论文部分内容阅读
设计了一种新型基于声表面波技术的气体传感器,理论分析了三维纳米线结构的比表面积大、灵敏度高等优点,采用具备高Q值和低插损的谐振型声表面波器件结构,制备了三维敏感膜结构的声表面波气体传感器。在此基础上,为提高吸附效应,对三维纳米线簇进行了修饰改进。通过将沙林气和芥子气注入放置了声表面波的气体传感器密闭腔体内,经过神经网络识别系统进行定性识别。实验结果表明,基于修饰改进后的纳米线簇敏感膜制备的声表面波气体传感器对给定毒气混合气体的整理识别率大于90%,能够满足通用的毒气定性检测要求。并且三维纳米声表面波气敏传感器的灵敏度和响应速度优于传统的传感装置,在识别系统加大样本数据量时,能够进一步提高识别精度。
A new type of gas sensor based on SAW technology is designed. The advantages of high specific surface area and high sensitivity of 3D nanowire structure are theoretically analyzed. The resonant SAW device structure with high Q value and low insertion loss is used to prepare Surface acoustic wave sensor with 3D sensitive membrane structure. On this basis, to improve the adsorption effect, three-dimensional nanowire clusters have been modified to improve. By injecting sarin gas and mustard gas into the sealed chamber of a gas sensor with surface acoustic wave, the neural network identification system is used for qualitative identification. The experimental results show that the surface acoustic wave sensor based on the modified nanowire-sensing film has a recognition rate of more than 90% for a given gas mixture, which can meet the requirements of qualitative detection of toxic gas. And three-dimensional nano-SAW gas sensor sensitivity and response speed than the traditional sensing device, the identification system to increase the amount of sample data, to further improve the recognition accuracy.