Design of All‐Optical Bidirectional Self‐Powered Synaptic Devices for Neuromorphic Computing Applications

Self-powered optoelectronic synaptic devices have garnered significant attention due to their ultra-low energy consumption and self-rectification properties. However, the mechanism of mimicking their inhibitory behaviors remains unclear, presenting a challenge in attempting to realize optically inhibitory behaviors. This study fabricates formamidinium lead iodide perovskite-based synaptic devices that exhibit self-powered-optical potentiation and electrical inhibition behaviors. The mechanism underlying the inhibitory behaviors is argued to be the defect trap at room temperature and iodine ion migration at lower temperatures. Considering the optical potentiation behaviors and inhibitory mechanism clarified here, ethanediamine dihydroiodide is incorporated into the perovskite layer to regulate the synaptic behaviors. Impressively, this additive results in a shift of the self-powered-optical potentiation to its inhibition. First-principles calculations reveal that an increase of iodide vacancy formation energies facilitates this transformation by possibly modulating the carrier trap and ion migration behaviors. Additionally, the optically excitatory and optically inhibitory synaptic behaviors of the integrated systems with and without EDADI are exploited to implement MINIST and CIFAR-10 recognition tasks and achieve the high recognition rates of 97.95% and 77.36%, respectively. This work significantly advances the understanding of mimicking self-powered optically inhibitory synaptic behaviors and contributes to the development of all-optical bidirectional self-powered neuromorphic computing systems.

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Publication Details

Journal
Small
Published
2025-07-01
DOI
https://doi.org/10.1002/smll.202505327
Citations
5
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
3.65

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article

Design of All‐Optical Bidirectional Self‐Powered Synaptic Devices for Neuromorphic Computing Applications

Xuegong Yu, Pengjie Hang, Xing’ao Li, Biao Li et al.
5 citations
Small
Advanced Memory and Neural Computing
3.65
article

Design of All‐Optical Bidirectional Self‐Powered Synaptic Devices for Neuromorphic Computing Applications

Xuegong Yu, Pengjie Hang, Xing’ao Li, Biao Li, Lei Wang, Zhengjian Lin, Jiawei Tang, Huixing Zhang, Xin Zhang, Wen Huang
article en
5 citations

Abstract

Self-powered optoelectronic synaptic devices have garnered significant attention due to their ultra-low energy consumption and self-rectification properties. However, the mechanism of mimicking their inhibitory behaviors remains unclear, presenting a challenge in attempting to realize optically inhibitory behaviors. This study fabricates formamidinium lead iodide perovskite-based synaptic devices that exhibit self-powered-optical potentiation and electrical inhibition behaviors. The mechanism underlying the inhibitory behaviors is argued to be the defect trap at room temperature and iodine ion migration at lower temperatures. Considering the optical potentiation behaviors and inhibitory mechanism clarified here, ethanediamine dihydroiodide is incorporated into the perovskite layer to regulate the synaptic behaviors. Impressively, this additive results in a shift of the self-powered-optical potentiation to its inhibition. First-principles calculations reveal that an increase of iodide vacancy formation energies facilitates this transformation by possibly modulating the carrier trap and ion migration behaviors. Additionally, the optically excitatory and optically inhibitory synaptic behaviors of the integrated systems with and without EDADI are exploited to implement MINIST and CIFAR-10 recognition tasks and achieve the high recognition rates of 97.95% and 77.36%, respectively. This work significantly advances the understanding of mimicking self-powered optically inhibitory synaptic behaviors and contributes to the development of all-optical bidirectional self-powered neuromorphic computing systems.

SmallVol. 21(34)
Nanjing University of Posts and Telecommunications (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Affordable and clean energy
Openalex Percentile: Top 7%
Advanced Memory and Neural Computing
3.65
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