CAREER: Non-volatile memory devices based on sliding ferroelectricity

职业：基于滑动铁电的非易失性存储器件

• 批准号: 2339093
• 负责人: Ying Wang
• 金额: $ 53.17万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-09-01 至 2029-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339093&HistoricalAwards=false
• 关键词: CAREER; Non; volatile; memory; devices

This project will deliver a range of inclusive research and educational activities, such as memory research opportunities, outreach programs, and scientific lectures, targeting diverse groups from high school students and teachers to undergraduates. Next-generation memory technology is significant in addressing the escalating data capacity and energy demands of modern computing and data-driven applications such as the Internet of Things, smart manufacturing, and AI-empowered medical care. With the need for higher data densities, lower power consumption, faster access times, traditional memory solutions are reaching their limits. This project seeks to develop a new type of memory device—sliding ferroelectric tunnel junctions. It aims to harness the unique advantages of nonvolatile sliding ferroelectricity in atomically thin layered materials, which includes ultralow energy consumption, fast switching speed and ultracompact footprint. The resulting memory devices can enhance the performance capabilities essential for emergent technologies in artificial intelligence, big data analytics, and edge computing. A new type of ferroelectricity has been discovered in van der Waals materials, namely sliding ferroelectricity. The relative arrangement of atomic layers can break the mirror symmetry and inversion symmetry, leading to vertical spontaneous polarization. The ferroelectric switching between two opposite polarization is accomplished by relative lateral sliding between adjacent atomic layers with remarkably ultralow switching energy barriers and ultrafast switching time. Together with the advantage of the atomically clean surface of van der Waals materials for constructing robust ferroelectric tunneling junctions, such novel sliding ferroelectricity is promising for next-generation memory, logic and computational technologies. This CAREER proposal seeks to understand sliding ferroelectric orders, their role in ferroelectric tunneling junctions with an objective to realize memory devices with ultrafast operation speed, ultralow energy consumption and multistate functionalities. The project encompasses comprehensive studies including fundamental understanding of sliding ferroelectricity in response to various electrical and mechanical boundary conditions, ferroelectric tunneling junction device prototyping, benchmark, and metric optimization, and multistate device development. New techniques developed in this project will be integrated into undergraduate and graduate education to foster enthusiasm for STEM careers among the future generation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将提供一系列包容性的研究和教育活动，例如记忆研究机会，外展计划和科学讲座，以高中生和教师到本科生的潜水员群体为目标。下一代内存技术对于解决现代计算和数据驱动的应用程序（例如物联网，智能制造和AI授权医疗服务）的数据能力和能源需求的不断升级而具有重要意义。由于需要更高的数据密度，较低的功耗，更快的访问时间，因此传统的存储解决方案已达到其限制。该项目旨在开发一种新型的存储器设备，即平板的铁电隧道连接。它的目的是利用原子薄层材料中非易失性滑动铁电的独特优势，其中包括超低能量消耗，快速开关速度和超跨足迹。最终的内存设备可以增强人工智能，大数据分析和边缘计算中新兴技术必不可少的性能功能。在范德华材料中发现了一种新型的铁电性，即滑动铁电性。原子层的相对排列可以打破镜像对称性和反转对称性，从而导致垂直的赞助商极化。两个相反极化之间的铁电交换是通过相邻的原子层之间的相对侧面滑动来实现的，具有极大的超低开关能量屏障和超快切换时间。加上范德华材料的原子清洁表面，用于构建坚固的铁电隧道连接，这种新型滑动铁电性对于下一代记忆，逻辑和计算技术都是有希望的。该职业建议旨在了解滑动铁电订单，它们在铁电隧道连接处的作用，目的是实现具有超快操作速度，超低能耗和多态功能的记忆设备。该项目涵盖了全面的研究，包括对各种电气和机械边界条件，铁电隧道连接装置原型制作，基准和度量优化的基本了解以及多层设备的开发。该项目中开发的新技术将纳入本科和研究生教育，以促进未来一代中的STEM职业的热情。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子优点和更广泛的影响来评估NSF的法定任务，并被认为是宝贵的支持。