Visible Light-Modulated Low-Power Resistive Switching in Perovskite Nickelate Photovoltaic Heterostructures
The increasing demand for information storage makes the development of advanced materials and regulation strategies urgent, integrating low-power consumption with a rapid resistive switching behavior. Perovskite nickelates, leveraging their unique metal-insulator transition, emerge as an ideal material platform for resistive switching applications. However, traditional modulation strategies (such as strain, electric fields, and ionic liquids) remain plagued by energy inefficiency and response hysteresis. Here, we demonstrate a visible light-modulated metal-insulator transition in NdNiO<sub>3</sub> photovoltaic heterostructures, achieving 2 orders of magnitude resistivity switching under low-intensity 20 mW·cm<sup>-2</sup> (0.2 sun) illumination with transient time. The photoinduced electron doping makes Ni 3d-orbital reconstruction to present the metallic behavior, where its upper Hubbard band broadens and is below the Fermi level. Nevertheless, these charged V<sub>O</sub> existing in the NdNiO<sub>3-δ</sub> interlayer would serve as charge recombination centers and severe electron-hole pair quenching, thereby aggravating the insulating behavior. By integrating multilevel resistive switching tunability (changing light intensity or temperature) and high-fidelity state reproducibility, our work establishes NdNiO<sub>3</sub> photovoltaic heterostructures to provide a new research platform for low-power optoelectronic memory and neuromorphic computing.
Authors
- Bin Peng (ORCID: https://orcid.org/0000-0002-3501-722X)
- Zicong Zhou (ORCID: https://orcid.org/0009-0005-3985-1309)
- J. Q. Wang
- Yifan Zhao (ORCID: https://orcid.org/0000-0001-5634-5348)
- Yufei Yao
- Pei Li (ORCID: https://orcid.org/0000-0001-8699-8825)
- Guannan Yang
- Zhengwei Tao
- Guohua Dong
- Ming Liu
- Xuhui Zhu
- Meng Zhao
- Yanan Zhao
Institutions
- Ministry of Education (IR)
- Physical Measurement Laboratory (US)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- ACS Applied Materials & Interfaces
- Published
- 2026-01-22
- DOI
- https://doi.org/10.1021/acsami.5c15606
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00