课题基金 / 基金详情

"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"

"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
“通过原子建模、实验验证和设计优化提高纳米结构材料的性能极限”
批准号:
418392-2012
负责人:
Singh, ChandraVeer
金额:
$1.75万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
翻译
人们常说成功之路是由失败铺成的。对于材料技术来说尤其如此;了解材料是如何失效的,就能让它们变得更好。尽管近几十年来通过纳米技术取得了重大突破,但先进材料通常在其固有极限的十分之一或更少的情况下失效,我们不明白为什么会这样。这种先进结构材料的失效是在能源、医疗保健和航空航天等广泛工业领域发展未来技术的主要瓶颈。就其本身而言,故障建模是一个古老的问题——新颖性来自于描述故障的数学模型中细节的准确性。过去,材料失效的建模是临时的和经验的。材料科学家的梦想是把材料的基本细节放入一个模型中,然后精确地预测它的失效,而不需要借助于特别的参数。通过计算材料科学和实验验证的明智协调,这个梦想开始变得可以实现。该项目旨在将经验主义从失效建模中剥离出来,并在计算材料设计方面取得明确进展。
英文摘要
It is often remarked that the road to success is paved with failure. This is particularly true for materials technology; understanding how materials fail paves the way to make them better. Despite significant breakthroughs in recent decades through nanotechnology, advanced materials typically fail at one-tenth or less of their intrinsic limits, and we do not understand why this is. This failure of advanced structural materials is a principal bottleneck for developing future technologies in a wide range of industrial sectors such as energy, healthcare and aerospace. By itself failure modeling is an age old problem - the novelty comes from the accuracy of details you put in the mathematical model that describes failure. In the past, modeling material failure has been ad-hoc and empirical. The material scientist's dream is to put in basic details of the material into a model and then predict its failure precisely without resorting to ad-hoc parameters. This dream is starting to become achievable through a judicious coordination of computational materials science and experimental validation. This project aims to take empiricism out of failure modeling and make clear-cut progress towards computational materials design. Our focus will be on failure modeling in novel nano-structured material systems using computational materials science. State of the art atomistic modeling techniques will be employed to study failure in a variety of materials systems: nanocrystalline microtruss hybrid materials, nanocomposites and nano-engineered alloys. The current research program aims to achieve two major goals: (1) Develop and experimentally validate computational models that can accurately predict properties and failure of these materials without resorting to empirical parameters, and (2) Suggest routes for improving material performance limits through modification at the nanometer level. The applicant's hope is to develop novel material designs by efficiently combining atomistic failure modeling with experimental validation and design optimization.
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Probabilistic Machine Learning Driven Discovery and Design of New Materials for Sustainable Energy and Transport
  • 批准号:
    RGPIN-2018-04642
  • 项目类别:
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  • 资助金额:
    $9.32万
  • 财政年份:
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    RGPIN-2018-04642
  • 项目类别:
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  • 资助金额:
    $4.66万
  • 财政年份:
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  • 负责人:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
    2020
  • 负责人:
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  • 依托单位:
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  • 批准号:
    522649-2018
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
  • 资助金额:
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  • 财政年份:
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  • 负责人:
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国内基金
海外基金
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海洋微藻生物固定燃煤烟气中CO2的性能与机理研究
  • 批准号:
    50806049
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2008
  • 负责人:
    赵兵涛
  • 依托单位:
Web服务质量(QoS)控制的策略、模型及其性能评价研究
  • 批准号:
    60373013
  • 项目类别:
    面上项目
  • 资助金额:
    20.0万元
  • 批准年份:
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  • 负责人:
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  • 依托单位: