Recent Advances in Wearable Gas Sensor Material Modules for Real-Time Environmental Gas Monitoring

可穿戴计算机 可扩展性 计算机科学 纳米技术 介孔材料 可穿戴技术 材料科学 信号处理 调制(音乐) 纳米材料 信号(编程语言) 工作(物理) 无线传感器网络 光学(聚焦) 氢 冗余(工程) 纳米机电系统
作者
Akanksha Pathak,Devendra Singh,Prerna Tripathi,Amit Kumar Verma,Atul Sharma,Shikha Singh
出处
期刊:ACS applied electronic materials [American Chemical Society]
卷期号:8 (17): 7227-7270
标识
DOI:10.1021/acsaelm.6c00976
摘要

Abstract Flexible electronics, textile engineering, and nanomaterials have combined to transform gas sensing from rigid devices into advanced wearable platforms. The most recent developments in flexible substrate-integrated gas sensor components are examined in this review, with particular attention paid to their ability to detect hydrogen (H2), nitrogen dioxide (NO2), and ammonia (NH3). Protonation-driven charge transfer for selective NH3 detection; catalytic lattice modulation via palladium hydride formation, which regulates H2 sensing via percolation dynamics; and adsorption-induced band modulation for NO2 detection based on oxidative electron withdrawal and engineered heterointerfaces are the three distinct methods of gas sensing. Furthermore, mesoporous diffusion paths, heterojunction-based signal amplification, defect-engineered nanostructures, and mechanically robust conductive networks all contribute to the improved performance of these systems. This work integrates textile compatibility, structural design, and gas material interaction chemistry to give a unified framework for the logical development of wearable sensing platforms with many functions. Cross-selectivity, humidity sensitivity, long-term mechanical durability, and scalable production are some of the major issues that still need to be resolved despite significant advancements in room temperature operation and mechanical flexibility. The integration of IoT-enabled data analytics, machine learning to aid in signal classification, and self-powered sensing devices will probably be the main focus in the future. With the goal to assist users to develop scalable, intelligent, and self-monitoring textile-based gas sensing networks, this paper integrates all the opportunities and issues into a single platform.
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