Optimization of vortex pinning by nanoparticles using simulations of time-dependent Ginzburg-Landau model

TL;DR

This paper uses large-scale simulations of the time-dependent Ginzburg-Landau model to optimize nanoparticle size and density for enhancing vortex pinning and critical current in superconductors under various magnetic fields.

Contribution

It provides a systematic numerical approach to determine optimal nanoparticle parameters for maximizing critical current in superconductors.

Findings

Optimal particle volume fraction is 15-23% for maximum critical current.

Optimal particle diameter decreases with increasing magnetic field.

Critical current peaks at specific particle densities depending on size and field.

Abstract

Introducing nanoparticles into superconducting materials has emerged as an efficient route to enhance their current-carrying capability. We address the problem of optimizing vortex pinning landscape for randomly distributed metallic spherical inclusions using large-scale numerical simulations of time-dependent Ginzburg-Landau equations. We found the size and density of particles for which the highest critical current is realized in a fixed magnetic field. For each particle size and magnetic field, the critical current reaches a maximum value at a certain particle density, which typically corresponds to 15-23% of the total volume being replaced by nonsuperconducting material. For fixed diameter, this optimal particle density increases with the magnetic field. Moreover, we found that the optimal particle diameter slowly decreases with the magnetic field from 4.5 to 2.5 coherence lengths at a given temperature. This result shows that pinning landscapes have to be designed for specific applications taking into account relevant magnetic field scales.