High-throughput screening, synthesis and characterisation of active materials for flow batteries (PREDICTOR)
At a glance
- Project leader : Prof. Dr. Jürgen Schumacher
- Deputy of project leader : Dr. Roman Pascal Schärer
- Project budget : CHF 584'791
- Project status : ongoing
- Funding partner : EU and other international programmes (Horizon Europe / Marie Skldowska-Curie Actions Doctoral Networks / Projekt Nr. 101168943)
- Project partner : Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. / Fraunhofer-Institut für Chemische Technologie ICT, Technical University of Denmark / Dept. of Energy Conversion and Storage, Software for Chemistry & Materials B.V. (SCM), Aalto University, Centre national de la recherche scientifique CNRS / Laboratoire de Réactivité et Chimie des Solides (LRCS), Karlsruher Institut für Technologie KIT / Institut für Mechanische Verfahrenstechnik und Mechanik, University of Cambridge / Chemical Engineering and Biotechnology, Enerox GmbH, Accelerated Materials Ltd., hte GmbH, Universität Bayreuth / Electrochemical Process Engineering, Harvard University / Electrochemical engineering for energy and the environment, Universität der Bundeswehr München / Institute of Physics, University of New South Wales / Mechanical and Manufacturing Engineering, BatteryNL Dutch Battery Materials / Shell, Golin Wissenschaftsmanagement, RWTH Aachen University / Institute of Technical Thermodynamics, University of Amsterdam / Van 't Hoff Institute for Molecular Sciences , Leiden University / Institute of Chemistry, Energy and Sustainability, Ghent University / Center for Molecular Modeling
- Contact person : Jürgen Schumacher
Description
PREDICTOR is a research and doctoral training project funded by the European Union’s Marie-Sklodowska-Curie programme. PREDICTOR aims to develop a fast, high-throughput method for material development for electrochemical energy storage. This includes modeling and simulation software for the computational screening of organic chemicals based on their potential performance in energy storage systems. Automated systems for chemical synthesis, electrolyte production and characterization will be used to produce the chemicals identified in the screening and test their suitability for energy storage. The process parameters are improved with the help of an optimization process based on artificial intelligence. New standards are also being developed for the management, storage and automated processing of the resulting data. In order to validate the newly developed materials, three redox flow battery cells are being built as part of the project.
The PREDICTOR project brings together a total of over 20 project partners, who will supervise 15 doctoral students. The ZHAW will supervise two of these doctoral students and support the project with its expertise in the modeling and simulation of redox flow batteries.