We develop multiscale computational models to simulate the operation principles of electrochemical energy materials, interfaces, components and full devices (batteries, fuel cells, electrolyzers...) as well as their manufacturing. Such multiscale models decribe mechanisms along different spatio-temporal scales. Their goal is to provide interpretation of experimental data, to optimize electrochemical energy devices and to provide advanced design guidelines. Examples of multiscale modeling approaches developed by the team include: using Coarse Grained Molecular Dynamics to predict 3D-resolved electrode mesostructures from their manufacturing simulation, which are then used in electrochemical energy device performance simulators (sequential coupling); using kinetic Monte Carlo (kMC) models resolving interfacial electrochemical kinetics from species concentrations resolved with continuum models describing these species transport in a porous electrode (iterative coupling); using continuum models describing electrochemical reactions and transport mechanisms with temperature-dependent parameters at the porous electrode scale coupled with a continuum model describing thermal management in the cell scale (tight coupling). We develop also hybrid models coupling data-driven models (supported on Artificial Intelligence) and physical models. We carry out advanced experimentations to extract parameters to feed into the models, to validate them and to follow the guidelines proposed by the models: this includes manufacturing battery electrodes, assembling cells and characterizing their textural and electrochemical properties. For performing these experimental activities, we benefit from the free access to the Laboratoire de Réactivité et Chimie des Solides facilities, including the battery manufacturing pilot line of the French Network on Electrochemical Energy Storage (RS2E).