Lithium‐ion battery (LIB) manufacturing requires a pilot stage that optimizes its characteristics. However, this process is costly and time‐consuming. One way to overcome this is to use a set of computational models that act as a digital twin of the pilot line, exchanging information in real‐time that can be compared with measurements to correct parameters. Here we discuss the parameters involved in each step of LIB manufacturing, show available computational modeling approaches, and discuss details about practical implementation in terms of software. Then, we analyze these parameters regarding their criticality for modeling set‐up and validation, measurement accuracy, and rapidity. Presenting this in an understandable format allows identifying missing aspects, remaining challenges, and opportunities for the emergence of pilot lines integrating digital twins. Finally, we present the challenges of managing the data produced by these models. As a snapshot of the state‐of‐the‐art, this work is an initial step towards digitalizing battery manufacturing pilot lines, paving the way toward autonomous optimization.

Our ARTISTIC project was born in 2018 to improve the efficiency of lithium‐ion battery cell manufacturing process through computational modelling, allowing the research and development of new digital tools to accelerate the optimization of this process. Thanks to the development and use of innovative numerical models, machine learning algorithms and virtual and mixed reality tools, we could significantly advance the understanding of manufacturing/battery cell performance relationships. However, scientific research by itself is not enough to bring innovations into practical applications for society. The creation of spin‐offs or start‐ups can ease the transition from research to application, since it allows scaling up the research outputs into products or services ready‐to‐use by the customers. In this Concept, we discuss the benefits of this transition, we introduce the research findings obtained in the last years within the framework of our ARTISTIC project, and our actions to move from our research to industrial products.

Networks of coupled oscillators show a wealth of fascinating dynamics and are capable of storing and processing information. In biological and social networks, the coupling is often asymmetric. We use the chirality of rotating spiral waves to introduce this asymmetry in an excitable reaction-diffusion model. The individual vortices are pinned to unexcitable disks and arranged at a constant spacing $L$ along straight lines or simple geometric patterns. In the case of periodic boundaries or pinning disks arranged along the edge of a closed shape, small $L$ values lead to synchronization via repeated wave collisions. The rate of synchronization as a function of $L$ shows a single maximum and is determined by the dispersion behavior of a continuous wave train traveling along the system boundary. For finite systems, spirals are affected by their upstream neighbor, and a single dominant spiral exists along each chain. Specific initial conditions can decouple neighboring vortices even for small $L$ values. We also present a time-delay differential equation that reproduces the phase dynamics in periodic systems.

Solvent‐free (SF) manufacturing of lithium‐ion battery (LIB) electrodes is safer and more environmentally friendly than the traditional slurry casting approach. However, as a young technique, SF manufacturing is under development of its pathways and operation conditions. In different SF processes reported in literature, extrusion is a common step. A detailed model of this process would be extremely computationally demanding. This work proposes a novel simplified discrete element model at the mesoscopic scale for the extrusion during SF manufacturing of LIB electrodes. In addition to active material particles, we consider fluid‐like solid particles to approximate the molten polymer and the carbon additive phases. The formulation and other process parameters are taken from our experimental facility that uses extrusion to fabricate filaments for 3D printing of LIB cells. The extrusion is carried out in a conical twin screw extruder. Our approach allows to obtain representative electrode microstructures after extrusion, where electrical conductivity, ionic effective diffusivity, tortuosity factor and porosity are calculated. The model is a proof of concept that is employed to investigate the influence of the extruder speed and the cohesion level on the resulting electrode properties.