Research on heterogeneous composite thin film ultraviolet detector based on self-depletion effect

Jiaxin Li; Yue Zhu; Weijia Niu; Ai Ai; Dongdong Liu; Shiyi Zhang; Qing Ma; Wenxuan Bao; Chenzao Lin

doi:10.1117/12.2675357

25 May 2023 Research on heterogeneous composite thin film ultraviolet detector based on self-depletion effect

Jiaxin Li, Yue Zhu, Weijia Niu, Ai Ai, Dongdong Liu, Shiyi Zhang, Qing Ma, Wenxuan Bao, Chenzao Lin

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 126363O (2023) https://doi.org/10.1117/12.2675357
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

In this paper, a TiO₂/NiO heterogeneous composite thin film ultraviolet detector based on the dark state self-depletion effect was designed and fabricated. The N-type TiO₂ film is prepared by the sol-gel method, and P-type NiO thin films and Ni/Au alloy electrodes are simultaneously prepared by a unique one-step oxidation method. Compared with devices based on a single thin film, the dark current of heterogeneous thin film devices is greatly improved, and performances such as responsivity and response/recovery speed are also improved. The dark current of the device with the best comprehensive performance is only 0.033 nA under 6 V bias, the peak spectral response reaches 181.9 A/W at 280 nm wavelength, and the response recovery time is 717 ms and 598 ms, respectively. This research shows that the heterogeneous composite thin-film ultraviolet detector based on the self-depletion effect and other mechanisms has significantly improved comprehensive performance and has more application potential.

Citation Download Citation

Jiaxin Li, Yue Zhu, Weijia Niu, Ai Ai, Dongdong Liu, Shiyi Zhang, Qing Ma, Wenxuan Bao, and Chenzao Lin "Research on heterogeneous composite thin film ultraviolet detector based on self-depletion effect", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 126363O (25 May 2023); https://doi.org/10.1117/12.2675357

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