In‐Memory‐Computed Low‐Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide. Issue 7 (16th January 2023)

• Record Type: Journal Article
• Authors: Shin, Wonjun; Kim, Jaehyeon; Jung, Gyuweon; Ju, Suyeon; Park, Sung‐Ho; Jeong, Yujeong; Hong, Seongbin; Koo, Ryun‐Han; Yang, Yeongheon; Kim, Jae‐Joon; Han, Seungwu; Lee, Jong‐Ho
• Is Part Of: Advanced science. Volume 10:Issue 7(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-16
• Subjects: in‐memory‐computing -- low‐frequency noise (LFN) -- selective detection -- tungsten oxide; Science -- Periodicals; 505
• DOI: 10.1002/advs.202205725
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Concerns about indoor and outdoor air quality, industrial gas leaks, and medical diagnostics are driving the demand for high‐performance gas sensors. Owing to their structural variety and large surface area, reducible metal oxides hold great promise for constructing a gas‐sensing system. While many earlier reports have successfully obtained a sufficient response to various types of target gases, the selective detection of target gases remains challenging. In this work, a novel method, low‐frequency noise (LFN) spectroscopy is presented, to achieve selective detection using a single FET‐type gas sensor. The LFN of the sensor is accurately modeled by considering the charge fluctuation in both the sensing material and the FET channel. Exposure to different target gases produces distinct corner frequencies of the power spectral density that can be used to achieve selective detection. In addition, a 3D vertical‐NAND flash array is used with the fast Fourier transform method via in‐memory‐computing, significantly improving the area and power efficiency rate. The proposed system provides a novel and efficient method capable of selectively detecting a target gas using in‐memory‐computed LFN spectroscopy and thus paving the way for the further development in gas sensing systems. Abstract : The fundamental obstacle faced by metal oxide‐based gas sensors is the cross‐sensitivity among different gases. Low‐frequency noise (LFN) spectroscopy in horizontal floating‐gate FET‐type gas sensors is presented to address this issue. The proposed LFN spectroscopy is implemented using in‐memory‐computed FFT computations based on 3D V‐NAND for an area‐ and energy‐efficient operations.