Accelerating photocarrier dynamics by constructing 2D-3D homojunction toward boosting self-powered UV photodetection

Heterojunction structures are favored for constructing photoelectrochemical ultraviolet photodetectors (PEC UV PDs), whereas lattice mismatches impede their optoelectronic performance. This work presents a novel homojunction consisting of two-dimensional (2D) In<sub>2</sub>O<sub>3</sub> nanosheets (NS) and three-dimensional (3D) In<sub>2</sub>O<sub>3</sub> microcubes (MC) with a suitable energy band alignment. 2D In<sub>2</sub>O<sub>3</sub> NS not only shows an enlarged bandgap due to the quantum confinement effect but also effectively upshifts the conductive band and Fermi level stemming from the oxygen vacancy demonstrated by the theoretical simulation and experimental results. The photogenerated carrier dynamic of In<sub>2</sub>O<sub>3</sub> photoanodes is boosted by the 2D-3D homojunction with a built-in electric field and more electrochemically active sites, leading to higher photogenerated carrier separation efficiency, faster interfacial charge transfer, and better self-powered capability. The In<sub>2</sub>O<sub>3</sub> 2D-3D homojunction PEC UV PDs exhibit outstanding self-powered deep-UV photoresponse at 0 V, with an ultrahigh responsivity of 316.5 mA/W for 254 nm light, a fast response speed of 15/15 ms, high detectivity of 1.12 × 10<sup>12</sup> Jones, and an outstanding UV-vis rejection ratio of 1507, surpassing most recorded PEC UV PDs. This work demonstrates the pivotal role of morphology-controlled homojunction in modulating photogenerated carrier dynamics and offers a new strategy for designing high-performance PEC devices.

Authors

Publication Details

Journal
Nano Research
Published
2025-06-30
DOI
https://doi.org/10.26599/nr.2025.94907728
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Accelerating photocarrier dynamics by constructing 2D-3D homojunction toward boosting self-powered UV photodetection

Zhengguang Shi, Wei Feng, PingAn Hu, Xinghan Li et al.
Nano Research
Neural Networks and Reservoir Computing
article

Accelerating photocarrier dynamics by constructing 2D-3D homojunction toward boosting self-powered UV photodetection

Zhengguang Shi, Wei Feng, PingAn Hu, Xinghan Li, Hsu‐Sheng Tsai, Zhitao Shao, Sha Zhao, Wenhui Li, Jiaming Liu, Nana Zhang, Xinyu Gao, Junxin Zhou, Ruyu Sun, Yuan Zhang
article en

Abstract

Heterojunction structures are favored for constructing photoelectrochemical ultraviolet photodetectors (PEC UV PDs), whereas lattice mismatches impede their optoelectronic performance. This work presents a novel homojunction consisting of two-dimensional (2D) In<sub>2</sub>O<sub>3</sub> nanosheets (NS) and three-dimensional (3D) In<sub>2</sub>O<sub>3</sub> microcubes (MC) with a suitable energy band alignment. 2D In<sub>2</sub>O<sub>3</sub> NS not only shows an enlarged bandgap due to the quantum confinement effect but also effectively upshifts the conductive band and Fermi level stemming from the oxygen vacancy demonstrated by the theoretical simulation and experimental results. The photogenerated carrier dynamic of In<sub>2</sub>O<sub>3</sub> photoanodes is boosted by the 2D-3D homojunction with a built-in electric field and more electrochemically active sites, leading to higher photogenerated carrier separation efficiency, faster interfacial charge transfer, and better self-powered capability. The In<sub>2</sub>O<sub>3</sub> 2D-3D homojunction PEC UV PDs exhibit outstanding self-powered deep-UV photoresponse at 0 V, with an ultrahigh responsivity of 316.5 mA/W for 254 nm light, a fast response speed of 15/15 ms, high detectivity of 1.12 × 10<sup>12</sup> Jones, and an outstanding UV-vis rejection ratio of 1507, surpassing most recorded PEC UV PDs. This work demonstrates the pivotal role of morphology-controlled homojunction in modulating photogenerated carrier dynamics and offers a new strategy for designing high-performance PEC devices.

Nano ResearchVol. 18(12)
Natural Science Foundation of Heilongjiang Province
Climate action
Openalex Percentile: Top 92%
Neural Networks and Reservoir Computing
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