Biological receptor-inspired flexible artificial synapse based on ionic dynamics

Qifeng Lu,Zihao Wang,Mingming Hao,Yingyi Wang,Shuqi Wang,Lin Liu,Lianhui Li,Fuqin Sun,Ting Zhang

doi:10.1038/s41378-020-00189-z

Abstract

The memristor has been regarded as a promising candidate for constructing a neuromorphic computing platform that is capable of confronting the bottleneck of the traditional von Neumann architecture. Here, inspired by the working mechanism of the G-protein-linked receptor of biological cells, a novel double-layer memristive device with reduced graphene oxide (rGO) nanosheets covered by chitosan (an ionic conductive polymer) as the channel material is constructed. The protons in chitosan and the functional groups in rGO nanosheets imitate the functions of the ligands and receptors of biological cells, respectively. Smooth changes in the response current depending on the historical applied voltages are observed, offering a promising pathway toward biorealistic synaptic emulation. The memristive behavior is mainly a result of the interaction between protons provided by chitosan and the defects and functional groups in the rGO nanosheets. The channel current is due to the hopping of protons through functional groups and is limited by the traps in the rGO nanosheets. The transition from short-term to long-term potentiation is achieved, and learning-forgetting behaviors of the memristor mimicking those of the human brain are demonstrated. Overall, the bioinspired memristor-type artificial synaptic device shows great potential in neuromorphic networks.

Highlights

Inspired by the massive parallelism, robust computation, fault tolerance, and energy efficiency of the human brain, neuromorphic computing has attracted a tremendous upsurge of research interest since synaptic behaviors were mimicked by Mead in 1996 using a floating-gate silicon metal-oxide-semiconductor transistor[1,2,3,4,5]
In the designed memristive device, the protons in CS and the functional groups in reduced graphene oxide (rGO) are able to imitate the functions of the ligands and receptors of biological cells, respectively
In conclusion, a bioinspired double-layered memristor matrix was fabricated with rGO nanosheets prepared by chemical redox reactions and natural CS biopolymers

Summary

Introduction

Inspired by the massive parallelism, robust computation, fault tolerance, and energy efficiency of the human brain, neuromorphic computing has attracted a tremendous upsurge of research interest since synaptic behaviors were mimicked by Mead in 1996 using a floating-gate silicon metal-oxide-semiconductor transistor[1,2,3,4,5]. Memristors are a type of two-terminal device with a layer of memristive material sandwiched between metal electrodes in either a vertical or planar structure. Lu et al Microsystems & Nanoengineering (2020)6:84 devices is highly related to the selection of both memristive and electrode materials. Binary metal oxides, oxide perovskites, polymers, and 2D materials have been widely used as memristive layers in the construction of memristors[9,10,11,12]. According to different working mechanisms, memristors can be categorized into filament-type and barrier-type devices[8]. Different from filament-type memristors, barrier-type memristors generally modulate the conductance states by the defect effect, which can overcome the electroforming randomness, ensuring reproducibility, and device-to-device uniformity[14,15]. Use of the barrier-type memristor is considered a more suitable approach to emulate synaptic behaviors

Methods

Results

Conclusion