Improving the understanding of filler-modified multifunctional polymers for conventional and renewable energy sector applications

提高对填料改性多功能聚合物在传统和可再生能源领域应用的理解

• 批准号: RGPIN-2016-04650
• 负责人: Mertiny, Pierre
• 金额: $ 2.11万
• 依托单位: University of Alberta
• 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=638557
• 关键词: Improving; understanding; filler; modified; multifunctional

This study will investigate the material and structure multifunctionality of polymer composites. Specifically, the research will focus on the prediction and model validation of binary and ternary micro- and nano-filler modified polymers, which includes their electrical, thermal and mechanical properties. For example, fillers such as graphene have been used in past projects in conjunction with epoxy and polyurethane polymers. In this research program, multifunctional polymer composites are defined as materials with enhanced performance and/or novel characteristics. The goal is to achieve specific property enhancements that do not occur at the detriment to other important material characteristics (e.g. improved thermal conductivity with reduced mechanical performance). In previous studies, the applicant’s group has investigated novel concepts for structural health monitoring in pressure equipment using filler-modified polymers. This work has high industrial as well as scientific relevance. Strong research support has been received for applied research aspects such as structure design and manufacturing. Through the current grant proposal, it is sought to enhance fundamental research on this subject matter, which offers considerable opportunities for broadening the understanding for multifunctional composite design and manufacturing. In this context, it is proposed to expand modelling work for the prediction of mechanical and physical properties of filler-modified polymers using stochastic (e.g. Monte Carlo) and numerical (e.g. finite element) approaches. Such techniques generally assume a homogeneous filler dispersion and distribution. However, emerging experimental studies suggest that significant property enhancements can be achieved by some degree of filler aggregation/flocculation and alignment. It is currently unclear what degree of aggregation and alignment leads to maximum property enhancements. To capture these effects, it is proposed to develop multi-domain modelling approaches. Processes that are directly related to individual filler particles, such as electron tunneling in the context of electrical conductivity, are conveniently evaluated using a nano-domain. Through the addition of a meso-domain modelling approach, aggregation/flocculation effects are to be captured allowing for the prediction of the bulk material behaviour through a representative volume unit. This unit will be composed from smaller sub-domains that facilitate filler densification for certain regions. The proposed work is of considerable scientific relevance, which is likely to yield the dissemination of notable research findings as well as guide the applied research. The required computational and experimental facilities are available. The support sought through this grant will provide training for four graduate and up to four undergraduate students.

这项研究将研究聚合物公司的材料和结构多功能性。具体而言，该研究将集中于二元和三元微型和纳米填充剂修饰的聚合物的预测和模型验证，其中包括其电气，热和机械性能。例如，诸如石墨烯之类的填料与环氧树脂和聚氨酯聚合物结合使用。在该研究计划中，多功能聚合物公司被定义为具有增强性能和/或新颖特征的材料。目的是实现在损害其他重要材料特征（例如，机械性能降低的导热率）时不会发生的特定性质增强。在先前的研究中，申请人小组研究了使用填充剂改装的聚合物在压力设备中进行结构健康监测的新颖概念。这项工作具有很高的工业和科学意义。已经获得了针对结构设计和制造等应用研究方面的强大研究支持。通过当前的赠款提案，人们可​​以感觉到这一主题的基本研究，该研究为扩大对多功能复合设计和制造的理解提供了考虑机会。在这种情况下，建议使用随机（例如Monte Carlo）和数值（例如有限元）方法来扩展填充聚合物的机械和物理特性的建模工作。这样的技术通常假设均质填充物分散和分布。但是，新兴的实验研究表明，可以通过一定程度的填充/拼接和比对来实现显着的性质增强。目前尚不清楚汇总和对齐程度的程度最大。为了捕获这些效果，建议开发多域建模方法。与单个填充颗粒直接相关的过程，例如在电导率的背景下进行电子隧穿，使用纳米域进行了方便评估。通过添加中域建模方法，应捕获聚集/拼接效应，以通过代表性体积单位预测散装物质行为。该单元将由较小的子域组成，可促进某些区域的填充剂致密化。拟议的工作是考虑到科学相关性的，这很可能会引起著名研究结果的传播，并指导应用研究。提供所需的计算和实验设施。通过这笔赠款所感知的支持将为四个研究生和最多四个本科生提供培训。