Effect of oxygen vacancy on the conduction modulation linearity and classification accuracy of pr0.7ca0.3mno3 memristor

Yeon Pyo, Jong Un Woo, Hyun Gyu Hwang, Sahn Nahm, Jichai Jeong

Research output: Contribution to journalArticlepeer-review

Abstract

An amorphous Pr0.7Ca0.3MnO3 (PCMO) film was grown on a TiN/SiO2/Si (TiN–Si) substrate at 300 °C and at an oxygen pressure (OP) of 100 mTorr. This PCMO memristor showed typ-ical bipolar switching characteristics, which were attributed to the generation and disruption of oxygen vacancy (OV) filaments. Fabrication of the PCMO memristor at a high OP resulted in non-linear conduction modulation with the application of equivalent pulses. However, the memristor fabricated at a low OP of 100 mTorr exhibited linear conduction modulation. The linearity of this memristor improved because the growth and disruption of the OV filaments were mostly deter-mined by the redox reaction of OV owing to the presence of numerous OVs in this PCMO film. Furthermore, simulation using a convolutional neural network revealed that this PCMO memristor has enhanced classification performance owing to its linear conduction modulation. This memris-tor also exhibited several biological synaptic characteristics, indicating that an amorphous PCMO thin film fabricated at a low OP would be a suitable candidate for artificial synapses.

Original languageEnglish
Article number2684
JournalNanomaterials
Volume11
Issue number10
DOIs
Publication statusPublished - 2021 Oct

Keywords

  • Convolutional neural network
  • Memristor
  • Pr0.7Ca0.3MnO3
  • Resistive switching memory

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Materials Science(all)

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