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Updated: Oct 26, 2026

The Frequency Domain Thermoreflectance Technique for Thermal Property Measurements
Published on: December 5, 2025
Gate-Tunable Single Ag-rGO FET Platform for Room-Temperature Trigas Detection with a CMOS-Compatible PWM Readout
Mayank Kohli1, Nimisha2, Swapnil Sharma1
1Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur 721302, India.
Abstract:
Room-temperature gas sensing requires high sensitivity and selectivity, which FET-based architectures achieve through gate-controlled modulation of surface potential and carrier transport, enabling tunable and efficient chemical transduction. In this work, we introduce a smart trigas sensor capable of selectively detecting three target gasesacetone, formaldehyde, and ammonia at room temperature using a single FET by simply tuning the gate voltage. By leveraging gate-induced modulation, this study demonstrates dynamic control over the interaction between gas molecules and the silver-decorated Reduced Graphene Oxide (Ag-rGO) channel-based gas FET sensor, enabling the individual and selective detection of three distinct gases using the single device. Furthermore, the proposed platform demonstrates distinct cross-sensitivity characteristics, wherein gate-bias modulation enables selective discrimination between formaldehyde, acetone, and ammonia under mixed-gas environments. The device exhibits high detection capability with experimentally estimated limits of detection (LOD) of 158 ppb for acetone, 31 ppb for formaldehyde, and 36 ppb for ammonia, highlighting its potential for low-concentration, room-temperature multigas sensing applications. Beyond material and device-level innovation, a TSMC 180 nm 3.3 V CMOS readout circuit is designed and simulated in Cadence Virtuoso, featuring analogue front-end design for interfacing the proposed gas sensor with a low-power embedded system via PWM signals. The proposed multigas sensor platform and the designed and simulated readout circuit establish a compact and low-power sensing framework, providing a foundation for future studies on breath biomarker analysis and disease-detection applications.
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