International Journal of Extreme Manufacturing, Volume. 6, Issue 3, 32006(2024)

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

Zijian Wang1...2,3, Yixian Song1,2,3, Guobin Zhang1,2, Qi Luo1,2, Kai Xu1,2, Dawei Gao1,2, Bin Yu1,2, Desmond Loke4, Shuai Zhong5, and Yishu Zhang12,* |Show fewer author(s)
Author Affiliations
  • 1College of Integrated Circuits, Zhejiang University, Hangzhou, Zhejiang 3112000, People’s Republic of China
  • 2ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 310027, People’s Republic of China
  • 3These authors contribute equally
  • 4Department of Science, Mathematics and Technology, Singapore University of Technology and Design,Singapore 487372, Singapore
  • 5Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai 519031, People’s Republic of China
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    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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    Zijian Wang, Yixian Song, Guobin Zhang, Qi Luo, Kai Xu, Dawei Gao, Bin Yu, Desmond Loke, Shuai Zhong, Yishu Zhang. Advances of embedded resistive random access memory in industrial manufacturing and its potential applications[J]. International Journal of Extreme Manufacturing, 2024, 6(3): 32006

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    Paper Information

    Received: Jul. 17, 2023

    Accepted: --

    Published Online: Sep. 11, 2024

    The Author Email: Zhang Yishu (zhangyishu@zju.edu.cn)

    DOI:10.1088/2631-7990/ad2fea

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