"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: University of Toronto
• 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
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638119
• 关键词: Enhancing; performance; limits; nano; structured

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.

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。我们的重点将是利用计算材料科学对新型纳米结构材料系统的失效建模。最先进的原子建模技术将被用于研究各种材料系统的失效：纳米晶微桁架混合材料、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，可以准确预测这些材料的性能和失效，而无需诉诸经验参数；(2)提出通过纳米级修改提高材料性能极限的途径。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颖的材料设计。