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
Copyright Status
Unknown
Socpus ID
85053191123 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85053191123
STARS Citation
Kalita, Hirokjyoti; Krishnaprasad, Adithi; Choudhary, Nitin; Das, Sonali; and Chung, Hee Suk, "Artificial Neuron Using Mos2/Graphene Threshold Switching Memristors" (2018). Scopus Export 2015-2019. 7663.
https://stars.library.ucf.edu/scopus2015/7663