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NER: Scalable techniques for massively parallel nanomaterial simulations for long-time behavior

NER: Scalable techniques for massively parallel nanomaterial simulations for long-time behavior
NER:用于长时间行为的大规模并行纳米材料模拟的可扩展技术
批准号:
0403746
负责人:
Ashok Srinivasan
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-06-01 至 2006-05-31

项目摘要

项目成果

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中文摘要
翻译
该提案是响应纳米科学和工程倡议NSF 03-043,类别NER而收到的。研究人员解决了一类涉及碳纳米管组装的问题,其中界面起着关键作用。这类问题涉及到长时间尺度的模拟,其中经典的过渡态理论是不适用的。解决方案策略基于利用大规模并行的力量。通过空间分解的传统并行化将是无效的,因为这将导致细粒度。所提出的努力的目的是在时间并行化使用预测验证的方法。研究的关键问题之一是开发适当的预测因子。从这一奋进的成功结果可以集成多尺度模拟,可以预测材料性能的时间尺度几个数量级大于今天,上述研究工作在纳米涂料,纳米传感器,纳米电子学和纳米复合材料领域的应用。在纳米技术发展的当前阶段,由于尺寸效应,与实验相比,计算(理论,建模和模拟)正在发挥主导作用。广泛使用计算模拟的绊脚石之一是难以实现逼真的时间尺度。这项研究解决了这个关键问题。上面提到的具体应用只是目前设想的纳米技术应用中的几个,对纳米级界面的研究将直接适用于这些应用。对物理学和计算的一些基本理解对更广泛的应用有潜在的用途,包括纳米生物技术。
英文摘要
This proposal was received in response to Nanoscale science and engineering initiative NSF 03-043, category NER. The investigators address a class of problems involving an assembly of carbon nanotubes, wherein interfaces play a key role. This class of problems pertains to long time scale simulations in which classical transition state theories are not applicable. The solution strategy is based on harnessing the power of massive parallelism. Conventional parallelization through spatial decomposition will not be effective since that will lead to fine granularity. The proposed effort is aimed at time-parallelization using a predictor-verifier approach. One of the key research issues is to develop appropriate predictors. Successful results from this endeavor can be integrated with multi-scale simulations that can predict material properties to time scales several orders of magnitude greater than that today.The above research effort has applications in the areas of nanocoatings, nanosensors, nanoelectronics and nanocomposites. In the current stage of the development of nanotechnology, computation (theory, modeling and simulations) is playing a leading role, compared to experiments, because of size effects. One of the stumbling blocks to the widespread use of computational simulations is the difficulty in achieving realistic time scales. This research addresses this key issue. The specific applications mentioned above are but a few of the currently envisioned applications of nanotechnology for which this research on nanoscale interfaces will be directly applicable. Some of the fundamental understanding of both physics and computations has potential use for a wider class of applications, including nano-biotechnology.
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IPA Agreement with University of West Florida 1st year (Srinivasan 2022)
  • 批准号:
    2219049
  • 项目类别:
    Intergovernmental Personnel Award
  • 资助金额:
    $22.27万
  • 财政年份:
    2022
  • 负责人:
    Ashok Srinivasan
  • 依托单位:
Collaborative Research: Petascale Simulation of Viral Infection Propagation Through Air Travel
  • 批准号:
    1640822
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.35万
  • 财政年份:
    2016
  • 负责人:
    Ashok Srinivasan
  • 依托单位:
Collaborative Research: Simulation-Based Policy Analysis for Reducing Ebola Transmission Risk in Air Travel
  • 批准号:
    1525061
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2015
  • 负责人:
    Ashok Srinivasan
  • 依托单位:
MSPA-MCS: Data-Driven Parallelization of Time in Molecular Dynamics Simulations
  • 批准号:
    0626180
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2006
  • 负责人:
    Ashok Srinivasan
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis