Modelling of the electrical and thermal transport mechanisms in graphene nano-modified polymer compounds and fibres

石墨烯是碳的一种二维同素异形体，在复合材料领域受到了大量的研究活动，特别是关于石墨烯修饰的纳米复合材料（如化合物和纤维）的无数已发表的研究。然而，目前还没有石墨烯与周围聚合物相互作用的定性和定量模型。缺乏对纳米复合材料结构形成的了解阻碍了高性能石墨烯改性纤维材料的发展。因此，GraSage项目的主要目标是开发一个模型，描述在纤维熔融纺丝过程中聚合物基体中石墨烯的取向和结构相互作用，并能够预测纳米复合材料的电学、热学和机械性能。当碳纳米管（CNTs）和炭黑与聚合物基体结合时，纺丝条件对纳米材料在纤维基体中的取向有很大影响，从而导致不同的力学、热学和电学性能。当使用还原氧化石墨烯（rGO）和非无缺陷型石墨烯作为改性剂时，这种效果尚未量化。因此，将以实验设计（DOE）的形式对石墨烯改性聚合物化合物和纤维进行实验研究。所获得的纤维将根据其结构、机械、热学和电学性能进行表征。在实验研究的同时，纳米复合材料的制造过程将在纳米和微观尺度上进行模拟，以深入了解聚合物/石墨烯界面的结构和热电性能。因此，将在纳米尺度上追求反应分子动力学方法，并在此基础上，采用自主创建有限元网格的手段进行微尺度模拟。这些在小尺度上获得的预测将被转移到（复合材料或纤维）材料、其加工和最终性能之间的定量模型中。建模将通过对DOE试验的分析，以数学方程的形式进行，并进一步通过可调节神经元网络和模糊逻辑的形式生成人工智能，这将有助于设计未来的复合材料和纤维制造工艺。该项目将对石墨烯纳米复合材料和纤维的热学和电学性能进行多尺度定量预测，并了解其改进的潜在机制。由于定制复合材料和纤维产品的可用性，获得的知识将加强石墨烯复合材料从实验室到工业规模的技术转移。本项目获得的基础知识将为减少石墨烯改性纳米工程聚合物复合材料的研究工作量和产品开发时间奠定基础。

Graphene, a two-dimensional allotrope of carbon, has been subject to tremendous research activities in the field of composite materials as highlighted by countless published studies focusing on graphene-modified nano-composite materials like compounds and fibres. However, no qualitative and quantitative model of the interactions between graphene and the surrounding polymer is currently available. The lack of knowledge about structural formation in nanocomposites does impede the development of high-performance graphene-modified fibre materials. Thus, the main goal of the GraSage project is to develop a model describing the orientation and structural interaction of graphene within the polymer matrix during a fibre melt-spinning process and able to predict the electrical , thermal and mechanical properties of the nanocomposites.When carbon nanotubes (CNTs) and carbon black are combined with a polymer matrix, the spinning conditions have great influence on the orientation of the nano-materials in a fibre matrix leading to dif-ferent mechanical, thermal and electrical properties. Such effects are not yet quantified when reduced graphene oxide (rGO) and not defect-free type graphene is used as a modifier. Consequently, an exper-imental study in the form of a design of experiments (DOE) on graphene-modified polymeric compounds and fibres will be performed. The obtained fibres will be characterized with respect to their structural, mechanical, thermal and electrical properties.Parallel to the experimental study, the fabrication process of the nanocomposites will be simulated at the nano- and microscales to provide an in-depth view of the structure and thermo-electrical properties of the polymer/graphene interface. Therefore, a reactive molecular dynamics approach will be pursued on nano-scale, and basing on that, means of independently created FE meshes will be applied for micro-scale simulation. These predictions obtained at small scales will then be transferred to quantitative models between the (composite or fibre) material, its processing and the resulting properties. Modeling will be performed in terms of mathematical equations via analysis of the DOE trials and furthermore by genera-tion of artificial intelligence in the form of adjustable neuronal nets and fuzzy logics which will help in the design of future composite and fibre fabrication processes.This project will result in multiscale quantitative predictions of the thermal and electrical properties of graphene nanocomposites and fibres and in understanding of the underlying mechanisms for their improvement. The obtained knowledge will strengthen the technology transfer of graphene composites from lab- to industrial scale thanks to the availability of tailor-made composite- and fibre products. The fundamental knowledge acquired in this project will serve as a basis for reduction of research efforts and product development time of graphene-modified nano engineered polymer composites.