[SY-H10] Thermal transport in polymer-based nanocomposite materials across multiple scales
The improved physical properties of composite materials are revolutionizing many fields, from automotive to biomedical industries, from electronics to space applications. Composites are typically made of polymeric matrices reinforced with macroscopic fillers, e.g. carbon fibres. Nowadays, scientists are investigating the possibility of introducing nanostructured fillers as wells, to further enhance the effective properties of composites. Carbon nanostructures such as carbon nanotubes or graphene are particularly suitable for that, because of their outstanding mechanical, electrical and thermal properties. However, the resulting nanocomposites are characterised by properties at scales spanning from nano to macro and, therefore, should be simulated by sophisticated multi-scale approaches.
In this work, an original multi-scale approach to the thermal transport in polymer-based materials reinforced with carbon nanotubes or graphene sheets is presented and experimentally validated. First, molecular dynamics simulations are adopted to compute the thermal boundary resistance at the polymer-nanofiller and nanofiller-nanofiller interfaces, according to the different structural and chemical characteristics of the nanocomposite. The thermal conductivities of nanofillers and polymer matrix are computed as well, with molecular precision. Second, these nanoscale transport properties are used to estimate the effective thermal conductivity of nanocomposite, thanks to a mesoscopic simulation approach based on Dijkstra algorithm. The accuracy of the code is verified against a finite element model. After that, sensitivity analyses are carried out to investigate the impact of different fillers on the effective thermal conductivity of nanocomposite. Modelling results are then validated by experiments, and the most severe bottlenecks in the thermal conductivity enhancement of nanocomposites are finally identified.
Our work provides guidelines towards the technical-economical optimization of novel nanostructured materials with tunable thermal properties, with the aim to transfer them from lab experiments to industrial exploitation.
This work has received funding from the European Union’s Horizon 2020 research and innovation program MODCOMP under grant agreement N. 685844.
In this work, an original multi-scale approach to the thermal transport in polymer-based materials reinforced with carbon nanotubes or graphene sheets is presented and experimentally validated. First, molecular dynamics simulations are adopted to compute the thermal boundary resistance at the polymer-nanofiller and nanofiller-nanofiller interfaces, according to the different structural and chemical characteristics of the nanocomposite. The thermal conductivities of nanofillers and polymer matrix are computed as well, with molecular precision. Second, these nanoscale transport properties are used to estimate the effective thermal conductivity of nanocomposite, thanks to a mesoscopic simulation approach based on Dijkstra algorithm. The accuracy of the code is verified against a finite element model. After that, sensitivity analyses are carried out to investigate the impact of different fillers on the effective thermal conductivity of nanocomposite. Modelling results are then validated by experiments, and the most severe bottlenecks in the thermal conductivity enhancement of nanocomposites are finally identified.
Our work provides guidelines towards the technical-economical optimization of novel nanostructured materials with tunable thermal properties, with the aim to transfer them from lab experiments to industrial exploitation.
This work has received funding from the European Union’s Horizon 2020 research and innovation program MODCOMP under grant agreement N. 685844.