Cover Feature: The ARTISTIC Battery Manufacturing Digitalization Initiative: From Fundamental Research to Industrialization (Batteries & Supercaps 1/2025)

IF 5.1 4区 材料科学 Q2 ELECTROCHEMISTRY
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).

Abstract Image

封面专题:艺术电池制造数字化倡议:从基础研究到产业化(电池&超级电容器1/2025)
覆盖功能代表了整个艺术项目的工作流程,以优化电池制造工艺参数。合成数据(由基于物理的制造建模链产生)和实验数据用于通过在不同制造阶段使用不同的机器学习技术来训练代理模型:混合&;浆料、涂料;干燥、压延、电解液填充及性能。然后,使用优化器(如贝叶斯)来确定最佳输入参数以优化输出电池性能。更多信息可以在A. A.的概念中找到。Franco和同事(DOI: 10.1002/bat .202400385)。
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来源期刊
CiteScore
8.60
自引率
5.30%
发文量
223
期刊介绍: 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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