Journal of Materials Science

, Volume 53, Issue 12, pp 8720–8746 | Cite as

Oxide-based RRAM materials for neuromorphic computing

  • XiaoLiang Hong
  • Desmond JiaJun Loy
  • Putu Andhita Dananjaya
  • Funan Tan
  • CheeMang Ng
  • WenSiang Lew


In this review, a comprehensive survey of different oxide-based resistive random-access memories (RRAMs) for neuromorphic computing is provided. We begin with the history of RRAM development, physical mechanism of conduction, fundamental of neuromorphic computing, followed by a review of a variety of RRAM oxide materials (PCMO, HfOx, TaOx, TiOx, NiOx, etc.) with a focus on their application for neuromorphic computing. Our goal is to give a broad review of oxide-based RRAM materials that can be adapted to neuromorphic computing and to help further ongoing research in the field.



This work was supported by a RIE2020 AME-Programmatic Grant (Neuromorphic computing, No. A1687b0033) and an Industry-IHL Partnership Program (NRF2015-IIP001-001). WSL is a member of the Singapore Spintronics Consortium (SG-SPIN).


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • XiaoLiang Hong
    • 1
  • Desmond JiaJun Loy
    • 1
  • Putu Andhita Dananjaya
    • 1
  • Funan Tan
    • 1
  • CheeMang Ng
    • 2
  • WenSiang Lew
    • 1
  1. 1.Division of Physics and Applied Physics, School of Physical and Mathematical SciencesNanyang Technological UniversitySingaporeSingapore
  2. 2.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

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