Descrizione del progetto
Materiali rinnovabili a base di lignocellulosa per le batterie di flusso
L’obiettivo dell’UE di effettuare la transizione verso le reti di energia rinnovabile è permeato da sfide, in particolare per quanto concerne la necessità di garantire uno stoccaggio di energia elettrica scalabile, sicuro e sostenibile. Questa difficoltà è aggravata dalla dipendenza da materie prime critiche provenienti da regioni politicamente instabili. Il progetto VanillaFlow, finanziato dall’UE, svilupperà metodi innovativi per lo stoccaggio dell’energia che prevedono di sfruttare la tecnologia delle batterie di flusso e di integrarla con l’intelligenza artificiale e l’apprendimento automatico. La visione del progetto comprende inoltre la sostituzione delle materie prime critiche non sostenibili attualmente utilizzate nelle batterie di flusso, come le membrane e le molecole redox-attive, con materiali rinnovabili derivati dall’amido e da fonti lignocellulosiche facilmente reperibili. VanillaFlow è destinato a rafforzare la leadership tecnologica europea promuovendo la collaborazione in vari settori.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Invito a presentare proposte
HORIZON-EIC-2022-PATHFINDERCHALLENGES-01
Vedi altri progetti per questo bandoMeccanismo di finanziamento
HORIZON-EIC - HORIZON EIC GrantsCoordinatore
8010 Graz
Austria