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Published on: August 29, 2025
Edge-Enriched Metal-Organic Framework Integrated with a Gate-Sensitive Field-Effect Transistor for Highly Sensitive
Jiaxin Liu1, Zhe Wang1, Chengxu Lin1
1State key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, P.R. China.
This study introduces an ultrafast metal-organic framework (MOF) gas sensor for noninvasive diabetes diagnosis using exhaled acetone. The portable device offers rapid, reliable breath analysis for early detection.
Area of Science:
- Materials Science
- Chemical Sensing
- Biomedical Engineering
Background:
- Exhaled acetone is a key biomarker for diabetes detection.
- Current acetone sensors lack portability and speed.
- Metal-organic frameworks (MOFs) offer potential but need performance enhancement.
Purpose of the Study:
- To develop an ultrafast, portable gas sensor for noninvasive acetone detection.
- To improve MOF-based sensor response time and stability.
- To enable real-time diabetes diagnosis via breath analysis.
Main Methods:
- Fabrication of a gate-sensitive field-effect transistor (GS-FET) gas sensor.
- Functionalization with a solvent-modified MOF for enhanced acetone adsorption.
- Integration with a portable, mobile-linked device for breath analysis.
- Development of a data analysis algorithm for rapid concentration prediction.
Main Results:
- Achieved a sub-500 ppb detection limit for acetone.
- Demonstrated ultrafast response time with real-time breath analysis capability.
- Developed a predictive algorithm for reliable acetone concentration assessment within 5 seconds.
- Confirmed enhanced adsorption activity via density functional theory (DFT) calculations.
Conclusions:
- The MOF-functionalized GS-FET sensor provides a practical platform for ultrafast, noninvasive diabetes diagnosis.
- The developed sensor and algorithm offer high performance and reliability for breath analysis.
- This work advances MOF-based gas sensing for medical diagnostics and highlights potential for high-performance sensor development.
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