nl9b05271_si_001.pdf (1.36 MB)
Three-Dimensional Nanoscale Flexible Memristor Networks with Ultralow Power for Information Transmission and Processing Application
journal contribution
posted on 2020-03-23, 11:35 authored by Tian-Yu Wang, Jia-Lin Meng, Ming-Yi Rao, Zhen-Yu He, Lin Chen, Hao Zhu, Qing-Qing Sun, Shi-Jin Ding, Wen-Zhong Bao, Peng Zhou, David Wei ZhangTo
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.