Recent Advances and Future Prospects for Memristive Materials, Devices, and Systems

Min Kyu Song, Ji Hoon Kang, Xinyuan Zhang, Wonjae Ji, Alon Ascoli, Ioannis Messaris, Ahmet Samil Demirkol, Bowei Dong, Samarth Aggarwal, Weier Wan, Seok Man Hong, Suma George Cardwell, Irem Boybat, Jae Sun Seo, Jang Sik Lee, Mario Lanza, Hanwool Yeon, Murat Onen, Ju Li, Bilge YildizJesús A. del Alamo, Seyoung Kim, Shinhyun Choi, Gianluca Milano, Carlo Ricciardi, Lambert Alff, Yang Chai, Zhongrui Wang, Harish Bhaskaran, Mark C. Hersam, Dmitri Strukov, H. S.Philip Wong, Ilia Valov, Bin Gao, Huaqiang Wu, Ronald Tetzlaff, Abu Sebastian, Wei Lu, Leon Chua, J. Joshua Yang, Jeehwan Kim

Research output: Contribution to journalReview articlepeer-review

91 Scopus citations

Abstract

Memristive technology has been rapidly emerging as a potential alternative to traditional CMOS technology, which is facing fundamental limitations in its development. Since oxide-based resistive switches were demonstrated as memristors in 2008, memristive devices have garnered significant attention due to their biomimetic memory properties, which promise to significantly improve power consumption in computing applications. Here, we provide a comprehensive overview of recent advances in memristive technology, including memristive devices, theory, algorithms, architectures, and systems. In addition, we discuss research directions for various applications of memristive technology including hardware accelerators for artificial intelligence, in-sensor computing, and probabilistic computing. Finally, we provide a forward-looking perspective on the future of memristive technology, outlining the challenges and opportunities for further research and innovation in this field. By providing an up-to-date overview of the state-of-the-art in memristive technology, this review aims to inform and inspire further research in this field.

Original languageEnglish (US)
Pages (from-to)11994-12039
Number of pages46
JournalACS nano
Volume17
Issue number13
DOIs
StatePublished - Jul 11 2023

Keywords

  • compute-in-memory
  • ferroelectric memory
  • in-sensor computing
  • ion-intercalation resistors
  • memristor
  • memtransistors
  • neuromorphic computing
  • phase change memory
  • resistive switching memory

ASJC Scopus subject areas

  • General Materials Science
  • General Engineering
  • General Physics and Astronomy

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