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Article Abstract
Realizing the dual-mode electric and optical synaptic plasticity within one neuromorphic device is impressive for the construction of a compact artificial visual system. Here, we proposed indium gallium zinc oxide (IGZO) photoelectric synaptic transistors utilizing all-solid-state electrolytes (Li-doped ZrO) as gate dielectric layers. The device was fabricated by using a facile and cost-effective all-solution method. The synaptic transistor exhibited dual-mode electric and optical synaptic plasticity. Meanwhile, the tunable conductance is achieved through electric potentiation and depression processes, demonstrating the potential for realizing neuromorphic computing. Based on this, a simulated convolutional neural network was designed to realize handwriting digit recognition, achieving an accuracy of 96.8%. Additionally, sophisticated neuromorphic applications such as logic operations, Pavlov's classical experiment, and pupillary reflex simulation were successfully realized. Therefore, the designed transistor demonstrates significant potential for future applications in artificial vision.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12044511 | PMC |
| http://dx.doi.org/10.1021/acsomega.5c01052 | DOI Listing |
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