Current crowding in nanoscale superconductors within the Ginzburg-Landau model

TL;DR

This study investigates current crowding effects in nanoscale superconductors using the Ginzburg-Landau model, combining numerical simulations and experiments to optimize superconductor design for improved critical current and device efficiency.

Contribution

It introduces a numerical analysis within the GTDGL model and proposes a new meander design to reduce current crowding in superconducting devices.

Findings

Current crowding reduces critical current, but less so in the GTDGL model.

Current redistribution effects counteract crowding, allowing higher fill factors.

Proposed meander design achieves high fill factor with low current crowding.

Abstract

The current density in a superconductor with turnarounds or constrictions is non-uniform due to a geometrical current crowding effect. This effect reduces the critical current in the superconducting structure compared to a straight segment and is of importance when designing superconducting devices. We investigate the current crowding effect in numerical simulations within the generalized time-dependent Ginzburg-Landau (GTDGL) model. The results are validated experimentally by measuring the magnetic field dependence of the critical current in superconducting nanowire structures, similar to those employed in single-photon detector devices. Comparing the results with London theory, we conclude that the reduction in critical current is significantly smaller in the GTDGL model. This difference is attributed to the current redistribution effect, which reduces the current density in weak points of the superconductor and counteracts the current crowding effect. We numerically investigate the effect of fill factor on the critical current in a meander and conclude that the reduction of critical current is low enough to justify fill factors higher than $33\,\%$ for applications where detection efficiency is critical. Finally, we propose a novel meander design which can combine high fill factor and low current crowding.