SOURCE-LINKED INTELLIGENCE
Green and Sustainable Processes for Electrode Production
ts porous silicon directly on the copper current-collector starting from locally produced silane gas (SiH4). Moreover, the use of advanced modelling and simulation techniques including digital twins, artificial intelligence, and machine learning are to be employed to predict and optimise cell performance in early development stages, support the cell production process by virtually assessing the influence and importance of production parameters and thus minimising the number of experiments and to accelerate electrode production optimisation steps. The greenSPEED cell aims at increasing energy density (+69%) while reducing energy consumption (-32%) and costs (-21%) of production as compared to state-of-the-art Li-ion cells. The concepts here proposed have been already demonstrated at TRL 2/3 with the aim of reaching TRL 5/6 by the end of the project. battery, green process, sustainability, Artificial Intelligence, Digital Twin
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 5289222.25
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T00:21:03.701Z. This is not the publication date.