Gas Adsorption Magnetic Variation Effect Enhanced Room-Temperature NO2 Sensing with Fe3GaTe2

Journal Article (2025)
Author(s)

Jiangnan Chang (South China Normal University)

Minghao Zheng (South China Normal University)

Yancong Feng (South China Normal University)

Min Zeng (South China Normal University, Shanghai Jiao Tong University)

Meijin Zhang (South China Normal University)

Patrick J. French (TU Delft - Bio-Electronics)

Renfeng Dong (South China Normal University, Lingnan Normal University)

Zhipeng Hou (South China Normal University)

Guofu Zhou (South China Normal University)

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Research Group
Bio-Electronics
DOI related publication
https://doi.org/10.1002/adfm.202526844
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Publication Year
2025
Language
English
Research Group
Bio-Electronics
Journal title
Advanced Functional Materials
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Abstract

Achieving high-performance, low-power gas detection at room temperature is critical to safety and energy efficiency, and the key is to deeply explore the interaction mechanisms between sensitive materials and gases. In this work, a magnetic field-assisted strategy is developed to achieve high-performance, low-power NO2 sensing with the Fe3GaTe2 at room temperature. Fe3GaTe2 nanoflakes are obtained from green solvents using ultrasound-assisted liquid phase exfoliation. The experimental results confirming that the Fe3GaTe2 nanoflakes sensor demonstrates an excellent response (S = 16 for 10 ppm NO2, 1.4 times higher than that without magnetic field), a lower actual detection limit (50 ppb) and a low-power consumption (0.25 nW) under 21 mT magnetic field at room temperature. Combining theoretical calculations and quasi in situ XPS, it is indicated that Fe is the main electron donor and serves as the main response site for NO2. Magnetic field-enhancing effect for gas sensing is revealed via comparing the in situ field-dependent magnetization curves of Fe3GaTe2 in air and NO2. It is found for the first time that the enhancement of gas sensing is mainly attributed to the gas adsorption magnetic variation effect (GAMVE) which generates in NO2. This study provides a strategy of GAMVE-driven sensing for next-generation gas sensors.

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