Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons

Haoming Yu, A. N.M.Nafiul Islam, Sandip Mondal, Abhronil Sengupta, Shriram Ramanathan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We report on switching dynamics of individual and coupled vanadium dioxide (VO2) devices subject to voltage pulses as the temperature is systematically varied from room temperature spanning the insulator-metal transition (IMT) temperature. The switching voltage of single devices has a strong relationship with both temperature and voltage pulsewidth. Two-step switching in connected VO2 devices has been noted in current transient plots and was found to depend on temperature, pulsewidth, and pulse amplitude. Experimental switching behavior measured from VO2 artificial neurons was implemented into a spiking neural network (SNN). During training, modulating the switching voltage via temperature affords a novel method to implement homeostasis with the coupled devices. Simulation results show the efficacy of the stochastic neuronal characteristics and the proposed homeostasis mechanism on a standard digit recognition task. These studies contribute to ongoing efforts in neuromorphic computing exploiting collective phase transitions.

Original languageEnglish (US)
Pages (from-to)3135-3141
Number of pages7
JournalIEEE Transactions on Electron Devices
Volume69
Issue number6
DOIs
StatePublished - Jun 1 2022

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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