Self-Powered Halide Perovskite Optoelectronic Synaptic Memristors for Reconfigurable Logic and Reservoir Computing Applications

The development of low-power neuromorphic systems requires the integration of sensing, logic operations, neuromorphic computing, and energy autonomy. Herein, we present a triple-cation and triple-anion perovskite-based (p-type/intrinsic/n-type) p-i-n optoelectronic memristor array that synergistically combines these functions. The device's inherent photovoltaic effect (∼0.8 V) enables self-powered optical synaptic plasticity at 520 nm, eliminating external biasing for near-zero power consumption. By coupling this intrinsic photovoltaic bias with tunable external voltages, we demonstrate four reconfigurable Boolean logic operations (NOT, XOR, NAND, IMPLY). Furthermore, a reservoir computing (RC) system for neuromorphic pattern recognition is implemented by leveraging the plasticity of the perovskite memristor, achieving classification accuracies of 97.94% for 1-bit and 90.73% for 4-bit handwritten digit recognition. The self-powered memristor integrating optical synapses, digital logic, and neuromorphic functionalities provide new paradigms for developing next-generation low-power, high-density integrated circuits with hybrid digital-analog architectures.

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Publication Details

Journal
Nano Letters
Published
2025-10-16
DOI
https://doi.org/10.1021/acs.nanolett.5c04297
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92
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article

Self-Powered Halide Perovskite Optoelectronic Synaptic Memristors for Reconfigurable Logic and Reservoir Computing Applications

Zhenhua Lin, Dongsheng Cui, Pusheng Guo, Yumeng Xu et al.
4 citations
Nano Letters
Advanced Memory and Neural Computing
2.92
article

Self-Powered Halide Perovskite Optoelectronic Synaptic Memristors for Reconfigurable Logic and Reservoir Computing Applications

Zhenhua Lin, Dongsheng Cui, Pusheng Guo, Yumeng Xu, Wei Wei, Jincheng Zhang, Jingjing Chang, Xing Guo, Xiangxiang Gao, Yue Hao
article en
4 citations

Abstract

The development of low-power neuromorphic systems requires the integration of sensing, logic operations, neuromorphic computing, and energy autonomy. Herein, we present a triple-cation and triple-anion perovskite-based (p-type/intrinsic/n-type) p-i-n optoelectronic memristor array that synergistically combines these functions. The device's inherent photovoltaic effect (∼0.8 V) enables self-powered optical synaptic plasticity at 520 nm, eliminating external biasing for near-zero power consumption. By coupling this intrinsic photovoltaic bias with tunable external voltages, we demonstrate four reconfigurable Boolean logic operations (NOT, XOR, NAND, IMPLY). Furthermore, a reservoir computing (RC) system for neuromorphic pattern recognition is implemented by leveraging the plasticity of the perovskite memristor, achieving classification accuracies of 97.94% for 1-bit and 90.73% for 4-bit handwritten digit recognition. The self-powered memristor integrating optical synapses, digital logic, and neuromorphic functionalities provide new paradigms for developing next-generation low-power, high-density integrated circuits with hybrid digital-analog architectures.

Nano LettersVol. 25(43)
Xidian University (CN), Advanced Pharma (US)
Openalex Percentile: Top 8%
Advanced Memory and Neural Computing
2.92
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