Collaborative Research: 2D Ambipolar Machine Learning & Logical Computing Systems

合作研究：2D 双极机器学习

• 批准号: 2154285
• 负责人: Jean Anne Incorvia
• 金额: $ 17万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2154285&HistoricalAwards=false
• 关键词: Collaborative; Research; 2D; Ambipolar; Machine

Emerging materials have novel behaviors that create new opportunities for information processing, especially if the natural behavior of the new materials can be leveraged, rather than trying to engineer them to behave like today’s electronics. In particular, atomically thin materials, also known as two-dimensional (2D) materials, can be naturally ambipolar, i.e. can conduct both electrons and holes. 2D materials also have additional properties, such as hysteresis and variability, that are usually suppressed when used for microelectronics. This interdisciplinary team aims to exploit these unique behaviors of 2D material-based field-effect transistors, and to show they can lead to significant improvements in area, speed, and energy-efficiency for both logical and machine learning (ML) applications. To do so, the team will develop 2D ambipolar materials and device structures, design ambipolar logic families and ML architectures, and experimentally demonstrate small-scale and medium-scale circuit prototypes that prove the utility of these materials as building blocks for the next generation of computing systems. This research will lead to a deeper understanding of the control of ambipolar devices, as well as innovations in circuit and system design, that could be used in additional new implementations of nanotechnology. The project will generate energy-efficient technologies to accomplish computing tasks relevant to many sectors of society, including cybersecurity, education, healthcare, and internet-of-things. The three PIs have designed a concerted plan to integrate the outcomes of the proposed work in education and outreach, including interdisciplinary training of students for a strong and bright workforce; designing lectures to expose a larger population of students to the subjects; and designing hands-on activities to reach K-12 girls to increase diversity in science, technology, engineering, and math.Emerging nanotechnologies exhibit novel switching phenomena that create new opportunities for information processing. In particular, two-dimensional (2D) dual-gate ambipolar field-effect transistors (DG-A-FETs) can be switched between n-type and p-type FET operation, permitting compact computing circuits that leverage the functionality of each individual FET. This project aims to exploit the unique behaviors of DG-A-FETs in logical and machine learning (ML) circuits and systems that provide significant improvements in area, speed, and energy-efficiency. In addition to the dual-gate functionality, the team aims to control and exploit behaviors of emerging 2D materials such as hysteresis and variability to benefit computing. This project will study 2D ambipolar materials and device structures to design several ambipolar logic families and ML architectures, and it will experimentally demonstrate small-scale and medium-scale circuit prototypes that prove the utility of DG-A-FETs as a building block for the next generation of computing systems. This research will lead to a deeper understanding of the dual-gate control of ambipolar devices, as well as innovations in circuit and system design, that could be used in additional new implementations of nanotechnology. The project will generate energy-efficient technologies to accomplish computing tasks relevant to many sectors of society, including cybersecurity, education, healthcare, and internet-of-things. The three PIs have designed a concerted plan to integrate the outcomes of the proposed work in education and outreach, including interdisciplinary training of students for a strong and bright workforce; designing lectures to expose a larger population of students to the subjects; and designing hands-on activities to reach K-12 girls at STEM days on multiple of the PIs’ campuses.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.

新兴材料具有新颖的行为，为信息处理创造了新的机会，特别是如果可以利用新材料的自然行为，而不是试图将它们设计成像今天的电子产品一样。特别地，原子级薄的材料，也称为二维（2D）材料，可以是自然双极的，即可以传导电子和空穴。2D材料还具有其他特性，例如滞后和可变性，这些特性在用于微电子时通常会受到抑制。这个跨学科团队的目标是利用2D材料基场效应晶体管的这些独特行为，并证明它们可以显著改善逻辑和机器学习（ML）应用的面积，速度和能效。为此，该团队将开发2D双极材料和器件结构，设计双极逻辑系列和ML架构，并通过实验展示小规模和中等规模的电路原型，证明这些材料作为下一代计算系统构建模块的实用性。这项研究将导致对双极器件控制的更深入理解，以及电路和系统设计的创新，可用于纳米技术的其他新实现。该项目将产生节能技术，以完成与社会许多部门相关的计算任务，包括网络安全，教育，医疗保健和物联网。这三个方案主管设计了一个协调一致的计划，将拟议的教育和外联工作的成果结合起来，包括对学生进行跨学科培训，以培养一支强大而聪明的劳动力队伍;设计讲座，使更多的学生了解这些科目;并设计动手活动，以达到K-12女孩，以增加科学，技术，工程，新兴的纳米技术展示了新的开关现象，为信息处理创造了新的机会。特别地，二维（2D）双栅极双极场效应晶体管（DG-A-FET）可以在n型FET操作和p型FET操作之间切换，从而允许利用每个单独FET的功能的紧凑计算电路。该项目旨在利用DG-A-FET在逻辑和机器学习（ML）电路和系统中的独特行为，从而在面积，速度和能效方面提供显着改进。除了双栅极功能外，该团队还旨在控制和利用新兴2D材料的行为，如滞后和可变性，以利于计算。该项目将研究2D双极材料和器件结构，以设计几种双极逻辑系列和ML架构，并将实验演示小规模和中等规模的电路原型，证明DG-A-FET作为下一代计算系统的构建模块的实用性。这项研究将导致更深入地了解双极器件的双栅极控制，以及电路和系统设计的创新，可用于纳米技术的其他新实现。该项目将产生节能技术，以完成与社会许多部门相关的计算任务，包括网络安全，教育，医疗保健和物联网。这三个方案主管设计了一个协调一致的计划，将拟议的教育和外联工作的成果结合起来，包括对学生进行跨学科培训，以培养一支强大而聪明的劳动力队伍;设计讲座，使更多的学生了解这些科目;并设计实践活动，以达到K-12名女孩参加了多个PI校园的STEM日。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进行评估，被认为值得支持的搜索.

项目成果

Cascaded Logic Gates Based on High-Performance Ambipolar Dual-Gate WSe 2 Thin Film Transistors

基于高性能双极双栅WSe 2 薄膜晶体管的级联逻辑门

• DOI: 10.1021/acsnano.3c03932
• 发表时间: 2023
• 期刊: ACS Nano
• 影响因子: 17.1
• 作者: Li, Xintong;Zhou, Peng;Hu, Xuan;Rivers, Ethan;Watanabe, Kenji;Taniguchi, Takashi;Akinwande, Deji;Friedman, Joseph S.;Incorvia, Jean Anne
• 通讯作者: Incorvia, Jean Anne