Advances of embedded resistive random access memory in industrial manufacturing and its potential applications

Zijian Wang; Yixian Song; Guobin Zhang; Qi Luo; Kai Xu; Dawei Gao; Bin Yu; Desmond Loke; Shuai Zhong; Yishu Zhang

doi:10.1088/2631-7990/ad2fea

Embedded memory, which heavily relies on the manufacturing process, has been widely adopted in various industrial applications. As the field of embedded memory continues to evolve, innovative strategies are emerging to enhance performance. Among them, resistive random access memory (RRAM) has gained significant attention due to its numerous advantages over traditional memory devices, including high speed (<1 ns), high density (4 F²·n^-1), high scalability (~nm), and low power consumption (~pJ). This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potential applications. It provides a brief introduction to the concepts and advantages of RRAM, discusses the key factors that impact its industrial manufacturing, and presents the commercial progress driven by cutting-edge nanotechnology, which has been pursued by many semiconductor giants. Additionally, it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing, with a particular emphasis on its role in neuromorphic computing. Finally, the review discusses the current challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.

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Advances of embedded resistive random access memory in industrial manufacturing and its potential applications

doi: 10.1088/2631-7990/ad2fea

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通讯作者: 陈斌, bchen63@163.com

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