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Hexagonal-Boron nitride nanotubes (h-BN) decorated with transition metals have been widely studied due to their enhanced physicochemical properties. In this paper, Pt cluster-modified h-BN is proposed as a sensitive material for a novel gas sensor for the online malfunction monitoring of oil-immersed transformers. The inner oil is ultimately decomposed to various gases during the long-term use of oil-immersed transformers. Exposure to excessively high temperatures produces the alkanes CH 4  and C 2 H 6 , whereas different degrees of discharge generate H 2  and C 2 H 2 . Therefore, the identification of H 2 , CH 4,  and C 2 H 2  gas efficiently measures the quality of transformers. Based on the density functional theory, the most stable h-BN doped with 1–4 Pt atoms is employed to simulate its adsorption performance and response behavior to these typical gases. The adsorption energy, charge transfer, total density of states, projected density of states, and orbital theory of these adsorption systems are analyzed and the results show high consistency. The adsorption ability for these decomposition components are ordered as follows: C 2 H 2  > H 2  > CH 4 . Pt cluster-modified h-BN shows good sensitivity to C 2 H 2 , H 2 , with decreasing conductivity in each system, but is insensitive to CH 4  due to its weak physical sorption. The conductivity change of Pt n -h-BN is considerably larger upon H 2  than that upon C 2 H 2 , but is negligible upon CH 4 . Our calculations suggest that Pt cluster modified h-BN can be employed in transformers to estimate their operation status.

Pt Cluster Modified h-BN for Gas Sensing and Adsorption of Dissolved Gases in Transformer Oil: A Density Functional Theory Study