Cover Feature: The ARTISTIC Battery Manufacturing Digitalization Initiative: From Fundamental Research to Industrialization (Batteries & Supercaps 1/2025)
Javier F. Troncoso, Franco M. Zanotto, Diego E. Galvez-Aranda, Diana Zapata Dominguez, Lucie Denisart, Alejandro A. Franco
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引用次数: 0
Abstract
The Cover Feature represents the whole ARTISTIC project workflow to optimize battery manufacturing process parameters. Synthetic data (produced by the physics-based manufacturing modeling chain) and experimental data are used to train surrogate models by using different machine learning techniques at the different manufacturing stages: mixing & slurry, coating & drying, calendering, electrolyte filling and performance. Then, optimizers, such as Bayesian, are used to determine the best input parameters to optimize output battery properties. More information can be found in the Concept by A. A. Franco and co-workers (DOI: 10.1002/batt.202400385).
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Electrochemical energy storage devices play a transformative role in our societies. They have allowed the emergence of portable electronics devices, have triggered the resurgence of electric transportation and constitute key components in smart power grids. Batteries & Supercaps publishes international high-impact experimental and theoretical research on the fundamentals and applications of electrochemical energy storage. We support the scientific community to advance energy efficiency and sustainability.
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