Electrical/light-modulated kesterite synaptic memristor for potential near-infrared vision imaging
Optoelectronic memristors with low-power and high parallelism have made neuromorphic artificial intelligence a viable reality. Several smart modulation of the memristive conductance by electrical and light signals is central for advancing the memristor with brain-like synaptic functions. Herein, a feasible visual synapse is presented in an Ag/CZTSSe/Mo structured optoelectric memristor. The device demonstrates not only a high switching ratio (>10 3 ), excellent retention time (>10 4 s), and continuously tunable conductance, but also the independently electrical- and light-modulated synaptic functionalities, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term potentiation/depression (STP/STD), and spike-timing-dependent plasticity (STDP). Particularly, taking advantage of the cognizable memory effects produced by multi-intensity near-infrared light, visual imaging of Monkey D. Luffy is achieved in a constructed 24 × 19 memristor arrays, closely mimicking the biological visual processing. These results hold the potential for CZTSSe-based optoelectronic memristor in advancing neuromorphic computing , offering a promising path toward the development of brain-inspired intelligent systems. • Electrical/light-modulated artificial optoelectronic synapse is successfully realized on kesterite-based memristor. • High On/Off switching ratio exceeding 10 3 and long retention time up to 10 4 s. • Excellent bio-synaptic behaviors mimicking by both electrical- and light-stimuli. • Near-infrared visual imaging application achieved in a 24 × 19 memristor arrays. • Potential in facilitating artificial optoelectronic synapses to enable neuromorphic computation.
Authors
- Yun Zhao (ORCID: https://orcid.org/0000-0002-4378-5317)
- Zhanchuan Cai (ORCID: https://orcid.org/0000-0002-6954-7691)
- Jian‐Hui Lan (ORCID: https://orcid.org/0000-0003-0654-8483)
- Xiaofei Dong (ORCID: https://orcid.org/0000-0001-5727-9231)
- Yan Li (ORCID: https://orcid.org/0000-0002-3402-3396)
Institutions
- Macau University of Science and Technology (MO)
- Hubei University of Automotive Technology (CN)
- Northwest Normal University (CN)
Publication Details
- Journal
- Journal of Alloys and Compounds
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1016/j.jallcom.2025.180469
- Citations
- 2
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Natural Science Foundation of China