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Nano Research 2023, 16(1): 1165-1182 https://doi.org/10.1007/s12274-022-4773-9
Review Article | Issue | Published: 23 August 2022

A review of Mott insulator in memristors: The materials, characteristics, applications for future computing systems and neuromorphic computing

Show Author's Information Yunfeng Ran1,  Yifei Pei1,  Zhenyu Zhou1,  Hong Wang1,  Yong Sun1,  Zhongrong Wang1,  Mengmeng Hao1,  Jianhui Zhao1( ),  Jingsheng Chen2( ),  Xiaobing Yan1( )
Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
Department of Materials Science and Engineering, National University of Singapore, Singapore 117576, Singapore
Keywords:
memristor, Mott insulator, the strongly correlated electronic system, neuromorphological calculations
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Nano device
Cite this article:
Ran Y, Pei Y, Zhou Z, et al. A review of Mott insulator in memristors: The materials, characteristics, applications for future computing systems and neuromorphic computing. Nano Research, 2023, 16(1): 1165-1182. https://doi.org/10.1007/s12274-022-4773-9
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Abstract Full text About this article

Mott insulator material, as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity, shows excellent application prospects in neuromorphological calculations and has attracted significant attention in the scientific community. Especially, computing systems based on Mott insulators can overcome the bottleneck of separated data storage and calculation in traditional artificial intelligence systems based on the von Neumann architecture, with the potential to save energy, increase operation speed, improve integration, scalability, and three-dimensionally stacked, and more suitable to neuromorphic computing than a complementary metal-oxide-semiconductor. In this review, we have reviewed Mott insulator materials, methods for driving Mott insulator transformation (pressure-, voltage-, and temperature-driven approaches), and recent relevant applications in neuromorphic calculations. The results in this review provide a path for further study of the applications in neuromorphic calculations based on Mott insulator materials and the related devices.


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About this article

A review of Mott insulator in memristors: The materials, characteristics, applications for future computing systems and neuromorphic computing

Show Author's information Yunfeng Ran1, Yifei Pei1, Zhenyu Zhou1, Hong Wang1, Yong Sun1, Zhongrong Wang1, Mengmeng Hao1, Jianhui Zhao1( ), Jingsheng Chen2( ), Xiaobing Yan1( )
Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
Department of Materials Science and Engineering, National University of Singapore, Singapore 117576, Singapore

Abstract

Mott insulator material, as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity, shows excellent application prospects in neuromorphological calculations and has attracted significant attention in the scientific community. Especially, computing systems based on Mott insulators can overcome the bottleneck of separated data storage and calculation in traditional artificial intelligence systems based on the von Neumann architecture, with the potential to save energy, increase operation speed, improve integration, scalability, and three-dimensionally stacked, and more suitable to neuromorphic computing than a complementary metal-oxide-semiconductor. In this review, we have reviewed Mott insulator materials, methods for driving Mott insulator transformation (pressure-, voltage-, and temperature-driven approaches), and recent relevant applications in neuromorphic calculations. The results in this review provide a path for further study of the applications in neuromorphic calculations based on Mott insulator materials and the related devices.

Keywords: memristor, Mott insulator, the strongly correlated electronic system, neuromorphological calculations

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Publication history
Copyright
Acknowledgements

Publication history

Received: 30 March 2022
Revised: 13 July 2022
Accepted: 14 July 2022
Published: 23 August 2022
Issue date: January 2023

Copyright

© Tsinghua University Press 2022

Acknowledgements

Acknowledgements

This work was financially supported by the National Key Research & Development Plan “Nano Frontier” Key Special Project (No. 2021YFA1200502), Cultivation projects of national major Research & Development project (No. 92164109), the National Natural Science Foundation of China (Nos. 61874158, 62004056, and 62104058), Special project of strategic leading science and technology of Chinese Academy of Sciences (No. XDB44000000-7), Hebei Basic Research Special Key Project (No. F2021201045), Support Program for the Top Young Talents of Hebei Province (No. 70280011807), Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province (No. SLRC2019018), Interdisciplinary Research Program of Natural Science of Hebei University (No. DXK202101), Institute of Life Sciences and Green Development (No. 521100311), Natural Science Foundation of Hebei Province (Nos. F2022201054 and F2021201022), Outstanding Young Scientific Research and Innovation Team of Hebei University (No. 605020521001), Special Support Funds for National High Level Talents (No. 041500120001), Advanced Talents Incubation Program of the Hebei University (Nos. 521000981426, 521100221071, and 521000981363), and Funded by Science and Technology Project of Hebei Education Department (Nos. QN2020178 and QN2021026).

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