ATTENTION/WARNING - NE PAS DÉPOSER ICI/DO NOT SUBMIT HERE

Ceci est la version de TEST de DIAL.mem. Veuillez ne pas soumettre votre mémoire sur ce site mais bien à l'URL suivante: 'https://thesis.dial.uclouvain.be'.
This is the TEST version of DIAL.mem. Please use the following URL to submit your master thesis: 'https://thesis.dial.uclouvain.be'.
 

Study of superconductors using machine learning

Sahbi, Najlae
(2023)

Files

Sahbi_22561900_2023.pdf
  • Open access
  • Adobe PDF
  • 2.46 MB
Download
Sahbi_22561900_2023.pdf
  • Open access
  • Adobe PDF
  • 2.46 MB
Download

Details

Supervisors
Gian-Marc
Degree label
Master [120] : ingénieur civil en science des données, à finalité spécialisée
Abstract
The development of simulation and modelling methods has made the creation of databases dedicated to materials research possible. This has enable scientists to apply machine learning algorithms to solid-state materials research. One area of research is the development of superconducting materials. This work analyses more than ten thousand superconducting compounds and uses classification and regression algorithms to predict the temperature at which the electrical resistivity vanishes.