Descriptif des activités de recherche
Research field: Battery Development: Structure modeling, Ampere Software Technology. Goal: My research project is focused on the development of a Generative AI model for the prediction of LIB positive electrode microstructure properties and is 3D representation after the calendering process. Furthermore, the model will incorporate contextual “knowledge” related to the physicochemical rules and constraints of the electrode mesoscale, in order to guide the learning process to a more valid and accurate output. This project aims to develop a tool that integrates mesoscale electrode modeling expertise with advanced AI methods. The goal is to investigate the intricate connections between mesoscale and macroscale battery properties, ultimately enhancing the throughput rate from current methods and speed up the production of high-energy-density cells for EVs.Parcours
Master of Science, MESC+ Program – (UPJV, France. 2022-2024, Erasmus Mundus joint Master Degree)
Research Internship – (IFM Deakin University, Australia. 2024, Investigation of SEI formation on Hard Carbon anodes for SIBs using Ionic liquid electrolytes)
Jr.PM / Business Analyst – (Odoo Technologies, 2021-2022)
Bachelor of Science, Chemical Engineering – (ITESM CEM, Mexico. 2015-2019, Ingenieria quimica administrativa IQA)
Compétences
Electrochemical Impedance Spectroscopy
Cyclic Voltammetry
Coin Cell prototyping
Film electrode manufacturing
Galvanostatic cell cycling
SEM Material Characterization
Project Management Methodologies.
Rietveld Refinement (GSAS-II)
Machine Learning.
Python for Data analysis.
Cyclic Voltammetry
Coin Cell prototyping
Film electrode manufacturing
Galvanostatic cell cycling
SEM Material Characterization
Project Management Methodologies.
Rietveld Refinement (GSAS-II)
Machine Learning.
Python for Data analysis.
Projets en cours
Thèse CIFRE - Génération de nouveaux matériaux pour les batteries avec l’IA/2025-2028/Ampere Software Technology.
