Yadav Vikas, Arkoti Naveen Kumar, Gautam Shivam K, Kuppireddy Suresh, Yendrapati Taraka Prabhu, Modem Sudhakar, Narayana Chandrabhas, Lee Hi-Deok, Siddhanta Soumik, Jayarmaulu Kolleboyina
Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Hybrid Porous Materials Lab, Department of Chemistry, Indian Institute of Technology Jammu, Jammu & Kashmir, 181221, India.
Nanoscale. 2025 Aug 29. doi: 10.1039/d5nr01757b.
Among various pollutants, nitrogen oxides (NO) stand out as particularly harmful irritant gases, known to cause airway inflammation at elevated concentrations. Chemiresistive gas sensing (CGS) has revolutionized gas detection with its low power consumption, cost-effectiveness, high sensitivity, fast response, and long-term stability. Traditional materials such as metal oxides, conducting polymers, and carbon-based materials used for NO detection often suffer from poor selectivity and require high operating temperatures, leading to high noise levels. In contrast, nanoporous materials offer superior chemiresistive NO gas sensing performance due to their large surface area and unique structural properties. Our review focuses on the fundamental mechanisms of NO sensing in chemiresistive sensors, comparing n-type and p-type materials. It also discusses the fabrication of flexible, wearable chemiresistive sensors while addressing challenges related to uniformity, scalability, and stability. This review primarily highlights nanoporous materials, including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), porous organic frameworks (POFs), and their hybrids, which exhibit enhanced gas adsorption and tunable properties, making them highly effective for NO detection. Furthermore, Raman spectroscopy provides molecular-level insights into surface interactions, adsorption mechanisms, and charge-transfer dynamics, optimizing sensor selectivity, sensitivity, and stability for NO gas sensing applications. This review also explores the integration of Internet of Things (IoT) technologies and machine learning (ML) into gas sensing systems, focusing on structure optimization, material performance, and the underlying mechanisms of emerging porous materials. It emphasizes their potential for real-time monitoring and data analysis to enhance sensor performance. Finally, the review concludes with future directions, emphasizing the development of hybrid materials, advanced devices, and multifunctional sensors for industrial and environmental applications.
在各种污染物中,氮氧化物(NO)是特别有害的刺激性气体,已知在浓度升高时会引起气道炎症。化学电阻式气体传感(CGS)凭借其低功耗、成本效益高、灵敏度高、响应快和长期稳定性,彻底改变了气体检测方式。用于检测NO的传统材料,如金属氧化物、导电聚合物和碳基材料,往往选择性差,需要高温操作,导致噪声水平高。相比之下,纳米多孔材料由于其大表面积和独特的结构特性,具有卓越的化学电阻式NO气体传感性能。我们的综述重点关注化学电阻式传感器中NO传感的基本机制,比较n型和p型材料。它还讨论了柔性、可穿戴化学电阻式传感器的制造,同时解决了与均匀性、可扩展性和稳定性相关的挑战。本综述主要强调纳米多孔材料,包括金属有机框架(MOF)、共价有机框架(COF)、多孔有机框架(POF)及其混合物,它们表现出增强的气体吸附和可调特性,使其对NO检测非常有效。此外,拉曼光谱提供了关于表面相互作用、吸附机制和电荷转移动力学的分子水平见解,优化了用于NO气体传感应用的传感器选择性、灵敏度和稳定性。本综述还探讨了物联网(IoT)技术和机器学习(ML)在气体传感系统中的集成,重点关注结构优化、材料性能和新兴多孔材料的潜在机制。它强调了它们在实时监测和数据分析方面的潜力,以提高传感器性能。最后,综述以未来方向作为结论,强调开发用于工业和环境应用的混合材料、先进设备和多功能传感器。