Robust and Low-Power-Consumption Black Phosphorus–Graphene Artificial Synaptic Devices

Abstract

black phosphorus (BP) materials, as the most promising building blocks for the development of artificial synapses, have attracted more and more attention. However, the instability of exfoliated 2D BP structures still remains a problem in the development of artificial synapse devices. In this study, the robust and low-power-consumption artificial-synapticbased BP was successfully manufactured. The synapse devices have high stability in the air atmosphere and do not show obvious degradation over 3 months. The obtained devices not only implement the main function of synapses but also perform the function of dendritic neural synapses and simple logical operations, revealing their very strong learning behavior. The high mobility of 2D BP as well as the coupled effect and quantum confinement effect of the graphene oxide quantum dot (GOQD) can greatly boost the performance of BP-based synapse devices, such as low power consumption (62 pW) and high sensitivity (ultrasmall stimuli at an amplitude of −20 mV). Moreover, benefiting from the GOQD and the interaction between BP and graphene, the main dominated mechanism of the BP− graphene synapse device can be the capture and release of electrons by the 2D BP and GOQD instead of the conductive filament.

Hybridization state transition-driven carbon quantum dot (CQD)-based resistive switches for bionic synapses

“…Synaptic activity is characterized by excitatory postsynaptic currents (EPSCs), which represent action currents generated by synapses after stimulation. 36–38 The logic operation behavior using EPSC of different strengths is demonstrated with this characteristic. 39 When low input voltages are applied to synapse 1 (0.4 V) and synapse 2 (0.6 V), the EPSCs obtained for both are less than 18 μA (set as threshold).…”

Self-powered optoelectronic artificial synapses based on a lead-free perovskite film for artificial visual perception systems

“…4,5 The sophisticated human nervous system, composed of the central nervous system for computing, memory, and learning and the sensory nervous system for the information detection of stimuli from the external environment, exhibits low energy consumption, highly parallel processing power, and fault-tolerance, has inspired researchers to develop a neuromorphic computing system for replacing the von Neumann machine in the future. 6–9…”

“…4,5 The sophisticated human nervous system, composed of the central nervous system for computing, memory, and learning and the sensory nervous system for the information detection of stimuli from the external environment, exhibits low energy consumption, highly parallel processing power, and fault-tolerance, has inspired researchers to develop a neuromorphic computing system for replacing the von Neumann machine in the future. [6][7][8][9] For humans, more than 80% of the information from the complex external environment is perceived, processed, and transmitted to the brain via the visual perception system. 9,10 It is universally acknowledged that developing an optoelectronic synaptic device, which not only incorporates photosensitive functions and synaptic plasticity but also possesses the prospective advantages of high bandwidth, neglectable crosstalk, and lowpower dissipation, is crucial to realize an artificial visual perception system.…”

Artificial Optoelectronic Synapse Based on Violet Phosphorus Microfiber Arrays

“…In 2022, our group conducted a study of BP artificial synapses and successfully fabricated rugged and low‐energy artificial BP synapses on the basis of the interplay between BP and graphene. [ 14 ] In actuality, more than 70% of the information learned by humans comes from the visual system, which is able to recognize various objects in complex environments and perceive visual information. At present, the introduction of light to construct optoelectronic synaptic devices to achieve the biological visual perception system and simulation of synaptic functions has become a research hotspot.…”