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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01bk128f226
Title: QCL Dataset, 10 Layer Structure, Tolerance [-5, +20] Å, Electric Field [10,10,150] kV/cm
Contributors: Correa Hernandez, Andres
Gmachl, Claire F.
Keywords: Quantum Cascade Laser, Mid-Infrared, Machine Learning, Figure of Merit
Issue Date: 20-Mar-2024
Publisher: Princeton University
Related Publication: https://doi.org/10.34770/bps9-7152
Abstract: A dataset of 2400 quantum cascade structures at 15 electric field iterations, for a total of 36000 unique designs. The structures are generated by randomly altering a starting 10-layer design of alternating Al0.48In0.52As barrier material and In0.53Ga0.47As well material, with layer thickness sequence of 9/57/11/54/12/45/25/34/14/33 Angstroms (starting with well material). The random tolerance range is from -5 to +20 Angstroms in 5 Angstrom increments. The laser transition Figure of Merit, among other quantities of interest, is identified for each design using a method found in: A. C. Hernandez, M. Lyu and C. F. Gmachl, "Generating Quantum Cascade Laser Datasets for Applications in Machine Learning," 2022 IEEE Photonics Society Summer Topicals Meeting Series (SUM), 2022, pp. 1-2, doi: 10.1109/SUM53465.2022.9858281
URI: http://arks.princeton.edu/ark:/88435/dsp01bk128f226
Https://doi.org/10.34770/d644-0c85
Referenced By: doi: 10.1109/SUM53465.2022.9858281
Appears in Collections:EE Research Data Sets

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QCL-layer_10-4rep-rand-m5d5p20A-efield_10-10-150-v22-dataset.csv9.83 MBCSVView/Download


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