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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683126
• 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.**

本研究将研究聚合物复合材料的材料和结构多功能性。具体来说，该研究将重点关注二元和三元微米和纳米填料改性聚合物的预测和模型验证，包括其电学、热学和机械性能。例如，石墨烯等填料在过去的项目中已与环氧树脂和聚氨酯聚合物一起使用。在该研究项目中，多功能聚合物复合材料被定义为具有增强性能和/或新颖特性的材料。目标是实现特定性能的增强，但不会损害其他重要的材料特性（例如，提高导热性并降低机械性能）。在之前的研究中，申请人的小组研究了使用填料改性聚合物进行压力设备结构健康监测的新概念。这项工作具有很高的工业和科学相关性。结构设计和制造等应用研究方面得到了强有力的研究支持。通过当前的拨款提案，旨在加强这一主题的基础研究，这为拓宽对多功能复合材料设计和制造的理解提供了相当多的机会。在这种情况下，建议使用随机（例如蒙特卡罗）和数值（例如有限元）方法扩展用于预测填料改性聚合物的机械和物理性能的建模工作。此类技术通常假定填料分散和分布均匀。然而，新兴的实验研究表明，通过某种程度的填料聚集/絮凝和排列可以实现显着的性能增强。目前还不清楚什么程度的聚合和对齐可以最大程度地增强性能。为了捕获这些影响，建议开发多域建模方法。使用纳米域可以方便地评估与单个填料颗粒直接相关的过程，例如导电性背景下的电子隧道效应。通过添加介观域建模方法，可以捕获聚集/絮凝效应，从而可以通过代表性体积单位预测散装材料的行为。该单元将由较小的子域组成，这些子域有助于某些区域的填料致密化。拟议的工作具有相当大的科学相关性，可能会传播著名的研究成果并指导应用研究。所需的计算和实验设施已具备。通过这笔赠款寻求的支持将为四名研究生和最多四名本科生提供培训。**