Abdelhamid Mohamed A A, Ki Mi-Ran, Yoon Hyo Jik, Pack Seung Pil
Faculty of Education and Arts, Sohar University, Sohar 311, Oman.
Department of Biotechnology and Bioinformatics, Korea University, Sejong-ro 2511, Sejong 30019, Republic of Korea.
Biosensors (Basel). 2025 Jul 22;15(8):474. doi: 10.3390/bios15080474.
The widespread and persistent occurrence of micropollutants-such as pesticides, pharmaceuticals, heavy metals, personal care products, microplastics, and per- and polyfluoroalkyl substances (PFAS)-has emerged as a critical environmental and public health concern, necessitating the development of highly sensitive, selective, and field-deployable detection technologies. Microfluidic sensors, including biosensors, have gained prominence as versatile and transformative tools for real-time environmental monitoring, enabling precise and rapid detection of trace-level contaminants in complex environmental matrices. Their miniaturized design, low reagent consumption, and compatibility with portable and smartphone-assisted platforms make them particularly suited for on-site applications. Recent breakthroughs in nanomaterials, synthetic recognition elements (e.g., aptamers and molecularly imprinted polymers), and enzyme-free detection strategies have significantly enhanced the performance of these biosensors in terms of sensitivity, specificity, and multiplexing capabilities. Moreover, the integration of artificial intelligence (AI) and machine learning algorithms into microfluidic platforms has opened new frontiers in data analysis, enabling automated signal processing, anomaly detection, and adaptive calibration for improved diagnostic accuracy and reliability. This review presents a comprehensive overview of cutting-edge microfluidic sensor technologies for micropollutant detection, emphasizing fabrication strategies, sensing mechanisms, and their application across diverse pollutant categories. We also address current challenges, such as device robustness, scalability, and potential signal interference, while highlighting emerging solutions including biodegradable substrates, modular integration, and AI-driven interpretive frameworks. Collectively, these innovations underscore the potential of microfluidic sensors to redefine environmental diagnostics and advance sustainable pollution monitoring and management strategies.
微污染物（如农药、药品、重金属、个人护理产品、微塑料以及全氟和多氟烷基物质（PFAS））的广泛且持续存在已成为关键的环境和公共卫生问题，这就需要开发高灵敏度、高选择性且可现场部署的检测技术。包括生物传感器在内的微流控传感器已成为实时环境监测的通用且变革性工具，能够精确快速地检测复杂环境基质中的痕量污染物。其小型化设计、低试剂消耗以及与便携式和智能手机辅助平台的兼容性使其特别适合现场应用。纳米材料、合成识别元件（如适配体和分子印迹聚合物）以及无酶检测策略方面的最新突破，在灵敏度、特异性和多重检测能力方面显著提升了这些生物传感器的性能。此外，将人工智能（AI）和机器学习算法集成到微流控平台中，为数据分析开辟了新领域，实现了自动信号处理、异常检测和自适应校准，以提高诊断准确性和可靠性。本综述全面概述了用于微污染物检测的前沿微流控传感器技术，重点介绍了制造策略、传感机制及其在不同污染物类别中的应用。我们还探讨了当前面临的挑战，如设备稳健性、可扩展性和潜在的信号干扰，同时强调了包括可生物降解底物、模块化集成和人工智能驱动的解释框架等新兴解决方案。总体而言，这些创新凸显了微流控传感器在重新定义环境诊断以及推进可持续污染监测和管理策略方面的潜力。
