Recent progress in continuous slurry production – towards smart manufacturing of electrode slurries

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State of the art electrode manufacturing lines rely usually on discontinuous slurry production processes. Especially with the increasing demand for battery electrodes, the extrusion process for continuous slurry production has caught the interest of both public research and industry. Twin screw extrusion lines combine superior scalability with short processing times and decent dispersing efficiency in a comparatively small form factor. The continuous slurry flow opens new possibilities for both process and quality control purposes by developing a cyber-physical system (CPS).
This presentation will guide the attendees through the latest research in the development of an autonomous, scalable slurry production using a twin screw extrusion device. based on the idea of a cyber-physical system. After briefly introducing the process and the idea of a CPS, the attendees will gain insight into the latest research regarding the implementation of such a CPS in slurry production. Therefore, four fundamental steps have to be accomplished: 1. Defining a quality parameter; 2. understanding process / product interactions; 3. Establishing inline monitoring; 4. Creating a control model. During the presentation the Carbon Black Dispersion Index (DI) will be introduced as a quality parameter that allows quick and easy quality assessment based on the dispersion of Carbon Black particles. This quality parameter was applied in a systematic process study, which allowed the identification of crucial process parameters. The results show a significant impact of both solids content and throughput on the dispersion. Moreover, the data allows the correlation between process parameters and the DI, which can further be used to set up a control model. Additionally, it was proven that the same parameter can be applied by solely using an inline characterization of the slurry, which is key for implementing cyber-physical systems. Future research is necessary to correlate the DI with the electrochemical performance to define the target value. On the other hand, the data will be used to create a process model that also takes into account the screw geometry.

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