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#edge computing Open access

Light‐Synergistic Enhanced Synaptic Devices Toward Superadditive In‐Sensor Computing

Sep 2026 · Rare Metals · Vol 45 · 50 references
Advanced Memory and Neural Computing Neural Networks and Reservoir Computing

Abstract

ABSTRACT Conventional neuromorphic devices face challenges in achieving efficient integration of light sensing and synaptic computation because of structural and material limitations. In this work, we developed an indium‐tin‐zinc oxide/transparent gelatin electrolyte synaptic transistor incorporating rare metal indium. The device features a lateral‐gate and top‐enclosed configuration, enabling independent and synergistic modulation of both horizontal electrical inputs and vertical optical signals. We further revealed an oxygen‐vacancy‐mediated asymmetric carrier trapping mechanism, which, under electro‐optical co‐stimulation, induces superadditive ion–photon–electron interactions and significantly enhances the dynamic range of synaptic weight modulation. Based on this mechanism, we demonstrated the first superadditive in‐sensor reservoir computing system capable of simultaneous spatiotemporal signal encoding and classification, achieving high‐accuracy recognition in both Morse code and handwritten digit tasks. This work establishes a new approach and hardware foundation for developing compact, high‐efficiency neuromorphic devices, holding great potential for edge‐oriented vision computing applications.

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