Hongyuan Zhao , Jiangni Yun , Zhen Li , Yu Liu , Lei Zheng , Peng Kang
{"title":"二维范德华铁电:通向下一代存储器和神经形态计算设备的途径","authors":"Hongyuan Zhao , Jiangni Yun , Zhen Li , Yu Liu , Lei Zheng , Peng Kang","doi":"10.1016/j.mser.2024.100873","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid increase in CPU processing speeds has significantly advanced artificial intelligence, yet it has also exacerbated the disparity in CPU utilization and data throughput rates due to the shared memory architecture of traditional von Neumann systems. To enhance computational efficiency, there is a critical need to explore advanced functional materials and integrate these into novel computing architectures. Two-dimensional (2D) ferroelectric materials, characterized by their atomic-scale ferroelectric non-volatile properties and low switching barriers, emerge as promising candidates. These materials are particularly suitable for use as non-volatile resistors and artificial synapses within in-memory computing frameworks. Furthermore, their compatibility with Si-CMOS technology enables the high-density integration of devices, potentially driving a new paradigm in integrated computation between processing units and storage architectures. This review focuses on recent developments in 2D ferroelectric materials, including their structural properties, polarization switching mechanisms, and diverse applications. Special emphasis is placed on their potential in integrated applications such as non-volatile memories, neural network computing, non-volatile logic operations, and optoelectronic memories within neuromorphic computing devices.</div></div>","PeriodicalId":386,"journal":{"name":"Materials Science and Engineering: R: Reports","volume":"161 ","pages":"Article 100873"},"PeriodicalIF":31.6000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two-dimensional van der Waals ferroelectrics: A pathway to next-generation devices in memory and neuromorphic computing\",\"authors\":\"Hongyuan Zhao , Jiangni Yun , Zhen Li , Yu Liu , Lei Zheng , Peng Kang\",\"doi\":\"10.1016/j.mser.2024.100873\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The rapid increase in CPU processing speeds has significantly advanced artificial intelligence, yet it has also exacerbated the disparity in CPU utilization and data throughput rates due to the shared memory architecture of traditional von Neumann systems. To enhance computational efficiency, there is a critical need to explore advanced functional materials and integrate these into novel computing architectures. Two-dimensional (2D) ferroelectric materials, characterized by their atomic-scale ferroelectric non-volatile properties and low switching barriers, emerge as promising candidates. These materials are particularly suitable for use as non-volatile resistors and artificial synapses within in-memory computing frameworks. Furthermore, their compatibility with Si-CMOS technology enables the high-density integration of devices, potentially driving a new paradigm in integrated computation between processing units and storage architectures. This review focuses on recent developments in 2D ferroelectric materials, including their structural properties, polarization switching mechanisms, and diverse applications. Special emphasis is placed on their potential in integrated applications such as non-volatile memories, neural network computing, non-volatile logic operations, and optoelectronic memories within neuromorphic computing devices.</div></div>\",\"PeriodicalId\":386,\"journal\":{\"name\":\"Materials Science and Engineering: R: Reports\",\"volume\":\"161 \",\"pages\":\"Article 100873\"},\"PeriodicalIF\":31.6000,\"publicationDate\":\"2024-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Science and Engineering: R: Reports\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0927796X24001037\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Science and Engineering: R: Reports","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0927796X24001037","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Two-dimensional van der Waals ferroelectrics: A pathway to next-generation devices in memory and neuromorphic computing
The rapid increase in CPU processing speeds has significantly advanced artificial intelligence, yet it has also exacerbated the disparity in CPU utilization and data throughput rates due to the shared memory architecture of traditional von Neumann systems. To enhance computational efficiency, there is a critical need to explore advanced functional materials and integrate these into novel computing architectures. Two-dimensional (2D) ferroelectric materials, characterized by their atomic-scale ferroelectric non-volatile properties and low switching barriers, emerge as promising candidates. These materials are particularly suitable for use as non-volatile resistors and artificial synapses within in-memory computing frameworks. Furthermore, their compatibility with Si-CMOS technology enables the high-density integration of devices, potentially driving a new paradigm in integrated computation between processing units and storage architectures. This review focuses on recent developments in 2D ferroelectric materials, including their structural properties, polarization switching mechanisms, and diverse applications. Special emphasis is placed on their potential in integrated applications such as non-volatile memories, neural network computing, non-volatile logic operations, and optoelectronic memories within neuromorphic computing devices.
期刊介绍:
Materials Science & Engineering R: Reports is a journal that covers a wide range of topics in the field of materials science and engineering. It publishes both experimental and theoretical research papers, providing background information and critical assessments on various topics. The journal aims to publish high-quality and novel research papers and reviews.
The subject areas covered by the journal include Materials Science (General), Electronic Materials, Optical Materials, and Magnetic Materials. In addition to regular issues, the journal also publishes special issues on key themes in the field of materials science, including Energy Materials, Materials for Health, Materials Discovery, Innovation for High Value Manufacturing, and Sustainable Materials development.