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研究和教育活动，例如内存研究机会、推广计划和科学讲座，针对从高中生、教师到本科生的不同群体下一代内存技术对于解决不断升级的数据具有重要意义。物联网、智能制造和人工智能医疗保健等现代计算和数据驱动应用的容量和能源需求，随着对更高数据密度、更低功耗、更快访问时间的需求，传统内存解决方案正在满足需求。他们的极限。新型存储器件——滑动铁电隧道结，旨在利用原子薄层材料中非易失性滑动铁电的独特优势，包括超低能耗、快速切换速度和超紧凑的占地面积，从而提高存储器件的性能。在范德华材料中发现了一种新型铁电性，即滑动铁电性，这对于人工智能、大数据分析和边缘计算等新兴技术至关重要。原子层可以打破镜像对称性和反演对称性，从而通过相邻原子层之间的相对横向滑动来实现两个相反极化之间的铁电切换，具有超低切换能垒和超快切换时间的优点。范德华材料的原子级清洁表面可用于构建坚固的铁电隧道结，这种新颖的滑动铁电性对于下一代存储器、逻辑和计算技术来说是有希望的。滑动铁电订单，它们在铁电隧道结中的作用，旨在实现具有超快运行速度、超低能耗和多态功能的存储器设备。该项目进行全面研究，包括对滑动铁电响应各种电气和机械边界条件的基本了解，该项目中开发的铁电隧道结器件原型设计、基准测试和度量优化以及多态器件开发将融入本科生和研究生教育，以培养未来 STEM 职业的热情。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。