Ga <sub>2</sub> O <sub>3</sub> Optoelectronic Array with Solar-Blind Ultraviolet Perception for Neuron Spatiotemporal Integration and Forgetting-Enabled Neuromorphic Computing

Optoelectronic neuromorphic devices capable of perceiving and memorizing light signals are essential for constructing artificial vision systems. While oxide-semiconductor-based optoelectronic devices are valued for their stable performance and mature fabrication processes, they primarily operate in the near-ultraviolet to near-infrared spectral range, lacking sensitivity to the solar-blind region (<280 nm), which offers extremely low background noise and enhanced signal-to-noise ratios. Herein, this study presents an optoelectronic neuromorphic device array based on wide-bandgap Ga<sub>2</sub>O<sub>3</sub>, designed to perceive optical signals in the solar-blind region. Stimulated by a 254 nm light pulse, the device emulates biological visual synaptic plasticity and exhibits tunable relaxation characteristics of postsynaptic current under varying stimuli. Notably, the device array replicates the spatiotemporal integration and processing of signals from multiple preneurons via dendritic structures, demonstrating its potential for implementing advanced neuromorphic computing, including the perception and memory of solar-blind ultraviolet images during learning processes. Moreover, leveraging the tunable relaxation properties of Ga<sub>2</sub>O<sub>3</sub> devices, a forgetting-based artificial neural network is developed to address multisolution problems in complex equations with ultralow power consumption. These findings not only establish an optoelectronic neuromorphic system capable of perceiving solar-blind signals but also broaden its potential applications in low-power computing and intelligent sensing.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-10-23
DOI
https://doi.org/10.1021/acsami.5c15360
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Ga 2 O 3 Optoelectronic Array with Solar-Blind Ultraviolet Perception for Neuron Spatiotemporal Integration and Forgetting-Enabled Neuromorphic Computing

Zehui Peng, Yu Jiang, H. H. Liu, Bing‐Ming Cheng et al.
1 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
0.73
article

Ga 2 O 3 Optoelectronic Array with Solar-Blind Ultraviolet Perception for Neuron Spatiotemporal Integration and Forgetting-Enabled Neuromorphic Computing

Zehui Peng, Yu Jiang, H. H. Liu, Bing‐Ming Cheng, Kuan‐Chang Chang, Ray‐Hua Horng, Lei Li, Qunkai Peng, Hao Yu
article en
1 citations

Abstract

Optoelectronic neuromorphic devices capable of perceiving and memorizing light signals are essential for constructing artificial vision systems. While oxide-semiconductor-based optoelectronic devices are valued for their stable performance and mature fabrication processes, they primarily operate in the near-ultraviolet to near-infrared spectral range, lacking sensitivity to the solar-blind region (<280 nm), which offers extremely low background noise and enhanced signal-to-noise ratios. Herein, this study presents an optoelectronic neuromorphic device array based on wide-bandgap Ga<sub>2</sub>O<sub>3</sub>, designed to perceive optical signals in the solar-blind region. Stimulated by a 254 nm light pulse, the device emulates biological visual synaptic plasticity and exhibits tunable relaxation characteristics of postsynaptic current under varying stimuli. Notably, the device array replicates the spatiotemporal integration and processing of signals from multiple preneurons via dendritic structures, demonstrating its potential for implementing advanced neuromorphic computing, including the perception and memory of solar-blind ultraviolet images during learning processes. Moreover, leveraging the tunable relaxation properties of Ga<sub>2</sub>O<sub>3</sub> devices, a forgetting-based artificial neural network is developed to address multisolution problems in complex equations with ultralow power consumption. These findings not only establish an optoelectronic neuromorphic system capable of perceiving solar-blind signals but also broaden its potential applications in low-power computing and intelligent sensing.

ACS Applied Materials & InterfacesVol. 17(44)
National Yang Ming Chiao Tung University (TW), National University of Singapore (SG), Peking University (CN), Key Laboratory of Guangdong Province (CN), Integrated Optoelectronics (Norway) (NO), Peking University Shenzhen Hospital (CN), Shenzhen Technology University (CN)
Openalex Percentile: Top 22%
Advanced Memory and Neural Computing
0.73
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