Room temperature multiplexed gas sensing using chemical-sensitive 3.5-nm-thin silicon transistors

• Published in: Science advances Vol. 3; no. 3; p. e1602557
• Main Authors: Fahad, Hossain Mohammad, Shiraki, Hiroshi, Amani, Matin, Zhang, Chuchu, Hebbar, Vivek Srinivas, Gao, Wei, Ota, Hiroki, Hettick, Mark, Kiriya, Daisuke, Chen, Yu-Ze, Chueh, Yu-Lun, Javey, Ali
• Format: Journal Article
• Language: English
• Published: United States AAAS 01.03.2017; American Association for the Advancement of Science
• Subjects: Applied Sciences and Engineering; MATERIALS SCIENCE; SciAdv r-articles; Science & Technology - Other Topics; room-temperature; Multi-gas sensors; nanoscale; silicon; selective; low power; sensitive; IoT
• ISSN: 2375-2548; 2375-2548
• DOI: 10.1126/sciadv.1602557

There is great interest in developing a low-power gas sensing technology that can sensitively and selectively quantify the chemical composition of a target atmosphere. Nanomaterials have emerged as extremely promising candidates for this technology due to their inherent low-dimensional nature and high surface-to-volume ratio. Among these, nanoscale silicon is of great interest because pristine silicon is largely inert on its own in the context of gas sensing, unless functionalized with an appropriate gas-sensitive material. We report a chemical-sensitive field-effect transistor (CS-FET) platform based on 3.5-nm-thin silicon channel transistors. Using industry-compatible processing techniques, the conventional electrically active gate stack is replaced by an ultrathin chemical-sensitive layer that is electrically nonconducting and coupled to the 3.5-nm-thin silicon channel. We demonstrate a low-power, sensitive, and selective multiplexed gas sensing technology using this platform by detecting H S, H , and NO at room temperature for environment, health, and safety in the oil and gas industry, offering significant advantages over existing technology. Moreover, the system described here can be readily integrated with mobile electronics for distributed sensor networks in environmental pollution mapping and personal air-quality monitors.