Department
Electrical and Computer Engineering
Document Type
Article
Publication Title
Photonics
ISSN
1471-2962
DOI
10.3390/photonics3030044
Publication Date
Fall 1-1-2016
Abstract
An automated design approach using an evolutionary algorithm for the development of quantum cascade lasers (QCLs) is presented. Our algorithmic approach merges computational intelligence techniques with the physics of device structures, representing a design methodology that reduces experimental effort and costs. The algorithm was developed to produce QCLs with a three-well, diagonal-transition active region and a five-well injector region. Specifically, we applied this technique to Alx Ga1−x1- x As/Iny y Ga1−y1- yAs strained active region designs. The algorithmic approach is a non-dominated sorting method using four aggregate objectives: target wavelength, population inversion via longitudinal-optical (LO) phonon extraction, injector level coupling, and an optical gain metric. Analysis indicates that the most plausible device candidates are a result of the optical gain metric and a total aggregate of all objectives. However, design limitations exist in many of the resulting candidates, indicating need for additional objective criteria and parameter limits to improve the application of this and other evolutionary algorithm methods.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Mueller, D.,
&
Triplett, G.
(2016).
Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers.
Photonics, ,
DOI: 10.3390/photonics3030044
https://scholarlycommons.pacific.edu/soecs-facarticles/211