Low-Power Consumption IGZO Memristor-Based Gas Sensor Embedded in an Internet of Things Monitoring System for Isopropanol Alcohol Gas.

Internet of Things gas sensor isopropanol alcohol gas memristor monitoring

Journal

Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903

Informations de publication

Date de publication:
29 Dec 2023
Historique:
received: 21 11 2023
revised: 27 12 2023
accepted: 28 12 2023
medline: 23 1 2024
pubmed: 23 1 2024
entrez: 23 1 2024
Statut: epublish

Résumé

Low-power-consumption gas sensors are crucial for diverse applications, including environmental monitoring and portable Internet of Things (IoT) systems. However, the desorption and adsorption characteristics of conventional metal oxide-based gas sensors require supplementary equipment, such as heaters, which is not optimal for low-power IoT monitoring systems. Memristor-based sensors (gasistors) have been investigated as innovative gas sensors owing to their advantages, including high response, low power consumption, and room-temperature (RT) operation. Based on IGZO, the proposed isopropanol alcohol (IPA) gas sensor demonstrates a detection speed of 105 s and a high response of 55.15 for 50 ppm of IPA gas at RT. Moreover, rapid recovery to the initial state was achievable in 50 μs using pulsed voltage and without gas purging. Finally, a low-power circuit module was integrated for wireless signal transmission and processing to ensure IoT compatibility. The stability of sensing results from gasistors based on IGZO has been demonstrated, even when integrated into IoT systems. This enables energy-efficient gas analysis and real-time monitoring at ~0.34 mW, supporting recovery via pulse bias. This research offers practical insights into IoT gas detection, presenting a wireless sensing system for sensitive, low-powered sensors.

Identifiants

pubmed: 38258196
pii: mi15010077
doi: 10.3390/mi15010077
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Korea Institute for Advancement of Technology
ID : P0020966
Organisme : National Research Foundation of Korea
ID : 2022R1F1A1060655
Organisme : the Nano-Material Technology Development Program, NRF, Ministry of Science, ICT, and Future Planning
ID : 2009-0082580

Auteurs

Myoungsu Chae (M)

Department of Semiconductor Systems Engineering, Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.

Doowon Lee (D)

Department of Semiconductor Systems Engineering, Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.
IHP GmbH-Leibniz Institute for Innovative Microelectronics, Im Technologiepark 25, 15236 Frankfurt (Oder), Germany.

Hee-Dong Kim (HD)

Department of Semiconductor Systems Engineering, Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.

Classifications MeSH