Emerging optoelectronic artificial synapses and memristors based on low-dimensional nanomaterials

  • Pengshan Xie
  • , Dengji Li
  • , Sen Po Yip
  • , Johnny C. Ho*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

The Von Neumann architecture has been the foundation of modern computing systems. Still, its limitations in processing large amounts of data and parallel processing have become more apparent as computing requirements increase. Neuromorphic computing, inspired by the architecture of the human brain, has emerged as a promising solution for developing next-generation computing and memory devices with unprecedented computational power and significantly lower energy consumption. In particular, the development of optoelectronic artificial synaptic devices has made significant progress toward emulating the functionality of biological synapses in the brain. Among them, the potential to mimic the function of the biological eye also paves the way for advancements in robot vision and artificial intelligence. This review focuses on the emerging field of optoelectronic artificial synapses and memristors based on low-dimensional nanomaterials. The unique photoelectric properties of these materials make them ideal for use in neuromorphic and optoelectronic storage devices, with advantages including high carrier mobility, size-tunable optical properties, and low resistor-capacitor circuit delay. The working mechanisms, device structure designs, and applications of these devices are also summarized to achieve truly sense-storage-computer integrated optoelectronic artificial synapses.

Original languageEnglish
Article number011303
JournalApplied Physics Reviews
Volume11
Issue number1
DOIs
StatePublished - 1 Mar 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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