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Published on: August 27, 2021
Impedance Analysis of Porous-Material-Functionalized RF Sensors toward Intelligent E-Nose and E-Tongue for
Zhiqiang Ma1, Yancheng Bi1, Chenyang Gao1
1College of Control Science and Engineering, Zhejiang University, Hangzhou310027, China.
None:
Electronic nose (e-nose) and electronic tongue (e-tongue) systems have emerged as powerful analytical tools for the rapid and specific detection of analytes. However, their performance is often impeded by technical bottlenecks inherent in traditional sensing technologies, particularly limited signal output dimensionality, short lifespan, and difficulties in miniaturization or integration. Radio frequency (RF) sensors, with their inherent advantages of multiparameter signal output, long-term stability, ease of integration, and wireless compatibility, offer a promising platform for e-nose and e-tongue development. In this context, porous materials can act as sensing films to adsorb target analytes, thereby modulating the impedance characteristics of RF sensors and facilitating robust detection. Notably, emerging porous materials, distinguished by their ultrahigh specific surface areas, tunable pore structures, and customizable surface chemistry, induce more rapid, pronounced, and targeted variations in the complex impedance of RF sensors during analyte interaction, which significantly enhance critical sensing metrics, including sensitivity, selectivity, and response kinetics. This review systematically summarizes the current research status of RF biochemical sensors integrated with porous materials, covering fundamental principles, material characteristics, and impedance-driven sensor analysis. Particularly, guided by the equivalent impedance model of RF sensors, we systematically propose design paradigms and performance optimization strategies. Furthermore, we analyze current advances and application scenarios in environmental monitoring, biomedical analysis, as well as process and quality control. Finally, we discuss future directions and ongoing challenges, providing a roadmap for next-generation intelligent e-nose and e-tongue systems.
