Detection and recognition of toluene and butanone in mixture based on SnO2 sensor via dynamic transient and steady-state response analysis in jump heating voltage mode

瞬态响应 响应时间 稳态(化学) 瞬态(计算机编程) 响应分析 控制理论(社会学) 频率响应 计算机科学 材料科学 生物系统 化学 工程类 人工智能 物理化学 计算机图形学(图像) 控制(管理) 电气工程 操作系统 结构工程 生物
作者
Hanyang Ji,Yang Liu,Renze Zhang,Zhenyu Yuan,Fanli Meng
出处
期刊:Sensors and Actuators B-chemical [Elsevier BV]
卷期号:376: 132969-132969 被引量:22
标识
DOI:10.1016/j.snb.2022.132969
摘要

The temperature modulation method is used to improve the selectivity of sensor, but there are still some deficiencies in the gas mixture recognition. The dynamic response law is insufficient understood because the dynamic response process itself is a complex change and there are some factors such as competition or suppression among multi-gases. This paper solves this problem by decomposing dynamic response and mapping static response. Based on the grain boundary barrier model, dynamic response is divided into dynamic temperature response and dynamic gas-sensing response. The dynamic temperature response is unaffected by the target gas and can be detected directly. Dynamic gas-sensing response cannot be detected directly but can be mapped through static responses. Therefore, this paper uses static response to grasp the dynamic response law to directionally optimize the experimental scheme. Dynamic transient response and dynamic steady-state response are analyzed one by one to discuss the role of dynamic response law in gas mixture recognition. High recognition rate is achieved in KNN recognition due to the selection of PCA dimensionality reduction results of the second dynamic transient response and dynamic steady-state response value. The study of the dynamic response law provides a new avenue for the recognition of gas mixture.
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