3D Nanoscale Flexible Memristor Networks with Ultralow Power for Information Transmission and Processing Application.

To construct an artificial intelligence system with high efficient information integration and computing capability like human brain, it is necessary to realize the biological neurotransmission and information processing in artificial neural network (ANN), rather than a single electronic synapse. Due to 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) makes it possible for constructing a higher energy efficient computing system than human brain. In this paper, a flexible three-layer crossbar memristor arrays based on HfAlOx film deposited by controlled growth of low-temperature atomic layer deposition is presented, exhibiting the multilevel information transmission functionality with the power consumption of 4.28 aJ and the speed of 50 ns in per synaptic event. The operating speed is orders of magnitude faster than human brain (millisecond level), making it possible for wearable neuromorphic computing system faster than human brain. Besides it, the images recognition with noise pixels is realized successfully (accuracy of 80.9%) by the flexible ANN to verify the high efficient information processing ability. This work is a significant step toward the development of ultrahigh efficient and ultrahigh speed wearable 3D neuromorphic computing system.