Skip to content

albert-queralto/ml_ijp_deposition_paper

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 

Repository files navigation

Machine learning applied to IJP deposition of REBCO films

This repository serves as a link to the data and jupyter notebooks used in the scientific article: A. Queralto, A. Pacheco, N. Jiménez, S. Ricart, X. Obradors, T. Puig, Defining Inkjet Printing Conditions of Superconducting Cuprate Films through Machine Learning, Journal of Materials Chemistry C, 2022, 10, 6885 - 6895, DOI: https://doi.org/10.1039/D1TC05913K, which can be found at https://digital.csic.es/handle/10261/253916.

In the article, machine learning was used for the optimization of inkjet printing deposition conditions of superconducting cuprate films. We employed a random forest regressor to create two models and used the SHAP library to provide better interpretability to the results obtained.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks