Li Xingxing, Fu Li, Karimi-Maleh Hassan, Chen Fei, Zhao Shichao
Key Laboratory of Novel Materials for Sensor of Zhejiang Province, College of Materials and Environmental Engineering, Hangzhou Dianzi University, Hangzhou, 310018, PR China.
School of Resources and Environment, University of Electronic Science and Technology of China, 611731, Chengdu, PR China.
Heliyon. 2024 Mar 13;10(6):e27740. doi: 10.1016/j.heliyon.2024.e27740. eCollection 2024 Mar 30.
This review critically examines the progress and challenges in the field of nanostructured tungsten oxide (WO) gas sensors. It delves into the significant advancements achieved through nanostructuring and composite formation of WO, which have markedly improved sensor sensitivity for gases like NO, NH, and VOCs, achieving detection limits in the ppb range. The review systematically explores various innovative approaches, such as doping WO with transition metals, creating heterojunctions with materials like CuO and graphene, and employing machine learning models to optimize sensor configurations. The challenges facing WO sensors are also thoroughly examined. Key issues include cross-sensitivity to different gases, particularly at higher temperatures, and long-term stability affected by factors like grain growth and volatility of dopants. The review assesses potential solutions to these challenges, including statistical analysis of sensor arrays, surface functionalization, and the use of novel nanostructures for enhanced performance and selectivity. In addition, the review discusses the impact of ambient humidity on sensor performance and the current strategies to mitigate it, such as composite materials with humidity shielding effects and surface functionalization with hydrophobic groups. The need for high operating temperatures, leading to higher power consumption, is also addressed, along with possible solutions like the use of advanced materials and new transduction principles to lower temperature requirements. The review concludes by highlighting the necessity for a multidisciplinary approach in future research. This approach should combine materials synthesis, device engineering, and data science to develop the next generation of WO sensors with enhanced sensitivity, ultrafast response rates, and improved portability. The integration of machine learning and IoT connectivity is posited as a key driver for new applications in areas like personal exposure monitoring, wearable diagnostics, and smart city networks, underlining WO's potential as a robust gas sensing material in future technological advancements.
本综述批判性地审视了纳米结构氧化钨(WO)气体传感器领域的进展与挑战。它深入探讨了通过WO的纳米结构化和复合材料形成所取得的重大进展,这些进展显著提高了对NO、NH和挥发性有机化合物(VOCs)等气体的传感器灵敏度,实现了ppb范围内的检测限。该综述系统地探索了各种创新方法,例如用过渡金属掺杂WO、与CuO和石墨烯等材料形成异质结,以及采用机器学习模型来优化传感器配置。同时也对WO传感器面临的挑战进行了全面审视。关键问题包括对不同气体的交叉敏感性,尤其是在较高温度下,以及受晶粒生长和掺杂剂挥发性等因素影响的长期稳定性。该综述评估了应对这些挑战的潜在解决方案,包括传感器阵列的统计分析、表面功能化以及使用新型纳米结构来提高性能和选择性。此外,该综述还讨论了环境湿度对传感器性能的影响以及当前减轻这种影响的策略,例如具有湿度屏蔽效应的复合材料和用疏水基团进行表面功能化。还提到了高工作温度导致高功耗的问题以及可能的解决方案,如使用先进材料和新的传感原理来降低温度要求。综述最后强调了未来研究采用多学科方法的必要性。这种方法应结合材料合成、器件工程和数据科学,以开发出具有更高灵敏度、超快响应速率和更好便携性的下一代WO传感器。机器学习和物联网连接的整合被认为是个人暴露监测、可穿戴诊断和智能城市网络等领域新应用的关键驱动力,突显了WO作为未来技术进步中一种强大气体传感材料的潜力。