记忆电阻器
纳米技术
石墨烯
材料科学
计算机科学
神经形态工程学
计算机体系结构
电阻随机存取存储器
电气工程
人工神经网络
人工智能
工程类
电压
作者
Zhican Zhou,Fengyou Yang,S. Wang,Lei Wang,Xiaofeng Wang,Cong Wang,Yong Xie,Qian Liu
标识
DOI:10.1007/s11467-021-1114-5
摘要
The rapid development of big-data analytics (BDA), internet of things (IoT) and artificial intelligent Technology (AI) demand outstanding electronic devices and systems with faster processing speed, lower power consumption, and smarter computer architecture. Memristor, as a promising Non-Volatile Memory (NVM) device, can effectively mimic biological synapse, and has been widely studied in recent years. The appearance and development of two-dimensional materials (2D material) accelerate and boost the progress of memristor systems owing to a bunch of the particularity of 2D material compared to conventional transition metal oxides (TMOs), therefore, 2D material-based memristors are called as new-generation intelligent memristors. In this review, the memristive (resistive switching) phenomena and the development of new-generation memristors are demonstrated involving graphene (GR), transition-metal dichalcogenides (TMDs) and hexagonal boron nitride (h-BN) based memristors. Moreover, the related progress of memristive mechanisms is remarked.
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