Back to Search Start Over

Data‐Driven Discovery for Robust Optimization of Semiconductor Nanowire Lasers.

Authors :
Church, Stephen A.
Vitale, Francesco
Gopakumar, Aswani
Gagrani, Nikita
Zhang, Yunyan
Jiang, Nian
Tan, Hark Hoe
Jagadish, Chennupati
Liu, Huiyun
Joyce, Hannah
Ronning, Carsten
Parkinson, Patrick
Source :
Laser & Photonics Reviews. Oct2024, p1. 9p. 4 Illustrations.
Publication Year :
2024

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 (NWLs) represent a flexible class of light source where each nanowire (NW) 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 NWL material systems are studied and compared using 55,516 NWLs to provide statistically robust insight into performance. These results demonstrate that, while it may be important to optimize internal quantum efficiency for certain materials, cavity effects are always critical. The study provides a roadmap to optimize the performance of NWLs made from any material: this can be achieved by ensuring a narrow spread of lengths and end‐facet reflectivities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18638880
Database :
Academic Search Index
Journal :
Laser & Photonics Reviews
Publication Type :
Academic Journal
Accession number :
180196674
Full Text :
https://doi.org/10.1002/lpor.202401194