The rise of metal halide perovskite memristors for edge computing

Tianwei Duan, Jiajia Zha, Ning Lin, Zhongrui Wang*, Chaoliang Tan*, Yuanyuan Zhou*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

8 Citations (Scopus)

Abstract

The rapid expansion of artificial intelligence and the internet of things demands an unprecedentedly high level of efficiency in edge computing. Processing-in-memory sensors, based on memristors, play a pivotal role in addressing these challenges, facilitating real-time decision-making, data optimization, and energy efficiency. Despite widespread interest, there's a dearth of innovation in memristor materials. Metal halide perovskites offer distinct advantages over mainstream memristive materials due to their lower formation energy and strong interaction with light, positioning them as an integrated optoelectronic platform for in-memory computing sensors. In this work, we review metal halide perovskite memristors emphasizing materials, devices, and applications. We discuss their mixed ionic and electronic properties and optoelectronically induced conduction channel formation. Furthermore, we examine device structures, memristive mechanisms, and synapse-like behaviors, together with an exploration of the potential for edge computing applications. Finally, we present our vision for their future development from both hardware and software perspectives.

Original languageEnglish
Article number100221
Number of pages20
JournalDevice
Volume1
Issue number6
DOIs
Publication statusPublished - 22 Dec 2023

Scopus Subject Areas

  • Engineering (miscellaneous)
  • Condensed Matter Physics

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