Descripción del proyecto
Materiales renovables a partir de lignocelulosa para baterías de flujo
La Unión Europea (UE) aspira a la transición a redes de energía renovable, pero afronta retos para lograr este objetivo, en particular para satisfacer la necesidad de un almacenamiento de energía eléctrica escalable, seguro y sostenible. Este reto se ve agravado por la dependencia de materias primas fundamentales procedentes de regiones políticamente inestables. El equipo del proyecto VanillaFlow, financiado con fondos europeos, desarrollará métodos innovadores de almacenamiento de energía. Se trata de aprovechar la tecnología de las baterías de flujo e integrarla con la inteligencia artificial y el aprendizaje automático. La visión del proyecto incluye la sustitución de las materias primas críticas que no resultan sostenibles utilizadas actualmente en las baterías de flujo, como las moléculas y membranas con actividad redox, por materiales renovables derivados del almidón y de fuentes lignocelulósicas fácilmente disponibles. En VanillaFlow están preparados para reforzar el liderazgo tecnológico europeo fomentando la colaboración en diversos campos.
Objetivo
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.
Ámbito científico
- 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
Palabras clave
Programa(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Convocatoria de propuestas
HORIZON-EIC-2022-PATHFINDERCHALLENGES-01
Consulte otros proyectos de esta convocatoriaRégimen de financiación
HORIZON-EIC - HORIZON EIC GrantsCoordinador
8010 Graz
Austria