Li Long, Zhou Licheng, Hu Zhixiang, Li Tiankun, Chen Bingbing, Li Hua-Yao, Liu Huan
School of Integrated Circuits, School of Optical and Electronic Information, Wuhan National Laboratory for Optoelectronics, Optics Valley Laboratory, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei 430074, P. R. China.
Wenzhou Advanced Manufacturing Institute, Huazhong University of Science and Technology, 1085 Meiquan Road, Wenzhou, Zhejiang 325035, P. R. China.
ACS Appl Mater Interfaces. 2023 Mar 29;15(12):15707-15720. doi: 10.1021/acsami.2c23088. Epub 2023 Mar 16.
The analysis of exhaled breath has opened up new exciting avenues in medical diagnostics, sleep monitoring, and drunk driving detection. Nevertheless, the detection accuracy is greatly affected due to high humidity in the exhaled breath. Here, we propose a regulation method to solve the problem of humidity adaptability in the ethanol-monitoring process by building a heterojunction and hollow-out nanostructure. Therefore, large specific surface area hollow-out FeO-loaded NiO heterojunction nanorods assembled by porous ultrathin nanosheets were prepared by a well-tailored interface reaction. The excellent response (51.2 toward 10 ppm ethanol at 80% relative humidity) and selectivity to ethanol under high relative humidity with a lower operating temperature (150 °C) were obtained, and the detection limit was as low as 0.5 ppb with excellent long-term stability. The superior gas-sensing performance was attributed to the high surface activity of the heterojunction and hollow-out nanostructure. More importantly, GC-MS, diffuse reflectance Fourier transform infrared spectroscopy, and DFT were utilized to analyze the mechanisms of heterojunction sensitization, ethanol-sensing reaction, and high-humidity adaptability. Our integrated low-power MEMS Internet of Things (IoT) system based on FeO@NiO successfully demonstrates the functional verification of ethanol detection in human exhalation, and the integrated voice alarm and IoT positioning functions are expected to solve the problem of real-time monitoring and rapid initial screening of drunk driving. Overall, this novel method plays a vital role in areas such as control of material morphology and composition, breath analysis, gas-sensing mechanism research, and artificial olfaction.
呼出气体分析在医学诊断、睡眠监测和酒驾检测等领域开辟了令人兴奋的新途径。然而，由于呼出气体中的高湿度，检测准确性受到很大影响。在此，我们提出一种调节方法，通过构建异质结和中空纳米结构来解决乙醇监测过程中的湿度适应性问题。因此，通过精心设计的界面反应制备了由多孔超薄纳米片组装而成的大比表面积中空负载FeO的NiO异质结纳米棒。该材料在相对湿度80%、较低工作温度（150℃）下对乙醇具有优异的响应（对10 ppm乙醇的响应为51.2）和选择性，检测限低至0.5 ppb，且具有出色的长期稳定性。优异的气敏性能归因于异质结和中空纳米结构的高表面活性。更重要的是，利用气相色谱 - 质谱联用仪、漫反射傅里叶变换红外光谱和密度泛函理论分析了异质结敏化、乙醇传感反应和高湿度适应性的机制。我们基于FeO@NiO的集成低功耗微机电系统物联网（IoT）系统成功展示了人体呼出气体中乙醇检测的功能验证，并且集成的语音报警和物联网定位功能有望解决酒驾实时监测和快速初步筛查的问题。总体而言，这种新方法在材料形态和成分控制、呼气分析、气敏机制研究和人工嗅觉等领域发挥着至关重要的作用。
