Description du projet
Des matériaux renouvelables issus de la lignocellulose pour les batteries d’écoulement
L’UE vise à passer à des réseaux d’énergie renouvelable, mais doit relever des défis pour atteindre cet objectif, en particulier pour répondre à un besoin de stockage d’énergie électrique évolutif, sûr et durable. Ce défi est exacerbé par la dépendance à l’égard de matières premières essentielles provenant de régions politiquement instables. Le projet VanillaFlow, financé par l’UE, vise à concevoir des méthodes innovantes de stockage de l’énergie. Il s’agit de tirer parti de la technologie des batteries à flux redox et de la combiner à l’intelligence artificielle et à l’apprentissage automatique. La vision du projet comprend le remplacement des matières premières critiques et non durables actuellement utilisées dans les piles à flux, telles que les molécules redox-actives et les membranes, par des matières renouvelables dérivées de l’amidon et de sources lignocellulosiques facilement disponibles. VanillaFlow contribuera à renforcer le leadership technologique de l’Europe en encourageant la collaboration dans différents domaines.
Objectif
The Grand Challenge ahead is to shift fossil-dominated centralized energy systems towards regenerative integrated multi-vector grids. This requires also sustainable electrical energy storage, including the related raw material supply, processes and systems. A real impact on economy, society and ecology is only created if materials, processes and products can be potentially transferred to large scale. This represents a particular challenge for mid to long term, systems-integrated energy storage, also because the EU strongly depends on critical raw materials from politically instable regions. In VanillaFlow, we develop radically new approaches for integrated energy storage which combine artificial intelligence (AI) and machine learning (ML) with flow battery technology to replace currently employed, non-sustainable, and critical raw materials (i.e. redox-active molecules, membranes) in flow batteries by readily-available renewable materials based on starch and lignocellulosics. VanillaFlow will use AI and ML techniques such as physics-informed modeling, causal discovery, and representation learning, and makes use of deep learning and symbolic regression. These approaches are used in designing redox active quinones, and to optimize their interplay with the other components of a battery on single and multi-cell level. The whole research will be guided by toxicology investigations to ensure that sustainable and inherently safe materials will be obtained in the project. Today, the innovation capacity of European scientists and industry in the area of renewable materials makes them already the leading global players in the field. VanillaFlow will further support the European technological leadership in the area by cross-fertilization of different fields (artificial intelligence, battery technology, pulp and paper, biotechnology, polymer technology, toxicity) while addressing needs of sustainable materials in mid to long term energy storage.
Champ scientifique
- natural scienceschemical scienceselectrochemistryelectric batteries
- natural sciencesbiological sciencesecology
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- medical and health sciencesbasic medicinetoxicology
- engineering and technologyenvironmental engineeringenergy and fuelsenergy conversion
Programme(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Régime de financement
HORIZON-EIC - HORIZON EIC GrantsCoordinateur
8010 Graz
Autriche