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
- 来源:
- 关键词:
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.
(Shaoping Xiao)SGER:该提案有限温度目标的基于碳纳米管的纳米电机力学设计是通过两种实验性验证和多种实验性模拟的有限性温度下的碳纳米管设计的纳米机电(NEMS)设计的可行性。为了实现这一目标,我们将执行以下任务:(1)设计和实施实验,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)利用一种层次多尺度方法,该方法结合了与温度相关的均质化技术来分析所提出的NEMS设计的大型模型。该提案的智力优点在于设计能够在有限温度下充当存储细胞的新NEMS的固有挑战。新的NEM将通过在纳米振荡器的外管上涂层电极来实现,以便诱导的电磁力可以克服与温度相关的层间摩擦。将设计一个新型的纳米技术实验,以研究室温下基于纳米管的振荡器的振荡机制和行为。实验方法还将加速提出的高速记忆细胞设计的制造。此外,提出的实验将验证提出的NEMS的多尺度模型,以便可以使用连续方法分析大型记忆细胞模型,在该方法中,将考虑温度效应(不仅室温和高温)。一旦开发,多尺度方法就可以作为设计其他纳米级设备的工具扩展。 拟议的努力的更广泛影响是纳米技术应用的巨大潜力,尤其是在纳米电子学中。在数值建模和实验研究的帮助下,该项目将为制造新型存储设备的制造构成可靠的基础,该设备可以用作内存设备和逻辑门的组成部分,而不是基于硅的电子设备的功能。 此外,拟议的努力还包括一个新生领域的工程本科生和研究生的培训组成部分。 PI还将涉及纳米技术的公共教育系统,尤其是K-12教育。因此,拟议的研究将广泛影响纳米技术的工程发展。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(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
- DOI:
10.1142/s2424913017500096 - 发表时间:
2017-06 - 期刊:
- 影响因子:0
- 作者:
Mir Ali Ghaffari;Yan Zhang;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
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
Intelligent Agricultural Management Considering N2O Emission and Climate Variability with Uncertainties
考虑N2O排放和不确定性气候变化的智能农业管理
- DOI:
10.48550/arxiv.2402.08832 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Zhaoan Wang;Shaoping Xiao;Jun Wang;Ashwin Parab;Shivam Patel - 通讯作者:
Shivam Patel
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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