In that sense, the optimization of the battery electrode manufacturing process is a critical step in terms of its influence on the final battery performance. The electrode manufacturing process can be decomposed overall in three stages (Figure ), one following each other: the slurry preparation through pre-mixing followed by mixing of Active Material (AM) with conductive additives and binders in a solvent, then the coating of the resulting slurry onto a current collector prior its drying, and finally the calendering of the resulting dried electrode. A well-manufactured electrode ensures optimal contact between the AM, the carbon additives and the liquid electrolyte filling the pores, enhancing electronic and ionic transport, and decreasing the overall internal resistances. On the other hand, inconsistencies or defects in the electrode microstructure can lead to uneven electrolyte wetting, increasing side reactions degrading the overall battery cell performance. One important stage along the manufacturing process is the drying phase. During the drying stage, the slurry undergoes processes involving solvents and moisture, which, if are not properly removed, can adversely affect the later electrochemical properties of the electrode. Insufficiently drying the slurry can lead to the presence of residual solvents in the produced electrode, which may result in chemical instability, reduced capacity, and an accelerated degradation during cycling. Furthermore, a properly executed drying helps achieve optimal electrode density and uniform distribution of AM as studied by us in a previous work. In order to have a better control on the electrode properties, it is necessary to enhance our understanding of the drying dynamics. Different drying techniques are being employed to study how it can affect the final performance and efficiency of LIB electrodes. Besides conventional heat drying, other advanced methods such as scalable dry printing, or laser drying are being proposed to reduce production costs, decrease environmental fingerprint, and increase the energy efficiency. In addition to experimental studies, computational tools have emerged as valuable techniques to complement and provide insights on how manufacturing parameters can impact the electrode microstructure. Moreover, the use of computational tools enables researchers to explore a broad range of electrode attributes such as composition and thickness. This not only helps at preserving resources and time but also minimizes the likelihood of errors. In this context, our ARTISTIC research initiative, has proposed several groundbreaking tools, experimentally validated, to understand the complexity among the different steps of the solvent-based manufacturing process and their impact to fabricate optimized electrodes and cells. These tools include computational workflows supported on Coarse-Grained Molecular Dynamics (CGMD) and Discrete Element Method (DEM). Our group's ARTISTIC project pioneered the digitalization of the entire key manufacturing process stages such as: slurry, drying, calendering, and electrolyte infiltration, with a further electrochemical performance evaluation. This digitalization of each one of the stages at the mesoscale was validated with experimental data. Ngandjong et al. from our group, developed the first generation of this workflow able to simulate, with a mesoscopic 3D approach, the electrode manufacturing together with the discharge behaviors of the digitally produced electrodes, and this for 3 different formulations using LiNi0.5Co0.2Mn0.3O2 as AM and Carbon Binder Domains (CBD). Additionally, Lombardo et al., also from our group, developed a 3D drying model capturing additives migration, as well as the role of drying rate in outputting heterogeneous electrodes. The electrode microstructure, defined as the spatial organization and interfaces between AM, CBD and pores within the electrode volume, impacts the practical performance of the manufactured LIB cells. Therefore, these model capabilities to simulate and predict electrode microstructures at the mesoscale as a function of manufacturing parameters such as formulation, solid content, AM particle size distribution, drying rate and calendering degree, are very important at the industrial level, because they allow closing the gap between the material properties and the machinery operation conditions.