神经形态工程学
记忆电阻器
横杆开关
材料科学
炸薯条
纳米技术
光电子学
计算机体系结构
计算机科学
电子工程
人工神经网络
工程类
人工智能
电信
作者
Jin-Gi Min,Hamin Park,Won-Ju Cho
出处
期刊:Nanomaterials
[Multidisciplinary Digital Publishing Institute]
日期:2022-08-28
卷期号:12 (17): 2978-2978
被引量:6
摘要
In this study, a high-performance bio-organic memristor with a crossbar array structure using milk as a resistive switching layer (RSL) is proposed. To ensure compatibility with the complementary metal oxide semiconductor process of milk RSL, a high-k Ta2O5 layer was deposited as a capping layer; this layer enables high-density, integration-capable, photolithography processes. The fabricated crossbar array memristors contain milk-Ta2O5 hybrid membranes, and they exhibit bipolar resistance switching behavior and uniform resistance distribution across hundreds of repeated test cycles. In terms of the artificial synaptic behavior and synaptic weight changes, milk-Ta2O5 hybrid crossbar array memristors have a stable analog RESET process, and the memristors are highly responsive to presynaptic stimulation via paired-pulse facilitation excitatory post-synaptic current. Moreover, spike-timing-dependent plasticity and potentiation and depression behaviors, which closely emulate long-term plasticity and modulate synaptic weights, were evaluated. Finally, an artificial neural network was designed and trained to recognize the pattern of the Modified National Institute of Standards and Technology (MNIST) digits to evaluate the capability of the neuromorphic computing system. Consequently, a high recognition rate of over 88% was achieved. Thus, the milk-Ta2O5 hybrid crossbar array memristor is a promising electronic platform for in-memory computing systems.
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