Emerging MXene-Based Memristors for In-Memory,Neuromorphic Computing,and Logic Operation |
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Authors: | Songtao Ling Cheng Zhang Chunlan Ma Yang Li Qichun Zhang |
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Affiliation: | 1. Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009 China;2. Department of Materials Science and Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, 999077 China |
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Abstract: | Confronted by the difficulties of the von Neumann bottleneck and memory wall, traditional computing systems are gradually inadequate for satisfying the demands of future data-intensive computing applications. Recently, memristors have emerged as promising candidates for advanced in-memory and neuromorphic computing, which pave one way for breaking through the dilemma of current computing architecture. Till now, varieties of functional materials have been developed for constructing high-performance memristors. Herein, the review focuses on the emerging 2D MXene materials-based memristors. First, the mainstream synthetic strategies and characterization methods of MXenes are introduced. Second, the different types of MXene-based memristive materials and their widely adopted switching mechanisms are overviewed. Third, the recent progress of MXene-based memristors for data storage, artificial synapses, neuromorphic computing, and logic circuits is comprehensively summarized. Finally, the challenges, development trends, and perspectives are discussed, aiming to provide guidelines for the preparation of novel MXene-based memristors and more engaging information technology applications. |
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Keywords: | 2D materials data storage logic operation memristors MXenes neuromorphic computing |
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