Alignment of Carbon Nanotube Additives for Improved Performance of Magnesium Diboride Superconductors

TL;DR

This paper presents a scalable method to align carbon nanotubes within MgB2 superconductor composites, significantly enhancing their magnetic critical current density and heat dissipation capabilities for advanced applications.

Contribution

It introduces a simple, scalable drawing technique to align CNTs in MgB2 wires, leading to substantial performance improvements over undoped samples.

Findings

Magnetic Jc(H) increased by over an order of magnitude in high fields

Aligned CNTs improve heat transfer and dissipation

Method is scalable and applicable to functional composite materials

Abstract

The rapid progress on MgB2 superconductor since its discovery[1] has made this material a strong competitor to low and high temperature superconductors (HTS) for applications with a great potential to catch the niche market such as in magnetic resonant imaging (MRI). Thanks to the lack of weak links and the two-gap superconductivity of MgB2 [2,3] a number of additives have been successfully used to enhance the critical current density, Jc and the upper critical field, Hc2.[4-12] Carbon nanotubes (CNTs) have unusually electrical, mechanical and thermal properties[13-16] and hence is an ideal component to fabricate composites for improving their performance. To take advantages of the extraordinary properties of CNTs it is important to align CNTs in the composites. Here we report a method of alignment of CNTs in the CNT/MgB2 superconductor composite wires through a readily scalable drawing technique. The aligned CNT doped MgB2 wires show an enhancement in magnetic Jc(H) by more than an order of magnitude in high magnetic fields, compared to the undoped ones. The CNTs have also significantly enhanced the heat transfer and dissipation. CNTs have been used mainly in structural materials, but here the advantage of their use in functional composites is shown and this has wider ramifications for other functional materials.