Abstract
MXenes are materials with a few thick layers of transition metal carbides, nitrides, and carbonitrides and have received considerable attention because of their widespread application in energy storage in photonic diodes. In addition, nanoscale devices that include either an MXene layer only or a combination of MXene and other functional layers were found to exhibit multiple non-volatile resistance states when subjected to an electrical stimulus. Therefore, the MXene layer has most recently shown a strong liaison with the concept of the well-known memristor, whereby a variety of MXene-based memristors have been developed for emerging neuromorphic applications. Despite the current prosperity, the physics behind which MXene-based devices enable memristive behaviour remains vague, and the advantages and disadvantages of these reported MXene-based memristors in association with their performance comparisons are missing. To address these issues, we first presented different types of MXene-based memristors according to the constitutions of their active layers, and the possible physical mechanisms that govern the memristive behaviours of these memristors were analysed. The promising applications of the reported MXene-based memristors, particularly in the field of neuromorphic intelligence, are subsequently discussed. Finally, the advantages and disadvantages of MXene-based memristors and their practical prospects are envisaged.
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No potential conflict of interest was reported by the author(s).
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Notes on contributors
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Xiaojuan Lian
Xiaojuan Lian received the B. S. degree in electronic science and technology and the M. S. degree in physical electronics from Xidian University, Xi’an, China, in 2008 and 2011 respectively. She received her Ph.D. degree in electrical engineering from the Universitat Autònoma de Barcelona, Spain, in 2014. She is currently an associate professor at the Department of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, China. Her research interests include memristive devices (RRAM, PCRAM and so on), 2D material-based devices, information storage, and artificial intelligence.
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Yuelin Shi
Yuelin Shi received the B. Eng. degree in information engineering from Ludong University, Shandong, China, in 2021. She is currently pursuing the M.S. degree with Nanjing University of Posts and Telecommunications, engaged in the research of neuromorphic computing applications based on memristor.
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Shiyu Li
Shiyu Li received the B. Eng. degree in Microelectronics Science and Engineering from Nanjing University of Posts and Telecommunications, Nanjing, China, in 2022. He is currently pursuing the M. S. degree with Nanjing University of Posts and Telecommunications, engaged in the design and analysis of memristor devices.
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Bingxin Ding
Bingxin Ding received the B. Eng. degree in new energy science and engineering from Yancheng Teachers University, Yancheng, China, in 2021. She is currently pursuing the M. S. degree with Nanjing University of Posts and Telecommunications, engaged in the research of logic gates research based on memristor.
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Chenfei Hua
Chenfei Hua received the B. Eng. degree in Science and Engineering of Microelectronics from Nanjing University of Posts and Telecommunications, JiangSu, China, in 2022. He is currently pursuing the M. S. degree with Nanjing University of Posts and Telecommunications, engaged in the research of Memoristor test.
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Lei Wang
Lei Wang received the B. Eng. degree in electrical engineering from the Beijing University of Science and Technology, Beijing, China, in 2003, the M. Sc. degree in electronic instrumentation systems from the University of Manchester, Manchester, U.K., in 2004, and the Ph.D degree in “Tbit/sq.in. scanning probe phase-change memory” from the University of Exeter, Exeter, U.K., in 2009. Between 2008 and 2011, he was employed as a Postdoctoral Research Fellow in the University of Exeter to work on a fellowship funded by European Commision. These works included the study of phase-change probe memory and phase-change memristor. Since 2020, he joined the Nanjing University of Posts and Telecommunications, Nanjing, P. R. China as a Professor, where he is engaged in the phase-change memories, phase-change neural networks, and other phase-change based optoelectronic devices and their potential applications.