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2D MXenes are highly attractive for fabricating high-precision gas sensors operated at room temperature (RT) due to their high surface-to-volume ratio. However, the limited selectivity and low sensitivity are still long-standing challenges for their further applications. Herein, the self-assembly of 0D–2D heterostructure for highly sensitive NO2 detection was achieved by integrating ZnO nanoparticles on Ti3C2Tx MXene-derived TiO2 nanosheets (designated as ZnO@M−TiO2). ZnO nanoparticles can not only act as spacers to prevent the restacking of M−TiO2 nanosheets and ensure effective transfer for gas molecules, but also enhance the sensitivity of the sensor the through trapping effect on electrons. Meanwhile, M−TiO2 nanosheets facilitate gas diffusion for rapid sensor response. Benefiting from the synergistic effect of individual components, the ZnO@M−TiO2 0D–2D heterostructure-based sensors revealed remarkable sensitivity and excellent selectivity to low concentration NO2 at RT. This work may facilitate the sensing application of MXene derivative and provide a new avenue for the development of high-performance gas sensors in safety assurance and environmental monitoring.

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Publication history

Received: 03 December 2022
Accepted: 13 February 2023
Published: 24 February 2023
Issue date: December 2023

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© 2023 Chongqing University.

Acknowledgements

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (No. 52103308), the Natural Science Foundation of Jiangsu Province of China (No. BK20210826), Outstanding Youth Foundation of Jiangsu Province of China (No. BK20211548), National Key Research and Development Program of China (No. 2017YFE0115900), Innovative Science and Technology Platform Project of Cooperation between Yangzhou City and Yangzhou University (No. YZ2020266), Lvyang Jinfeng Plan for Excellent Doctor of Yangzhou City, Special Funds for Self-Made Experimental Equipment of Yangzhou University, and the Doctor of Suzhou University Scientific Research Foundation Project (No. 2022BSK003).

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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