Francisco
Fernandez
Tél. : 0322825335
Descriptif des activités de recherche
I am developing a multi-fidelity modeling approach for the electrode manufacturing process of lithium ion battery cells. For this purpose I combine particle dynamics, discrete element, finite element, and machine learning. This models are obtained with softwares, like LAMMPS, and calibrated, trained, and validated with experimental data.Parcours
PhD (Laboratorio de Energías Sustentables (LaES), Dr. Ezequiel Leiva & Dr. Daniel Barraco, 2019-2024, Computational modeling of lithium-ion battery electrodes)
Compétences
Particle dynamics, discrete element, molecular dynamics and machine learning
Projets en cours
European DIGICELL project
Physics-Assisted Machine Learning for the Simulation of the Slurry Drying in the Manufacturing Process of Battery Electrodes: A Hybrid Time-Dependent VGG16-DEM Model
Diego E. Galvez-Aranda, Francisco Fernandez, Alejandro A. Franco
ACS Applied Materials & Interfaces, 2025
Transfer learning assessment of small datasets relating manufacturing parameters with electrochemical energy cell component properties
Francisco Fernandez, Soorya Saravanan, Rashen Lou Omongos, Javier F. Troncoso, Diego E. Galvez-Aranda and Alejandro Franco
npj computational materials, 2025
