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Fully automatized quantum cascade laser design by genetic optimization
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View: Figures


Image of FIG. 1.
FIG. 1.

Automatic optimization of a mid-infrared 1% strain-compensated structure. All the individuals were sorted, the first ones with the higher merit function values. The graph shows a clear optimization for all the individuals in the best pool as a function of the generation. Inset: The best individuals of the 13th generation. The selected and discarded designs are highlighted.

Image of FIG. 2.
FIG. 2.

Conduction band diagram of a period of the reference design (top panel) and the genetically modified design (bottom panel) at an average field of 75 kV/cm. The moduli squared of the relevant envelop wavefunctions are shown.

Image of FIG. 3.
FIG. 3.

Energy separation as function of the electric field between the upper lasing state 4 and the injector ground state i’ (top panel) and between the first excited state 5 and the upper lasing state 4(bottom panel) for both the reference and the optimized design.

Image of FIG. 4.
FIG. 4.

Simulated electric field (left axis) and output power (right axis) as function of the current density for the reference and the optimized designs. The discontinuities in the curves are due to the alignment of states that are weakly coupled. The simulation of the structures has been performed using two separate bases one for the active region and one for the injection region. This allows to suppress most of these model instabilities but some minor ones are still present.

Image of FIG. 5.
FIG. 5.

Top panel: Measured voltage and output power as function of the current density for the reference and the optimized designs in the case of 8.5 μm wide and 4.9 mm long devices measured in pulsed operation (100 ns pulse width, 100 kHz repetition rate). Emission wavelength is centered at ∼4.5 μm. Bottom panel: Comparison between the wallplug efficiency for the two designs. The effect of growth optimization on the reference design is also presented (dashed line) from Ref. 1, showing the possibility to obtain further improvement of the optimized design by analyzing the growth conditions.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Fully automatized quantum cascade laser design by genetic optimization