Author(s): Liang, JR (Liang, Jiran); Yu, X (Yu, Xuan); Qiu, J (Qiu, Jie); Wang, M (Wang, Ming); Cheng, CT (Cheng, Chuantong); Huang, BJ (Huang, Beiju); Zhang, HJ (Zhang, Hengjie); Chen, R (Chen, Run); Pei, WH (Pei, Weihua); Chen, HD (Chen, Hongda)

Source: ACS APPLIED MATERIALS & INTERFACES DOI: 10.1021/acsami.2c20166 Early Access Date: FEB 2023

Abstract: Artificial synapses with the capability of optical sensing and synaptic functions are fundamental components to construct neuromorphic visual systems. However, most reported artificial optical synapses require a combination of optical and electrical stimuli to achieve bidirectional synaptic conductance modulation, leading to an increase in the processing time and system complexity. Here, an all-optically controlled artificial synapse based on the graphene/titanium dioxide (TiO2) quantum dot heterostructure is reported, whose conductance could be reversibly tuned by the effects of light-induced oxygen adsorption and desorption. Synaptic behaviors, such as excitatory and inhibitory, short-term and long-term plasticity, and learning-forgetting processes, are implemented using the device. An artificial neural network simulator based on the artificial synapse was used to train and recognize handwritten digits with a recognition rate of 92.2%. Furthermore, a 5 x 5 optical synaptic array that could simultaneously sense and memorize light stimuli was fabricated, mimicking the sensing and memory functionality of the retina. Such an all-optically controlled artificial synapse shows a promising prospect in the application of perception, learning, and memory tasks for future neuromorphic visual systems.

Accession Number: WOS:000935747900001

PubMed ID: 36752383

ISSN: 1944-8244

eISSN: 1944-8252

Full Text: https://pubs.acs.org/doi/10.1021/acsami.2c20166