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

Publikation: Beitrag in FachzeitschriftÜbersichtsartikel (Review)BeigetragenBegutachtung

Beitragende

  • Min Kyu Song - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Ji Hoon Kang - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Xinyuan Zhang - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Wonjae Ji - , Pohang University of Science and Technology (Autor:in)
  • Alon Ascoli - , Professur für Grundlagen der Elektronik (Autor:in)
  • Ioannis Messaris - , Professur für Grundlagen der Elektronik (Autor:in)
  • Ahmet Samil Demirkol - , Professur für Grundlagen der Elektronik (Autor:in)
  • Bowei Dong - , University of Oxford (Autor:in)
  • Samarth Aggarwal - , University of Oxford (Autor:in)
  • Weier Wan - , Stanford Engineering (Autor:in)
  • Seok Man Hong - , Korea Advanced Institute of Science and Technology (Autor:in)
  • Suma George Cardwell - , Sandia National Laboratories (Autor:in)
  • Irem Boybat - , IBM Research Zurich (Autor:in)
  • Jae Sun Seo - , Arizona State University (Autor:in)
  • Jang Sik Lee - , Pohang University of Science and Technology (Autor:in)
  • Mario Lanza - , King Abdullah University of Science and Technology (Autor:in)
  • Hanwool Yeon - , Gwangju Institute of Science and Technology (Autor:in)
  • Murat Onen - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Ju Li - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Bilge Yildiz - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Jesús A. del Alamo - , Massachusetts Institute of Technology (MIT) (Autor:in)
  • Seyoung Kim - , Pohang University of Science and Technology (Autor:in)
  • Shinhyun Choi - , Korea Advanced Institute of Science and Technology (Autor:in)
  • Gianluca Milano - , Istituto Nazionale di Ricerca Metrologica (Autor:in)
  • Carlo Ricciardi - , Politecnico di Torino (Autor:in)
  • Lambert Alff - , Technische Universität Darmstadt (Autor:in)
  • Yang Chai - , Hong Kong Polytechnic University (Autor:in)
  • Zhongrui Wang - , The University of Hong Kong (Autor:in)
  • Harish Bhaskaran - , University of Oxford (Autor:in)
  • Mark C. Hersam - , Northwestern University (Autor:in)
  • Dmitri Strukov - , University of California at Santa Barbara (Autor:in)
  • H. S.Philip Wong - , Stanford Engineering (Autor:in)
  • Ilia Valov - , Forschungszentrum Jülich, Bulgarian Academy of Sciences (Autor:in)
  • Bin Gao - , Tsinghua University (Autor:in)
  • Huaqiang Wu - , Tsinghua University (Autor:in)
  • Ronald Tetzlaff - , Professur für Grundlagen der Elektronik (Autor:in)
  • Abu Sebastian - , IBM Research Zurich (Autor:in)
  • Wei Lu - , University of Michigan, Ann Arbor (Autor:in)
  • Leon Chua - , University of California at Berkeley (Autor:in)
  • J. Joshua Yang - , University of Southern California (Autor:in)
  • Jeehwan Kim - , Massachusetts Institute of Technology (MIT) (Autor:in)

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.

Details

OriginalspracheEnglisch
Seiten (von - bis)11994-12039
Seitenumfang46
FachzeitschriftACS nano
Jahrgang17
Ausgabenummer13
PublikationsstatusVeröffentlicht - 11 Juli 2023
Peer-Review-StatusJa

Externe IDs

PubMed 37382380
ORCID /0000-0001-7436-0103/work/172566293
ORCID /0000-0002-1236-1300/work/172567145

Schlagworte

Schlagwörter

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