journal article·2024-09Open access

Fully UV Modulated Artificial Synapses with Integrated Sensing, Storage and Computation

Shuyi Sun, Tao Zhang, Shuoqi Jin, Xinhua Pan, Jianguo Lu, Zhizhen Ye, Bin Lu

Advanced Functional Materials· Volume 34· Issue 36

Abstract

Abstract Optical synaptic devices are considered a preferred substitute to electrical synapses for low‐energy, high‐efficiency neuromorphic computing (NC). However, most optical synapses irreversible optical response severely restricts their application scenarios. In this study, a fully photon‐modulated synaptic device constructed from Si‐doped beta‐gallium oxide (β‐Ga2O3)/ZnO heterojunction is demonstrated. The device exhibits reversible conductance changes and mimics a range of synaptic behaviors, which are modulated by two different wavelengths (255 and 370 nm) of UV light. Owing to the device's plasticity, four types of logic functions including “AND”, “OR”, “NOR” and “NAND” are implemented in the device by optical stimulation. Furthermore, an artificial neural network (ANN) is simulated based on the device's excitatory and inhibitory characteristics, and an optical programming scheme is employed to enhance the network's performance, resulting in a high recognition rate of 95.5% for handwritten digits. The fully photon‐modulated synapse development strategy and programming scheme, as presented in this work, advance the utilization of optical artificial synapses in ANN.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Transition Metal Oxide Nanomaterials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Hangzhou 310058 China

Funding

National Natural Science Foundation of China · Key Research and Development Program of Zhejiang Province

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