Reducing the thermal conductivity of carbon nanotubes below the random isotope limit

TL;DR

This paper demonstrates that segmented isotopic disorder in carbon nanotubes can significantly lower their thermal conductivity below the random isotope limit by exploiting phonon scattering across multiple length scales.

Contribution

It introduces a novel approach of segmented isotopic disorder to reduce thermal conductivity in carbon nanotubes, supported by ab-initio calculations.

Findings

Thermal conductivity can be reduced below the uncorrelated disorder limit.

Segmented isotopic patterns influence phonon scattering across different length scales.

The method is experimentally feasible using isotope-engineered fullerenes.

Abstract

We find that introducing segmented isotopic disorder patterns may considerably reduce the thermal conductivity of pristine carbon nanotubes below the uncorrelated disorder value. This is a result of the interplay between different length scales in the phonon scattering process. We use ab-initio atomistic Green's function calculations to quantify the effect of various types of segmentation similar to that experimentally produced by coalescence of isotope-engineered fullerenes.