Computational study of the thermal conductivity in defective carbon nanostructures

TL;DR

This study uses molecular dynamics simulations to analyze how defects and isotopic impurities significantly reduce the thermal conductivity of carbon nanostructures like nanotubes and graphene, clarifying previous conflicting results.

Contribution

It provides a comprehensive computational analysis of defect effects on thermal conductivity, reconciling prior inconsistent findings and highlighting the impact of isotopic impurities and structural defects.

Findings

Isotopic impurities halve thermal conductivity in perfect nanotubes and graphene.

Structural defects further reduce thermal conductivity in graphene nanoribbons.

The study clarifies discrepancies in previous computational results.

Abstract

We use non-equilibrium molecular dynamics simulations to study the adverse role of defects including isotopic impurities on the thermal conductivity of carbon nanotubes, graphene and graphene nanoribbons. We find that even in structurally perfect nanotubes and graphene, isotopic impurities reduce thermal conductivity by up to one half by decreasing the phonon mean free path. An even larger thermal conductivity reduction, with the same physical origin, occurs in presence of structural defects including vacancies and edges in narrow graphene nanoribbons. Our calculations reconcile results of former studies, which differed by up to an order of magnitude, by identifying limitations of various computational approaches.