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
- 2020-2022: Masters in Advanced Material Innovative Recycling by EIT Raw Materials
i. 2020-2021: Masters in Chemistry from University of Bordeaux, France
ii. 2021-2022: Masters in Circular Economy speciality in minerals and construction productsfrom Universidad Politecnica de Madrid, Spain
- 2016, B.Sc.(Research) from Indian Institute of Science, Bangalore, India
Projets en cours
DESTINY Ph.D Programme : An European Doctorate Programme (2022-2025).
Supported and co-funded by the European Commission through the Horizon 2020 Marie Sklodowska-Curie COFUND PhD Programme (Grant Agreement # 945357)
Time-Dependent Deep Learning Manufacturing Process Model for Battery Electrode Microstructure Prediction
Diego E. Galvez-Aranda, Tan Le Dinh, Utkarsh Vijay, Franco M. Zanotto, Alejandro A. Franco
Advanced Energy Materials, 2024