Title

Artificial Neuron Using Mos2/Graphene Threshold Switching Memristors

Abstract

With the ever-increasing demand for low power electronics, neuromorphic computing has garnered huge interest in recent times. Artificial neurons form a critical part in neuromorphic circuits, and have been realized with complex CMOS circuitry in the past. Recently, metal-insulator-transition materials have been used to realize artificial neurons [1]-[3]. Although memristors have been used to realize synaptic behavior, not much work has been done in demonstrating neuronal response with these devices. A threshold switching memristor with Ag/SiO2/ Au was used recently to demonstrate the integration-and-fire behavior of a neuron [4] while a neuristor was realized using Mott memristors [5]. In this work, we use the volatility of threshold switching MoS2/Graphene (Gr) 2D/2D heterojunction system to realize the integration-and-fire response of a neuron. We use large area chemical vapor deposited (CVD) graphene and Mos2, enabling large scale realization of these devices. These low power devices can emulate the most vital properties of a neuron, such as a threshold driven spiking and a refractory period. These results show that the developed artificial neuron can playa crucial role in neuromorphic computing.

Publication Date

8-20-2018

Publication Title

Device Research Conference - Conference Digest, DRC

Volume

2018-June

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/DRC.2018.8443301

Socpus ID

85053191123 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85053191123

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