Three-Dimensional Nanoscale Flexible Memristor Networks with Ultralow Power for Information Transmission and Processing Application

• Published in: Nano letters Vol. 20; no. 6; pp. 4111 - 4120
• Main Authors: Wang, Tian-Yu, Meng, Jia-Lin, Rao, Ming-Yi, He, Zhen-Yu, Chen, Lin, Zhu, Hao, Sun, Qing-Qing, Ding, Shi-Jin, Bao, Wen-Zhong, Zhou, Peng, Zhang, David Wei
• Format: Journal Article
• Language: English
• Published: United States 10.06.2020
• Subjects: artificial neural network; memristor array; information transmission; wearable electronics
• ISSN: 1530-6984; 1530-6992; 1530-6992
• DOI: 10.1021/acs.nanolett.9b05271

To construct an artificial intelligence system with high efficient information integration and computing capability like the human brain, it is necessary to realize the biological neurotransmission and information processing in artificial neural network (ANN), rather than a single electronic synapse as most reports. Because the power consumption of single synaptic event is ∼10 fJ in biology, designing an intelligent memristors-based 3D ANN with energy consumption lower than femtojoule-level (e.g., attojoule-level) and faster operating speed than millisecond-level makes it possible for constructing a higher energy efficient and higher speed computing system than the human brain. In this paper, a flexible 3D crossbar memristor array is presented, exhibiting the multilevel information transmission functionality with the power consumption of 4.28 aJ and the response speed of 50 ns per synaptic event. This work is a significant step toward the development of an ultrahigh efficient and ultrahigh-speed wearable 3D neuromorphic computing system.