X-Ray Irradiation Improved WSe2 Optical–Electrical Synapse for Handwritten Digit Recognition

Two-dimensional (2D) materials are promising candidates for neuromorphic computing owing to their atomically thin structure and tunable optoelectronic properties. However, achieving controllable synaptic behavior via defect engineering remains challenging. In this work, we introduce X-ray irradiation as a facile strategy to modulate defect states and enhance synaptic plasticity in WSe<sub>2</sub>-based optoelectronic synapses. The introduction of selenium vacancies via irradiation significantly improved both electrical and optical responses. Under electrical stimulation, short-term potentiation (STP) exhibited enhanced excitatory postsynaptic current (EPSC) retention exceeding 10%, measured 20 s after the stimulation peak. In addition, the nonlinearity of long-term potentiation (LTP) and long-term depression (LTD) was reduced, and the signal decay time was extended. Under optical stimulation, STP showed more than 4% improvement in EPSC retention at 16 s with similar relaxation enhancement. These effects are attributed to irradiation-induced defect states that facilitate charge carrier trapping and extend signal persistence. Moreover, the reduced nonlinearity in synaptic weight modulation improved the recognition accuracy of handwritten digits in a CrossSim-simulated MNIST task, increasing from 88.5% to 93.75%. This study demonstrates that X-ray irradiation is an effective method for modulating synaptic weights in 2D materials, offering a universal strategy for defect engineering in neuromorphic device applications.

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Publication Details

Journal
Nanomaterials
Published
2025-09-12
DOI
https://doi.org/10.3390/nano15181408
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46

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article

X-Ray Irradiation Improved WSe2 Optical–Electrical Synapse for Handwritten Digit Recognition

Qi Sun, Yaxian Lu, Chuanwen Chen, Ping Chen
2 citations
Nanomaterials
Advanced Memory and Neural Computing
1.46
article

X-Ray Irradiation Improved WSe2 Optical–Electrical Synapse for Handwritten Digit Recognition

Qi Sun, Yaxian Lu, Chuanwen Chen, Ping Chen
article en
2 citations

Abstract

Two-dimensional (2D) materials are promising candidates for neuromorphic computing owing to their atomically thin structure and tunable optoelectronic properties. However, achieving controllable synaptic behavior via defect engineering remains challenging. In this work, we introduce X-ray irradiation as a facile strategy to modulate defect states and enhance synaptic plasticity in WSe<sub>2</sub>-based optoelectronic synapses. The introduction of selenium vacancies via irradiation significantly improved both electrical and optical responses. Under electrical stimulation, short-term potentiation (STP) exhibited enhanced excitatory postsynaptic current (EPSC) retention exceeding 10%, measured 20 s after the stimulation peak. In addition, the nonlinearity of long-term potentiation (LTP) and long-term depression (LTD) was reduced, and the signal decay time was extended. Under optical stimulation, STP showed more than 4% improvement in EPSC retention at 16 s with similar relaxation enhancement. These effects are attributed to irradiation-induced defect states that facilitate charge carrier trapping and extend signal persistence. Moreover, the reduced nonlinearity in synaptic weight modulation improved the recognition accuracy of handwritten digits in a CrossSim-simulated MNIST task, increasing from 88.5% to 93.75%. This study demonstrates that X-ray irradiation is an effective method for modulating synaptic weights in 2D materials, offering a universal strategy for defect engineering in neuromorphic device applications.

NanomaterialsVol. 15(18)
Guangxi University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province
Openalex Percentile: Top 15%
Advanced Memory and Neural Computing
1.46
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X-Ray Irradiation Improved WSe2 Optical–Electrical Synapse for Handwritten Digit Recognition — Qi Sun, Yaxian Lu, et al. · Nanomaterials (2025) | TGRS Research Map | TGRS