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
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- PhD (Laboratorio de Energías Sustentables (LaES), Dr. Ezequiel Leiva & Dr. Daniel Barraco, 2019-2024, Computational modeling of lithium-ion battery electrodes)
Expertise
- Particle dynamics
- Discrete element
- Molecular dynamics
- Machine learning
Implication dans des projets
- European DIGICELL project
Dernières publications
Publications
Surrogate Modeling of Lithium-Ion Battery Electrode Manufacturing by Combining Physics-Based Simulation and Deep Learning
Utkarsh Vijay, Francisco Fernandez, Siwar Ben Hadj Ali, Mark Asch, Alejandro A. FrancoBatteries & Supercaps, 2025
3D Resolved Computational Modeling to Simulate the Electrolyte Wetting of a Lithium-Ion Battery Cell with 18650 Format
Emmanuel Yerumoh, Imelda Cardenas-Sierra, Francisco Fernandez, Alejandro A. FrancoBatteries & Supercaps, 2025
A microstructure-resolved model of sodium-ion battery hard carbon electrodes
Imelda Cardenas-Sierra, Francisco Fernandez, Martin Petit, Alejandro A. FrancoJournal of Power Sources, 2025
Digital correlation analysis and optimization of microporous layer through a machine learning workflow for PEMFC applications
Rashen Lou Omongos, Diego E. Galvez-Aranda, Francisco Fernandez, András Vernes, Alejandro A. FrancoJournal of Power Sources, 2025
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