Electrical Kinetic Model of a Hydroxylated Graphene FET Gas Sensor
Graphene transistor sensors, with advantages such as facile surface functionalization and high sensitivity, have gained extensive research interest in gas detection applications. This study fabricated back-gated graphene transistors and employed a hydroxylation scheme for the surface functionalization of graphene. On the basis of the interaction mechanisms between gas molecules and graphene's electrical properties, a compact electrical kinetics model considering the gas-solid surface reaction of graphene transistors is proposed. The model can accurately predict the electrical kinetic performance and can be used to optimize sensor characteristics. The bias condition of a higher response can be rapidly determined. In addition, the density of hydroxyl groups on graphene is revealed to be the direction of improvement and a key factor of response. Hence, the gas detection capacity of sensors with varying densities of hydroxyl groups was assessed concerning ammonia gas, and design technology co-optimization (DTCO) is realized. Measurement results show that the sensor with 70 s of hydroxylation time has a 7.7% response under 22 ppm ammonia gas.
Authors
- Zhengyi Cao
- Kai Kang (ORCID: https://orcid.org/0000-0002-8878-2080)
- Huihua Liu (ORCID: https://orcid.org/0000-0002-9146-7620)
- Yunqiu Wu (ORCID: https://orcid.org/0000-0001-6856-7431)
- Zegao Wang (ORCID: https://orcid.org/0000-0002-0033-6538)
- Xiaowen Gu (ORCID: https://orcid.org/0000-0002-2237-6231)
- Chenxi Zhao (ORCID: https://orcid.org/0000-0001-7166-2755)
- Yiming Yu (ORCID: https://orcid.org/0000-0003-0616-2994)
- Xi Fan (ORCID: https://orcid.org/0000-0003-4280-1386)
- Jie Chen (ORCID: https://orcid.org/0000-0003-0724-6911)
- Yuehang Xu (ORCID: https://orcid.org/0000-0003-1706-2681)
- Ru Bai (ORCID: https://orcid.org/0000-0003-4676-6047)
- Tao Xu (ORCID: https://orcid.org/0009-0009-2070-9061)
- Minmin Zhao (ORCID: https://orcid.org/0009-0005-1286-0440)
- Qi Tang
Institutions
- University of Electronic Science and Technology of China (CN)
- Sichuan University (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2024-09-16
- DOI
- https://doi.org/10.1021/acssensors.4c01322
- Citations
- 4
- Primary Topic
- Graphene research and applications
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Sichuan Province