Data-driven Discovery for Robust Optimization of Semiconductor Nanowire Lasers

TL;DR

This paper analyzes a large dataset of semiconductor nanowire lasers to identify key factors affecting their performance, providing a comprehensive roadmap for optimizing nanowire laser design across various materials.

Contribution

It offers the first large-scale statistical comparison of nine nanowire laser systems, revealing that cavity effects are universally critical and proposing optimization strategies based on geometric and reflectivity control.

Findings

Cavity effects are always critical for nanowire laser performance.

Optimizing length and end-facet reflectivities improves laser consistency.

Internal quantum efficiency is important but less universally critical.

Abstract

Active wavelength-scale optoelectronic components are widely used in photonic integrated circuitry, however coherent sources of light -- namely optical lasers -- remain the most challenging component to integrate. Semiconductor nanowire lasers represent a flexible class of light source where each nanowire is both gain material and cavity; however, strong coupling between these properties and the performance leads to inhomogeneity across the population. While this has been studied and optimized for individual material systems, no architecture-wide insight is available. Here, nine nanowire laser material systems are studied and compared using 55,516 nanowire lasers to provide statistically robust insight into performance. These results demonstrate that, while it may be important to optimise internal quantum efficiency for certain materials, cavity effects are always critical. Our study provides a roadmap to optimize the performance of nanowire lasers made from any material: this can be achieved by ensuring a narrow spread of lengths and end-facet reflectivities.