Manufacturing of graphene based synaptic devices for optoelectronic applications

Neuromorphic computing systems can perform memory and computing tasks in parallel on artificial synaptic devices through simulating synaptic functions,which is promising for breaking the conventional von Neumann bottlenecks at hardware level.Artificial optoelectronic synapses enable the synergistic coupling between optical and electrical signals in synaptic modulation,which opens up an innovative path for effective neuromorphic systems.With the advantages of high mobility,optical transparency,ultrawideband tunability,and environmental stability,graphene has attracted tremendous interest for electronic and optoelectronic applications.Recent progress highlights the significance of implementing graphene into artificial synaptic devices.Herein,to better understand the potential of graphene-based synaptic devices,the fabrication technologies of graphene are first presented.Then,the roles of graphene in various synaptic devices are demonstrated.Furthermore,their typical optoelectronic applications in neuromorphic systems are reviewed.Finally,outlooks for development of synaptic devices based on graphene are proposed.This review will provide a comprehensive understanding of graphene fabrication technologies and graphene-based synaptic device for optoelectronic applications,also present an outlook for development of graphene-based synaptic device in future neuromorphic systems.

Recent advances in memristors based on two-dimensional ferroelectric materials

In this big data era, the explosive growth of information puts ultra-high demands on the data storage/computing, such as high computing power, low energy consumption, and excellent stability. However, facing this challenge, the traditional von Neumann architecture-based computing system is out of its depth owing to the separated memory and data processing unit architecture. One of the most effective ways to solve this challenge is building brain inspired computing system with in-memory computing and parallel processing ability based on neuromorphic devices. Therefore, there is a research trend toward the memristors, that can be applied to build neuromorphic computing systems due to their large switching ratio, high storage density, low power consumption, and high stability. Two-dimensional (2D) ferroelectric materials, as novel types of functional materials, show great potential in the preparations of memristors because of the atomic scale thickness, high carrier mobility, mechanical flexibility, and thermal stability. 2D ferroelectric materials can realize resistive switching (RS) because of the presence of natural dipoles whose direction can be flipped with the change of the applied electric field thus producing different polarizations, therefore, making them powerful candidates for future data storage and computing. In this review article, we introduce the physical mechanisms, characterizations, and synthetic methods of 2D ferroelectric materials, and then summarize the applications of 2D ferroelectric materials in memristors for memory and synaptic devices. At last, we deliberate the advantages and future challenges of 2D ferroelectric materials in the application of memristors devices.

Triboelectric nanogenerator for neuromorphic electronics

Building the brain-inspired neural network computing system based neuromorphic electronics is an effective approach to break the von Neumann bottleneck on the hardware level and realize the information processing with high efficiency and low energy consumption in this big data explosion age.Triboelectric nanogenerator(TENG)has two functions of sensing and energy conversion,which promote the application as sensor and/or power supply in self-powered neuromorphic electronics for data storage and biological synapse/neuron behaviors mimicking.This article highlights the relevant works of TENGs for memory devices,artificial synapses and artificial neurons,performs a systematic comparison,and puts forward the future research possibilities and challenges,with the hope of attracting more researchers into this field and promoting the development of TENG based neuromorphic electronics.