Memristive synapse based on perovskite Cs3Cu2I5 for reservoir computing

Perovskite memristors have attracted considerable attention for their potential in emulating artificial synapses. However, the widespread use of the toxic lead-based perovskites poses significant challenges to futural application. In this work, we developed a lead-free memristor with an Ag/PMMA/Cs3Cu2I5/ITO architecture, in which the Cs3Cu2I5 halide perovskites functional layer was fabricated by physical vapor deposition. The memristor demonstrated a data retention time of 104 s and stable resistive switching behavior over 100 cycles under electrical pulses stimulation. Furthermore, it emulated a range of biologically relevant synaptic functions, including paired-pulse facilitation, short-term plasticity, long-term plasticity, spike-amplitude-dependent plasticity, spike-number-dependent plasticity, and spike-duration-dependent plasticity. Capitalizing on its nonlinear dynamics and short-term memory characteristics, the device was further integrated into a reservoir computing (RC) system. The RC system demonstrated strong recognition performance and robustness when tested with distorted digital image datasets. These results suggest that the Cs3Cu2I5-based memristor provides a promising, environmentally friendly platform for next-generation artificial intelligence hardware.

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Publication Details

Journal
Applied Physics Letters
Published
2025-09-01
DOI
https://doi.org/10.1063/5.0281204
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Memristive synapse based on perovskite Cs3Cu2I5 for reservoir computing

Xinman Chen, Hong Zhou, Yin Zheng, Yao Meng et al.
Applied Physics Letters
Advanced Memory and Neural Computing
article

Memristive synapse based on perovskite Cs3Cu2I5 for reservoir computing

Xinman Chen, Hong Zhou, Yin Zheng, Yao Meng, Jinwen Lin, Bin Li, Jiang Wu
article en

Abstract

Perovskite memristors have attracted considerable attention for their potential in emulating artificial synapses. However, the widespread use of the toxic lead-based perovskites poses significant challenges to futural application. In this work, we developed a lead-free memristor with an Ag/PMMA/Cs3Cu2I5/ITO architecture, in which the Cs3Cu2I5 halide perovskites functional layer was fabricated by physical vapor deposition. The memristor demonstrated a data retention time of 104 s and stable resistive switching behavior over 100 cycles under electrical pulses stimulation. Furthermore, it emulated a range of biologically relevant synaptic functions, including paired-pulse facilitation, short-term plasticity, long-term plasticity, spike-amplitude-dependent plasticity, spike-number-dependent plasticity, and spike-duration-dependent plasticity. Capitalizing on its nonlinear dynamics and short-term memory characteristics, the device was further integrated into a reservoir computing (RC) system. The RC system demonstrated strong recognition performance and robustness when tested with distorted digital image datasets. These results suggest that the Cs3Cu2I5-based memristor provides a promising, environmentally friendly platform for next-generation artificial intelligence hardware.

Applied Physics LettersVol. 127(9)
Hunan University (CN), South China Normal University (CN)
Science and Technology Planning Project of Guangdong Province
Openalex Percentile: Top 78%
Advanced Memory and Neural Computing
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