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Xu B, Chang H, Yang G, Xu Z, Li J, Gu Z, Li J. An integrated wearable sticker based on extended-gate AlGaN/GaN high electron mobility transistors for real-time cortisol detection in human sweat. Analyst 2024; 149:958-967. [PMID: 38197472 DOI: 10.1039/d3an02115g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Cortisol hormone imbalances can be detected through non-invasive sweat monitoring using field-effect transistor (FET) biosensors, which provide rapid and sensitive detection. However, challenges like skin compatibility and integration with sweat collection have hindered FET biosensors as wearable sensing platforms. In this study, we present an integrated wearable sticker for real-time cortisol detection based on an extended-gate AlGaN/GaN high electron mobility transistor (HEMT) combined with a soft bottom substrate and flexible channel for sweat collection. The developed devices exhibit excellent linearity (R2 = 0.990) and a high sensitivity of 1.245 μA dec-1 for cortisol sensing from 1 nM to 100 μM in high-ionic-strength solution, with successful cortisol detection demonstrated using authentic human sweat samples. Additionally, the chip's microminiature design effectively reduces bending impact during the wearable process of traditional soft binding sweat sensors. The extendedgate structure design of the HEMT chip enhances both width-to-length ratio and active sensing area, resulting in an exceptionally low detection limit of 100 fM. Futhermore, due to GaN material's inherent stability, this device exhibits long-term stability with sustained performance within a certain attenuation range even after 60 days. These stickers possess small, lightweight, and portable features that enable real-time cortisol detection within 5 minutes through direct sweat collection. The application of this technology holds great potential in the field of personal health management, facilitating users to conveniently monitor their mental and physical conditions.
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Affiliation(s)
- Boxuan Xu
- The College of Materials Science and Engineering, Shanghai University, Shanghai, 200072, People's Republic of China.
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215125, People's Republic of China.
| | - Hui Chang
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215125, People's Republic of China.
- School of Nano Technology and Nano Bionics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
| | - Guo Yang
- School of Electrical and Mechanical Engineering, Changchun University of Science and Technology, Changchun 130022, China
| | - Zhan Xu
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215125, People's Republic of China.
- School of Nano Technology and Nano Bionics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
| | - Jun Li
- The College of Materials Science and Engineering, Shanghai University, Shanghai, 200072, People's Republic of China.
| | - Zhiqi Gu
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215125, People's Republic of China.
| | - Jiadong Li
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou 215125, People's Republic of China.
- School of Nano Technology and Nano Bionics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
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