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| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Lyu, Ming | - |
| dc.contributor.author | Hernandez, Andres Correa | - |
| dc.contributor.author | Gmachl, Claire F. | - |
| dc.date.accessioned | 2023-12-07T17:24:10Z | - |
| dc.date.available | 2023-12-07T17:24:10Z | - |
| dc.date.created | 2023-04-17 | - |
| dc.date.issued | 2023-12 | - |
| dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp012f75rc341 | - |
| dc.identifier.uri | https://doi.org/10.34770/r7nr-ee50 | - |
| dc.description | The method for building QC datasets and identifying the laser transition for a design is referenced in [1] 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. | en_US |
| dc.description.abstract | This dataset contains 1800 quantum cascade (QC) structures generated by randomly modifying an initial 10-layer design in the tolerance range of -2 to +3 Angstroms at an applied electric field range of 0 to 150 kV/cm (in 10 kV/cm increments). One structure at one electric field is one design, thus there are 27000 unique designs, represented as a row in the dataset. The layer thicknesses (in angstroms) and the electric field are inputs which get evaluated using a Schrödinger solver, ErwinJr2, to identify the laser transition Figure of Merit (fom*), among other reported outputs. | en_US |
| dc.description.sponsorship | Schmidt DataX Fund at Princeton University, National Science Foundation under Grant No. DGE-2039656, and the Center for Statistics and Machine Learning at Princeton University through the support of Microsoft | en_US |
| dc.description.tableofcontents | QCL-layer_10-4rep-rand-m2A_3A-efield_0-10-150-v22-dataset.csv, README.txt | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Princeton University | en_US |
| dc.rights | CC-BY 4.0 | en_US |
| dc.subject | quantum cascade laser, mid-infrared, figure of merit | en_US |
| dc.title | QCL Dataset, 10 Layer Structure, Tolerance [-2, +3] A, Electric Field [0,10,150] kV/cm | en_US |
| dc.title.alternative | QCL-layer_10-4rep-rand-m2A_3A-efield_0-10-150-v22-dataset | en_US |
| dc.type | Dataset | en_US |
| Appears in Collections: | EE Research Data Sets | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| README.txt | 2.71 kB | Text | View/Download | |
| QCL-layer_10-4rep-rand-m2A_3A-efield_0-10-150-v22-dataset.csv | 7.38 MB | CSV | View/Download |
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