An electroforming-free, analog interface-type memristor based on a SrFeOx epitaxial heterojunction for neuromorphic computing

  • J. Rao
  • , Z. Fan*
  • , L. Hong
  • , S. Cheng
  • , Q. Huang
  • , J. Zhao
  • , X. Xiang
  • , E. J. Guo
  • , H. Guo
  • , Z. Hou
  • , Y. Chen
  • , X. Lu
  • , G. Zhou
  • , X. Gao
  • , J. M. Liu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Distinct from the conductive filament-type counterparts, the interface-type resistive switching (RS) devices are electroforming-free and exhibit bidirectionally continuous conductance changes, making them promising candidates as analog synapses. While the interface-type RS devices typically operate through the interfacial oxygen migration, materials which can tolerate a wide range of oxygen non-stoichiometry and possess high oxygen mobility are therefore demanded. SrFeOx (SFO), which can easily transform between a conductive, oxygenated perovskite SrFeO3 (PV-SFO) phase and an insulating, oxygen-vacancy-rich brownmillerite SrFeO2.5 (BM-SFO) phase under electric field, emerges as a suitable material. Herein, an interface-type RS device is ingeniously structured by two epitaxial SFO layers: a PV-SFO matrix layer and an ultrathin BM-SFO interfacial layer, aiming to leverage the oxygen migration-induced interfacial BM-PV phase transformation to realize the gradual conductance modulation. Experimentally, the fabricated device exhibits electroforming-free, analog memristive behavior. This device also emulates essential synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, transition from short-term memory to long-term memory, spike-timing-dependent plasticity, and potentiation/depression. A simulated neural network built from the SFO-based synapses achieves accuracies above 88% for image recognition. This work provides a novel approach to use the SFO family of topotactic materials for developing analog synapses as building blocks for neuromorphic computing circuits.

Original languageEnglish
Article number100392
JournalMaterials Today Physics
Volume18
DOIs
Publication statusPublished - May 2021
Externally publishedYes

Keywords

  • Interface-type resistive switching
  • Memristors
  • Neuromorphic computing
  • SrFeO
  • Topotactic phase transformation

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