Porous Material-Based Electronic Noses for the Sensing of Volatile Organic Compounds
- 21 October 2025
- journal article
- review article
- Published by American Chemical Society (ACS) in ACS Applied Materials & Interfaces
- Vol. 17 (44) , 60055-60103
Abstract
Volatile organic compounds (VOCs) serve as key markers in environmental monitoring, healthcare, and food safety, yet their detection remains challenging due to low concentrations and complex matrices. Porous materials, with their tunable pore structures, high specific surface areas, and modifiable surface chemistries, have emerged as ideal sensing materials for electronic nose (e-nose) systems. This comprehensive review systematically explores the classification and synthetic strategies of porous materials─including microporous zeolites, mesoporous silicas, metal-organic frameworks (MOFs), carbon-based materials, and porous polymers─and their integration into e-nose platforms. We provide a detailed account of the working principles, sensor array designs, and pattern-recognition algorithms that underpin e-nose functionality. The review highlights the application of porous materials in enhancing sensor sensitivity, selectivity, and stability through molecular sieving, surface functionalization, and hierarchical pore-structure engineering. Advanced performance-optimization strategies such as pore-structure engineering, surface-chemistry modification, and device-level innovations are discussed. Moreover, we showcase practical applications in medical diagnostics, environmental monitoring, and food-quality control, demonstrating the transition from laboratory research to real-world applications. Despite progress, challenges remain in long-term stability, cost-effective scalability, standardization, and anti-interference capabilities. Future directions point toward miniaturization, AI-driven data analysis, multimodal sensor fusion, and bioinspired design. This review underscores the transformative potential of porous-material-based e-noses in achieving precise, reliable, and scalable VOC detection for next-generation intelligent sensing systems.Keywords
Funding Information
- East China Normal University (2025ZY-008)
- Natural Science Foundation of Chongqing Municipality (CSTB2023NSCQ-MSX0339)
- Science and Technology Commission of Shanghai Municipality (24140711700)
- National Natural Science Foundation of China (22274051, 22274053)
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