Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers
Department of Electrical and Computer Engineering, University of the Pacific, Stockton, CA 95211, USA
Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA
Author to whom correspondence should be addressed.
Received: 1 June 2016 / Revised: 16 July 2016 / Accepted: 18 July 2016 / Published: 22 July 2016
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 Al
As 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.
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MDPI and ACS Style
Mueller, D.; Triplett, G. Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers. Photonics 2016, 3, 44.
Mueller D, Triplett G. Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers. Photonics. 2016; 3(3):44.
Mueller, David; Triplett, Gregory. 2016. "Development of a Multi-Objective Evolutionary Algorithm for Strain-Enhanced Quantum Cascade Lasers." Photonics 3, no. 3: 44.
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