Two-terminal β-Ga2O3 photo-synapse for diversified in-sensor computing via self-trapped holes engineering
Yiyin Nie; Shujie Jiao; Xing Yang; Shiyong Gao; Dongbo Wang; Y F Li; Jinzhong Wang; Liancheng Zhao · 2026 · Light Science & Applications
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract The rapid advancement of artificial intelligence has propelled the development of β-Ga 2 O 3 photo-synapses for solar-blind ultraviolet neuromorphic machine vision systems. However, existing β-Ga 2 O 3 photo-synapses not only exhibit reduced stability but also display high weight update nonlinearity. Herein, we propose a novel strategy to construct β-Ga 2 O 3 photo-synapses with low weight update nonlinearity based on self-trapped holes, aiming to achieve multi-level in-sensor computing tasks. Theoretical and experimental investigations revealed that the interaction between the larger
Abstract by Yiyin Nie; Shujie Jiao; Xing Yang; Shiyong Gao; Dongbo Wang; Y F Li; Jinzhong Wang; Liancheng Zhao, Light Science & Applications (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1038/s41377-026-02298-2