Applications of MXene-based memristors in neuromorphic intelligence applications. Issue 2 (3rd April 2022)

• Record Type: Journal Article
• Authors: Lian, Xiaojuan; Shi, Yuelin; Li, Shiyu; Ding, Bingxin; Hua, Chenfei; Wang, Lei
• Is Part Of: Contemporary physics. Volume 63:Issue 2(2022)
• Page Start: 87
• Page End: 105
• Publication Date: 2022-04-03
• Subjects: MXene material -- memristor -- resistance switching -- neuromorphic intelligence; Physics -- Periodicals; 530
• DOI: 10.1080/00107514.2022.2160542
• Languages: English
• ISSNs: 0010-7514

Abstract

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.