Halide perovskite based synaptic devices for neuromorphic systems

Keonwon Beom, Zhaoyang Fan, Dawen Li, Nathan Newman

Research output: Contribution to journalReview articlepeer-review

Abstract

Information systems with architectures that mimic biological neural networks are of interest because they can efficiently perform adaptive learning and memory functions and process vast amount of information instantly. Halide perovskites (HPs) have been recently explored to fabricate memristors, memcapacitors, and phototransistors as neuromorphic devices used in these systems, thanks to their unique properties, which have not been seen in conventional semiconductors and metal oxides. In this review, we introduce fundamentals of artificial neural networks (ANNs), emphasize unique properties of HPs in such a context, discuss different HP-based neuromorphic devices suitable for ANNs, highlight examples on their preliminary performance demonstration, and comment on their issues and future perspectives.

Original languageEnglish (US)
Article number100667
JournalMaterials Today Physics
Volume24
DOIs
StatePublished - May 2022
Externally publishedYes

Keywords

  • Halide perovskite
  • Memcapacitors
  • Memristors
  • Neuromorphic systems
  • Synaptic phototransistors

ASJC Scopus subject areas

  • Materials Science(all)
  • Energy (miscellaneous)
  • Physics and Astronomy (miscellaneous)

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