High Photoresponsivity and Fast Response Speed Ferroelectric Photomemristor for Artificial Visual System Application
Abstract Ferroelectric photoelectric devices show promising applications in artificial vision systems. However, this type of devices used in artificial vision systems exhibits low photoresponsivity and this limited cyclability of photocurrents, which hinders the progress of artificial vision systems. In this study, an artificial vision system is constructed with high photoresponsivity, fast photoresponse speed, and high read/write speed based on the Pd/PbZr 0.4 Ti 0.6 O 3 /La 0.3 Sr 0.7 MnO 3 /LaAlO 3 ferroelectric photomemristor. The high optical response (18.86 nanoamperes) and read/write speeds (50 nanoseconds) of the device significantly improve the robustness and speed of the neuromorphic visual system while reducing power consumption for recognition. The artificial vision system developed in this study provides excellent real‐time image processing capabilities, including edge detection and classification with 100% accuracy for musical key patterns, and it is expected to offer great potential for the development of high‐performance self‐powered artificial vision systems.
Authors
- Jikang Xu (ORCID: https://orcid.org/0000-0002-3751-0632)
- Zhenqiang Guo (ORCID: https://orcid.org/0000-0003-1751-991X)
- Xiaobing Yan (ORCID: https://orcid.org/0000-0002-3266-515X)
- Jiameng Sun
- Yinxing Zhang (ORCID: https://orcid.org/0000-0001-9598-2542)
- Z. Wang (ORCID: https://orcid.org/0009-0002-1377-6580)
- Yifei Pei (ORCID: https://orcid.org/0000-0002-4981-3980)
- Weifeng Zhang
- Yousef Faraj (ORCID: https://orcid.org/0000-0003-4418-3649)
- Zhen Zhao (ORCID: https://orcid.org/0000-0003-3650-0747)
- Yongrui Wang (ORCID: https://orcid.org/0009-0006-3576-5742)
- Jiacheng Wang (ORCID: https://orcid.org/0000-0003-1252-8761)
- Jingsheng Chen (ORCID: https://orcid.org/0000-0003-3188-2803)
- Jianning Wang (ORCID: https://orcid.org/0000-0001-5911-7834)
- Changliang Li (ORCID: https://orcid.org/0000-0003-2306-6048)
- Shu‐Shen Li (ORCID: https://orcid.org/0009-0005-3744-2085)
- Haozhen Cui
- Pengli Zhao
Institutions
- University of Chester (GB)
- National University of Singapore (SG)
- Chinese Academy of Sciences (CN)
- Institute of Semiconductors (CN)
- Hebei University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2024-08-22
- DOI
- https://doi.org/10.1002/adfm.202406666
- Citations
- 14
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hebei Province