Published April 22, 2024
| Version v1
Dataset
Open
Potential profile, design parameters and thermal properties of asymmetric double-barrier heterostructures based on AlGaAs simulated with NEGF+H
Contributors
Data collector:
Data manager:
Research groups:
Supervisors:
-
1.
Universidade de Santiago de Compostela
-
2.
Institut des Matériaux, de Microélectronique et des Nanosciences de Provence
Description
This is a repository for assymmetric double barrier heterostructures that were simulated using the NEGF coupled with the heat equation described in BESCOND:Phys. Rev. Applied:2020.
- Relation between the csv columns and variables:
| Column | Variable | Definition |
| 1 | Lb1 [nm] | First barrier length |
| 2 | LQW [nm] | Quantum well length |
| 3 | Lb2 [nm] | Second barrier length |
| 4 | γ | Fraction on Al in AlGaAs alloy |
| 5 | V [V] | Bias between emitter and collector |
| 6 | CP [W/m²] | Cooling power |
| 7 | Te [K] | Electron temperature in the Quantum well |
| 8 | W1 [eV] | First activation energy |
| 9 | W2 [eV] | Second activation energy |
| 10-1525 | PP [eV] | Potential profile |
These data was used to feed the machine learning workflow shared in https://gitlab.citius.usc.es/modev/coolML.
This work was supported by the Spanish MICINN/AEI, Xunta de Galicia, and FEDER Funds under Grant RYC-2017-23312, Grant PID2019-104834GB-I00, Grant PID2022-141623NB-I00, Grant PID2022-142709OB-C21/PID2022-142709OA-C22, Grant ED431F 2020/008, Grant ED431C 2022/16 and GELATO ANR project (ANR-21-CE50-0017).
Files
Cooling_device.png
Additional details
Software
- Repository URL
- https://gitlab.citius.usc.es/modev/coolML
- Programming language
- Python
- Development Status
- Active