ZnO photoconductive synaptic devices for neuromorphic computing

材料科学 神经形态工程学 光电子学 欧姆接触 光子学 纳米技术 计算机科学 人工神经网络 人工智能 图层(电子)
作者
Qiuchen Shang,Wenbo Peng,Tuo Song,Zeyang Li,Fangpei Li,Yongning He
出处
期刊:Materials Science in Semiconductor Processing [Elsevier BV]
卷期号:162: 107489-107489 被引量:6
标识
DOI:10.1016/j.mssp.2023.107489
摘要

In the field of artificial intelligence, neuromorphic computing offers the allure of human brain simulation. The capacity of optoelectronic synapses to intelligently handle optoelectronic input signals makes them a key component of neuromorphic computing. In this work, we fabricated ZnO-based optoelectronic synapses and investigated their electronic and photonic synaptic plasticity. The device fabrication process flow is as follows: photolithography is performed on ITO glass, followed by hydrochloric acid etching and degumming to obtain interdigital electrodes on the glass substrate, and a ZnO film is grown on the interdigitated electrodes by magnetron sputtering. A good Ohmic contact is formed between the ZnO and ITO electrodes, and the device exhibits a linear relationship between current and voltage under dark field conditions, and exhibits excellent synaptic properties and sensitivity in UV switching response experiments. Additional processes were subsequently introduced through growing ZnO nanowires and annealing, and the synaptic properties of ZnO device were improved. The shift from short-term to long-term memory, short-term plasticity, long-term plasticity, paired-pulse facilitation, and learning to experience behavior are only a few of the synaptic activities of the nervous system that have been successfully described. The manufactured array device also includes a special memory recall feature that may retrieve previous optoelectronic data. This work will advance the field of artificial intelligence and stimulate additional study on optoelectronic synapses.
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