SGER: A Nanoelectromechanical Design for Carbon Nanotube-Based Memory Cells at Finite Temperatures

SGER:有限温度下基于碳纳米管的存储单元的纳米机电设计

基本信息

  • 批准号:
    0630153
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-07-01 至 2008-06-30
  • 项目状态:
    已结题

项目摘要

(Shaoping Xiao)SGER: A Nanoelectromechanical Design for Carbon Nanotube-Based Memory Cells at Finite TemperaturesThe objective of this proposal is analyzing the feasibility of a nanoelectromechanical (NEMS) design for carbon nanotube-based memory cells at finite temperatures through both experimental validation and multiscale simulation. To achieve this objective we will do the following tasks: (1) Design and implementation of an experiment to investigate the oscillatory mechanisms of nanotube-based oscillators in order to confirm the proposed NEMS design. (2) Utilization of a hierarchical multiscale method that incorporates a temperature-related homogenization technique to analyze large models of the proposed NEMS design.The intellectual merits of this proposal lie in the inherent challenge of designing a new NEMS capable of functioning as a memory cell at finite temperatures. The new NEMS will be achieved by coating electrodes on the outer tube of a nano-oscillator so that induced electromagnetic forces can overcome temperature-related interlayer friction. A novel nanotechnology experiment will be designed to study the oscillatory mechanisms and behavior of nanotube-based oscillators at room temperature. The experimental methodology will also serve to accelerate fabrication of the proposed high-speed memory cell design. Furthermore, the proposed experiments will validate a multiscale model of the proposed NEMS so that large memory cell models can be analyzed using a continuum approach in which temperature effects (not only room temperature but also high temperatures) will be considered. Once developed, the multiscale method can be extended as a tool for the design of other nanoscale devices. The broader impact of the proposed effort is the considerable potential for nanotechnology applications, especially in nanoelectronics. With the assistance of numerical modeling and experimental investigation, this project will form a solid basis for fabrication of a novel memory device that could be used as a building block for memory devices and logic gates beyond the capabilities of silicon-based electronics. In addition, the proposed effort also includes a training component for engineering undergraduate and graduate students in this nascent field. The PI will also involve the public education system in nanotechnology, particularly K-12 education. Hence, the proposed research will broadly impact engineering development in nanotechnology.
(肖少平)SGER:有限温度下基于碳纳米管的存储单元的纳机电设计本提案的目的是通过实验验证和多尺度模拟来分析基于碳纳米管的存储单元的纳机电(NEMS)设计在有限温度下的可行性。为了实现这一目标,我们将做以下工作:(1)设计和实施一个实验,以研究基于纳米管的振荡器的振荡机制,以确认所提出的NEMS设计。(2)利用分层多尺度方法,结合了温度相关的均匀化技术,分析拟议NEMS design.The智力优势的建议在于设计一个新的NEMS能够在有限的温度下作为一个存储单元的固有挑战的大模型。新的NEMS将通过在纳米振荡器的外管上涂覆电极来实现,这样感应的电磁力可以克服与温度相关的层间摩擦。本研究将设计一个新颖的奈米科技实验,以研究奈米管振荡器在室温下的振荡机制与行为。实验方法也将有助于加速所提出的高速存储单元设计的制造。此外,所提出的实验将验证多尺度模型的建议NEMS,使大型存储单元模型可以使用连续的方法,其中温度效应(不仅室温,但也高温)将被考虑进行分析。一旦开发,多尺度方法可以扩展为其他纳米器件的设计工具。 拟议努力的更广泛影响是纳米技术应用的巨大潜力,特别是在纳米电子学方面。在数值模拟和实验研究的帮助下,该项目将为制造一种新型存储器件奠定坚实的基础,这种新型存储器件可用作存储器件和逻辑门的构建模块,超出了硅基电子器件的能力。 此外,拟议的努力还包括对这一新生领域的工程本科生和研究生进行培训。 PI还将涉及纳米技术的公共教育系统,特别是K-12教育。因此,拟议的研究将广泛影响纳米技术的工程开发。

项目成果

期刊论文数量(0)
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Shaoping Xiao其他文献

Model-free reinforcement learning for motion planning of autonomous agents with complex tasks in partially observable environments
用于在部分可观察环境中执行复杂任务的自主代理的运动规划的无模型强化学习
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Junchao Li;Mingyu Cai;Zhen Kan;Shaoping Xiao
  • 通讯作者:
    Shaoping Xiao
Molecular dynamics modeling and simulation of lubricant between sliding solids
滑动固体间润滑剂的分子动力学建模与模拟
Peridynamics with Corrected Boundary Conditions and Its Implementation in Multiscale Modeling of Rolling Contact Fatigue
修正边界条件的近场动力学及其在滚动接触疲劳多尺度建模中的实现
  • DOI:
    10.1142/s1756973718410032
  • 发表时间:
    2019-05
  • 期刊:
  • 影响因子:
    1.5
  • 作者:
    Mir Ali Ghaffari;Yanjue Gong;Siamak Attarian;Shaoping Xiao
  • 通讯作者:
    Shaoping Xiao
Reinforcement learning-based motion planning in partially observable environments under ethical constraints
道德约束下部分可观察环境中基于强化学习的运动规划
  • DOI:
    10.1007/s43681-024-00441-6
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Junchao Li;Mingyu Cai;Shaoping Xiao
  • 通讯作者:
    Shaoping Xiao
Studies of TiB and Ti-TiB composites at multiple scales
多尺度 TiB 及 Ti-TiB 复合材料的研究
  • DOI:
    10.1016/j.jallcom.2025.180441
  • 发表时间:
    2025-05-05
  • 期刊:
  • 影响因子:
    6.300
  • 作者:
    Yingbin Chen;Akram Ghaffarigharehbagh;Shaoping Xiao
  • 通讯作者:
    Shaoping Xiao

Shaoping Xiao的其他文献

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{{ truncateString('Shaoping Xiao', 18)}}的其他基金

BRITE Pivot: Learning-based Optimal Control of Streamflow with Potentially Infeasible Time-bound Constraints for Flood Mitigation
BRITE Pivot:基于学习的水流优化控制,具有可能不可行的防洪时限约束
  • 批准号:
    2226936
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
Machine Learning–Enhanced Multiscale Modeling of Spatially Tailored Materials
机器学习 - 空间定制材料的增强多尺度建模
  • 批准号:
    2104383
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant

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用于量子位传感的纳米机电谐振器
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EAGER:合作研究:用于极端温度和恶劣环境传感的石墨烯纳米机电振荡器
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