Using normal modes to calculate and optimize thermal conductivity in functionalized macromolecules

Abstract

The quest for high thermal conductivity materials has led to nanocomposites incorporating macromolecular materials with excellent thermal conductivity, such as carbon nanotubes and graphene nanoribbons, in a matrix of poorer thermal conductivity. To minimize the interface thermal resistance the stiff, incorporated materials can be chemically functionalized with various side chains. We report here an efficient theoretical method using normal modes to calculate the thermal conductivity of such systems and show how the participation ratio of these modes can be used to evaluate different choices for functionalization. We use this method to examine how effective different alkane chains improve the heat flux through a graphene nanosheet.

A comparison of genetic algorithms and simulated annealing in maximizing the thermal conductance of harmonic lattices

“…Two methods, a genetic algorithm and simulated annealing, were implemented to obtain thermally conductive 1-dimensional chains. The objective function was evaluated using the Green's function method outlined in [12]. It was shown that sets of hyperparameters can be selected after testing the performance of the algorithm(s) on a grid.…”

“…We calculate the thermal conductivity of molecules through the Green's function method detailed in [12]. In such an approach, the molecules under study are relaxed to equilibrium and their effective spring constants between the atoms are determined.…”

Improving the thermal conductivity of epoxy resin by the addition of a mixture of graphite nanoplatelets and silicon carbide microparticles

“…Recently, experimental studies have been stimulated to address the heat transport in the GNP/epoxy composites , and theoretical analysis, e.g. based on effective medium model [2,11] and normal modes [27], was also conducted to analyze the effective thermal conductivity of the GNP/epoxy composites. Owing to the high thermal conductivity (250 W/(m·K) in basal plane and 80 W/(m·K) across basal plane at room temperature [3]), two-dimensional (2-D) structure and high aspect ratio of GNP, GNPs were found to be more efficient than carbon black (CB) nanoparticles [3][4][5], single-walled CNTs (SWCNTs) [4][5][6] and multiwalled CNTs (MWCNTs) [7,17] in improving the thermal conductivity of epoxy.…”