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题名

An Intelligent Gas Analysis System Consisting of Sensors and a Neural Network Implemented Using Thin-Film Transistors

作者
DOI
发表日期
2023
会议名称
36th IEEE International Conference on Micro Electro Mechanical Systems (MEMS)
ISSN
1084-6999
ISBN
978-1-6654-9309-3
会议录名称
卷号
2023-January
页码
259-262
会议日期
15-19 Jan. 2023
会议地点
Munich, Germany
出版地
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者
摘要
Described presently is an "intelligent" gas-analysis system consisting of a gas-sensor array and an artificial neural network (ANN) consisting of dual-gate thin-film transistors (TFTs) for in-system inferencing. The micro-hotplates needed for implementing gas sensors with improved specificity are constructed using a silicon-migration technology for the spontaneous creation of a suspended diaphragm. The TFTs deployed in both the array and the network sub-systems are based on semiconducting indium-gallium-zinc oxide. The two sub-systems are packaged on a printed-circuit board. The ANN infers from the raw sensor signals the identity and the concentration of the gas, thus demonstrating the feasibility of building TFT-based intelligent sensor systems.
关键词
学校署名
第一
语种
英语
相关链接[IEEE记录]
收录类别
资助项目
Science and Technology Program of Shenzhen["SGDX20190918105001787","JCYJ20200109140601691"] ; Innovation and Technology Fund[GHP/013/19SZ]
WOS研究方向
Engineering ; Science & Technology - Other Topics
WOS类目
Engineering, Electrical & Electronic ; Engineering, Mechanical ; Nanoscience & Nanotechnology
WOS记录号
WOS:000975359200068
EI入藏号
20231113731676
EI主题词
Chemical sensors ; Gallium compounds ; Gas detectors ; Gases ; II-VI semiconductors ; Monolithic integrated circuits ; Printed circuit boards ; Thin film circuits ; Thin film transistors ; Thin films ; Zinc oxide
EI分类号
Semiconducting Materials:712.1 ; Semiconductor Devices and Integrated Circuits:714.2 ; Chemistry:801 ; Inorganic Compounds:804.2 ; Accidents and Accident Prevention:914.1 ; Special Purpose Instruments:943.3
来源库
IEEE
全文链接https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10052572
引用统计
被引频次[WOS]:2
成果类型会议论文
条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/502067
专题南方科技大学
作者单位
1.Southern University of Science and Technology, China
2.The Hong Kong University of Science and Technology, Hong Kong
第一作者单位南方科技大学
第一作者的第一单位南方科技大学
推荐引用方式
GB/T 7714
Zong Liu,Yushen Hu,Gabriel E. Carranza,et al. An Intelligent Gas Analysis System Consisting of Sensors and a Neural Network Implemented Using Thin-Film Transistors[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:259-262.
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