Improving linearity by introducing Al in HfO2 as a memristor synapse device

Sridhar Chandrasekaran, Firman Mangasa Simanjuntak, R. Saminathan, Debashis Panda, Tseung-Yuen Tseng

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Artificial synapse having good linearity is crucial to achieve an efficient learning process in neuromorphic computing. It is found that the synaptic linearity can be enhanced by engineering the doping region across the switching layer. The nonlinearity of potentiation and depression of the pure device is 36% and 91%, respectively; meanwhile, the nonlinearity after doping can be suppressed to be 22% (potentiation) and 60% (depression). Henceforth, the learning accuracy of the doped device is 91% with only 13 iterations; meanwhile, the pure device is 78%. A detailed conduction mechanism to understand this phenomenon is proposed.

Original languageEnglish
Article number445205
JournalNanotechnology
Volume30
Issue number44
DOIs
StatePublished - 1 Nov 2019

Keywords

  • artificial synaptic
  • memristor
  • neuromorphic
  • resistive switching

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