Self-Consistent Optimization of Multi-Quantum Well Structures by a Genetic Algorithm

This work presents a self-consistent optimization of multi-quantum well based nanostructured semiconductors. A Genetic Algorithm is used for the search module. The simulation module is based on the self-consistent solution of the coupled Poisson and Schrödinger equations by using the finite-element...

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Veröffentlicht in:	IEEE transactions on magnetics 2010-08, Vol.46 (8), p.2759-2762
Hauptverfasser:	Passaro, Angelo, Tanaka, Roberto Yuji, Muraro, Ademar, Vieira, Gustavo Soares, Abe, Nancy Mieko
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer simulation Cross-disciplinary physics: materials science rheology Design optimization Exact sciences and technology Gallium arsenide Genetic algorithms Magnetism Materials science Mathematical analysis Modules Nanostructure Optimization optimization methods Other topics in materials science Photodetectors Physics Poisson equations Quantum cascade lasers Quantum dot lasers quantum effect semiconductor devices Quantum well devices quantum wells Schroedinger equation Semiconductor device doping Semiconductor materials Semiconductors
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Beschreibung
Zusammenfassung:	This work presents a self-consistent optimization of multi-quantum well based nanostructured semiconductors. A Genetic Algorithm is used for the search module. The simulation module is based on the self-consistent solution of the coupled Poisson and Schrödinger equations by using the finite-element method. The results of two case tests are presented and discussed.
ISSN:	0018-9464 1941-0069
DOI:	10.1109/TMAG.2010.2044151