration and drift correction- Sensor fusion and intelligent data acquisition- IoT-enabled environmental sensing- Smartphone-integrated sensing platforms- Mechanical flexibility, durability, and fatigue of sensor platforms- Electrode architecture and mass-transfer optimization- Stability and regeneration of nanostructured sensing interfaces- Field validation in wastewater and natural water- Sustainable and low-energy sensor design Topic editors: Rishi Ranjan Kumar, Dr Chandra Kumar, Kamakshi Pandey, Garima Awasthi Source: https://www.frontiersin.org/research-topics/85689/ai-driven-flexible-electrochemical-microsystems-for-real-time-and-multiplex-monitoring-of-emerging-pharmaceutical-contaminants