Artificial Neuron using Ag/2D-MoS/Au Threshold Switching Memristor

Durjoy Dev, Adithi Krishnaprasad, Zhezhi He, Sonali Das, Mashiyat Sumaiya Shawkat, Madison Manley, Olaleye Aina, Deliang Fan, Yeonwoong Jung, Tania Roy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


The phenomenal evolution of information and communication drives future technologies towards highly parallel, energy-efficient self-learning systems like the human brain. The limitations of current von Neumann computation systems have paved the way for artificial neural networks (ANN) to meet these criteria. The memristor has become an emerging candidate to realize ANN through emulating biological synapse and neuron behavior [1]-[3]. We previously reported an artificial neuron with 2D Mos2 and graphene electrode, but the operating voltage was high, and the output current was low [4]. In this work, we harness threshold switching in Mos2 enabled by Ag electrode, to emulate integration and firing behavior of neuron and demonstrate digit recognition application with these devices. The simple vertical structure of Ag/MoS/ Au threshold switching memristor (TSM), with very low threshold voltage (\mathrm{V}-{\mathrm{t}\mathrm{h}}=0.4-0.5\mathrm{V}), displays the four crucial features of neuron all-or-nothing spiking, threshold-driven firing, post firing refractory period and stimulus strength based frequency response.

Original languageEnglish (US)
Title of host publication2019 Device Research Conference, DRC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages2
ISBN (Electronic)9781728121123
StatePublished - Jun 2019
Externally publishedYes
Event2019 Device Research Conference, DRC 2019 - Ann Arbor, United States
Duration: Jun 23 2019Jun 26 2019

Publication series

NameDevice Research Conference - Conference Digest, DRC
ISSN (Print)1548-3770


Conference2019 Device Research Conference, DRC 2019
Country/TerritoryUnited States
CityAnn Arbor

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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