Descriptif des activités de recherche


My Ph.D. project aims at developing and demonstrating a novel computational approach for quasi-real-time physics-informed simulation of the battery electrode manufacturing process and of the influence of its parameters on the electrode architecture, paving the way to a concrete Battery Industry 4.0. This approach will be supported on surrogate models powered by machine learning (ML) methods, able to mimic the results of physics-based manufacturing process models

Parcours


Expertise


  • Modeling

Implication dans des projets


  • DESTINY

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. Franco
Batteries & Supercaps, 2025

Metaverse For Battery Manufacturing: Connecting Students From Different Geographical Locations To Solve Battery Manufacturing Problems In The Virtual Reality Space

Soorya Saravanan, Utkarsh Vijay, Sophie Tran, Maris Minna Mathew, Desislava Yordanova Apostolova, Inaki Gandarias, Aubin Leclere, Romain Lelong, Alejandro A. Franco
Batteries & Supercaps, 2025

Integration of lithium-ion battery recycling into manufacturing through digitalization: A perspective

Imelda Cardenas-Sierra, Utkarsh Vijay, Frederic Aguesse, Néstor Antuñano, Elixabete Ayerbe, Lukas Gold, Aleksandra Naumann, Laida Otaegui, Nadir Recham, Simon Stier, Sandro Süß, Lalitha Subramanian, Nicolas Vallin, Gabriela Ventura Silva, Nicolas Von Drachenfels, Dennis Weitze, Alejandro A. Franco
Journal of Power Sources, 2025

A Hybrid Modelling Approach Coupling Physics-based Simulation and Deep Learning for Battery Electrode Manufacturing Simulations

Utkarsh Vijay, Diego E. Galvez-Aranda, Franco M. Zanotto, Tan Le-Dinh, Mohammed Alabdali, Mark Asch, Alejandro A. Franco
Energy Storage Materials, 2024

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