Unveiling the invisible: Polarization-sensitive ferroelectric photomemristors for enhanced image recognition
Photoresponsive memristors (i.e., photomemristors) have been recently highly regarded to tackle data latency and energy consumption challenges in conventional Von Neumann architecture-based image recognition systems. However, their efficacy in recognizing low-contrast images is quite limited, and while preprocessing algorithms are usually employed to enhance these images, which naturally introduce delays that hinder real-time recognition in complex conditions. To address this challenge, here we present a self-driven polarization-sensitive ferroelectric photomemristor inspired by advanced biological systems. The proposed prototype device is engineered to extract image polarization information, enabling real-time and in-situ enhanced image recognition and classification capabilities. By combining the anisotropic optical feature of the two-dimensional material (ReSe<sub>2</sub>) and ferroelectric polarization of single-crystalline Diisopropylammonium Bromide (DIPAB) thin film, tunable and self-driven polarized responsiveness with intelligence was achieved. With remarkable optoelectronic synaptic characteristics of the fabricated device, a significant enhancement was demonstrated in recognition probability—averaging an impressive 85.9% for low-contrast scenarios, in contrast to the mere 47.5% exhibited by traditional photomemristors. This holds substantial implications for the detection and recognition of subtle information in diverse scenes such as autonomous driving, medical imaging, and astronomical observation.
Authors
- Chunxiao Cong (ORCID: https://orcid.org/0000-0001-9786-825X)
- Zhijun Qiu (ORCID: https://orcid.org/0000-0002-7089-8114)
- Xiaofei Yue
- Dacheng Xia
- Laigui Hu (ORCID: https://orcid.org/0000-0003-1995-1423)
- Shuwen Shen
- Jiao Wang (ORCID: https://orcid.org/0000-0001-7640-3947)
- Ran Liu (ORCID: https://orcid.org/0000-0002-1657-9542)
- Chenxu Sheng
- Shoaib Awan (ORCID: https://orcid.org/0009-0008-2222-989X)
Publication Details
- Journal
- Nano Research
- Published
- 2025-09-02
- DOI
- https://doi.org/10.26599/nr.2025.94908019
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China