"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"
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:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
人们常说,通往成功的道路是由失败铺成的。对于材料技术来说尤其如此;了解材料如何失败为改进它们铺平了道路。尽管近几十年来通过纳米技术取得了重大突破,但先进材料通常会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。先进结构材料的这种失效是能源、医疗保健和航空航天等广泛工业领域未来技术发展的主要瓶颈。故障建模本身是一个古老的问题-新奇来自于描述故障的数学模型中的细节的准确性。在过去,建模材料故障一直是特设和经验。材料科学家的梦想是将材料的基本细节放入模型中,然后精确地预测其失效,而无需求助于特定参数。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。该项目的目的是采取破坏模型的精确性,并取得明确的进展,对计算材料设计。我们的重点将是在新的纳米结构材料系统使用计算材料科学的故障建模。最先进的原子建模技术将被用来研究各种材料系统的故障:纳米晶体微桁架混合材料,纳米复合材料和纳米工程合金。目前的研究计划旨在实现两个主要目标:(1)开发和实验验证计算模型,可以准确地预测这些材料的性能和故障,而无需诉诸经验参数,(2)建议通过纳米级改性来提高材料性能极限的路线。申请人希望通过有效地将原子失效建模与实验验证和设计优化相结合来开发新的材料设计。
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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:Discovery Grants Program - Individual
-
资助金额:$9.32万
-
财政年份:2022
-
负责人:Singh, ChandraVeer
-
依托单位:
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:Discovery Grants Program - Individual
-
资助金额:$4.66万
-
财政年份:2021
-
负责人:Singh, ChandraVeer
-
依托单位:
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:Discovery Grants Program - Individual
-
资助金额:$4.66万
-
财政年份:2020
-
负责人:Singh, ChandraVeer
-
依托单位:
Probabilistic Machine Learning Driven Discovery and Design of New Materials for Sustainable Energy and Transport
-
批准号:522649-2018
-
项目类别:Discovery Grants Program - Accelerator Supplements
-
资助金额:$5.83万
-
财政年份:2019
-
负责人:Singh, ChandraVeer
-
依托单位:
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:Discovery Grants Program - Individual
-
资助金额:$4.66万
-
财政年份:2019
-
负责人:Singh, ChandraVeer
-
依托单位:
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:Discovery Grants Program - Individual
-
资助金额:$4.66万
-
财政年份:2018
-
负责人:Singh, ChandraVeer
-
依托单位:
Probabilistic Machine Learning Driven Discovery and Design of New Materials for Sustainable Energy and Transport
-
批准号:522649-2018
-
项目类别:Discovery Grants Program - Accelerator Supplements
-
资助金额:$2.91万
-
财政年份:2018
-
负责人:Singh, ChandraVeer
-
依托单位:
Experimental characterization and modeling of mechanical properties of high and intermediate Mn steels
-
批准号:492306-2015
-
项目类别:Engage Grants Program
-
资助金额:$1.82万
-
财政年份:2016
-
负责人:Singh, ChandraVeer
-
依托单位:
"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
-
批准号:418392-2012
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.75万
-
财政年份:2016
-
负责人:Singh, ChandraVeer
-
依托单位:
"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
-
批准号:418392-2012
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.75万
-
财政年份:2015
-
负责人:Singh, ChandraVeer
-
依托单位:
Computational screening of alloy catalysts for methane reforming processes
-
批准号:484867-2015
-
项目类别:Engage Grants Program
-
资助金额:$1.82万
-
财政年份:2015
-
负责人:Singh, ChandraVeer
-
依托单位:
"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
-
批准号:418392-2012
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.75万
-
财政年份:2014
-
负责人:Singh, ChandraVeer
-
依托单位:
"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
-
批准号:418392-2012
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.75万
-
财政年份:2013
-
负责人:Singh, ChandraVeer
-
依托单位:
Computational modeling of age hardening and fracture toughness in Al 7255 alloy
-
批准号:447140-2013
-
项目类别:Engage Grants Program
-
资助金额:$1.82万
-
财政年份:2013
-
负责人:Singh, ChandraVeer
-
依托单位:
"Enhancing the performance limits of nano-structured materials through atomistic modeling, experimental validation and design optimization"
-
批准号:418392-2012
-
项目类别:Discovery Grants Program - Individual
-
资助金额:$1.75万
-
财政年份:2012
-
负责人:Singh, ChandraVeer
-
依托单位:
Deformation and failure mechanisms in multi-layered alloy nanostructures
-
批准号:445054-2012
-
项目类别:Engage Grants Program
-
资助金额:$1.82万
-
财政年份:2012
-
负责人:Singh, ChandraVeer
-
依托单位:
国内基金
海外基金
CuAgSe基热电材料的结构特性与构效关系研究
-
批准号:22375214
-
项目类别:面上项目
-
资助金额:50.00万元
-
批准年份:2023
-
负责人:周钲洋
-
依托单位:
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:2003
-
负责人:单志广
-
依托单位: