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

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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.