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• W4360992743 abstract "Recent studies on nanostructured MoS2 show promising performance in the detection of reducing gases like ammonia (NH3). However, this material in the pristine form possesses limitations in terms of response, recovery, and repeatability over a long duration of time. Several attempts have been made to overcome these shortcomings by modifying it chemically to make a hybrid form or direct doping with other atoms. In this work, we demonstrate that suitable defect engineering of 3D nanostructured MoS2 induced by a low energy ion beam can lead to a significantly improved performance of sensing NH3 compared to the as-prepared one. Significant decreases in response and recovery times have been demonstrated at room temperature for the modified MoS2 compared to its pristine form, which shows its best response only at a higher temperature of about 200 °C. A 3D nanoflower-like structure of MoS2 was synthesized hydrothermally, which was coated on substrates, and then irradiated with 5 keV argon ions at different doses. While the ion beam-induced morphological modifications are observed via electron microscopic study, the surface defects are apparent in X-ray diffraction, Raman scattering, and X-ray spectroscopic studies. The ion beam-modified MoS2 shows a higher electrical conductivity and water-repelling nature compared to the pristine one, which are complementary properties for better sensing performance. While Monte Carlo-based 3D ion-solid interaction simulation was used to support the morphological modifications and defect developments after ion irradiation, the sensing mechanism and change in conductivity were successfully explained using density functional theory-based simulations." @default.
• W4360992743 created "2023-03-30" @default.
• W4360992743 creator A5043740286 @default.
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• W4360992743 date "2023-03-27" @default.
• W4360992743 modified "2023-09-27" @default.
• W4360992743 title "Defect-Engineered 3D Nanostructured MoS₂ for Detection of Ammonia Gas at Room Temperature" @default.
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• W4360992743 doi "https://doi.org/10.1021/acsanm.2c05361" @default.
• W4360992743 hasPublicationYear "2023" @default.
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