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Modelling for the search for new active materials for redox flow batteries

Project description

Energising redox flow batteries

SONAR will develop a framework for the simulation-based screening of electroactive materials for aqueous and nonaqueous organic redox flow batteries (RFBs). It will adopt a multiscale modelling paradigm, in which simulation methods at different physical scales will be further advanced and linked by combining physics- and data-based modelling. SONAR will develop a screening framework to determine levelized cost of storage, starting from the automatic generation of candidate structures for the electroactive material, then iterating through molecular-, electrochemical interface-, porous electrodes-, cell-, stack-, system- and techno-economic-level models. To increase the throughput of the screening, SONAR will exploit advanced data integration, analysis and machine-learning techniques, drawing on the growing amount of data produced during the project. Project results are expected to reduce the cost and time-to-market of redox flow batteries, thus strengthening the competitiveness of the EU battery industry.

Objective

SONAR will develop a framework for the simulation-based screening of electroactive materials for aqueous and nonaqueous organic redox flow batteries (RFBs). It will adopt a multiscale modelling paradigm, in which simulation methods at different physical scales will be further advanced and linked by combining physics- and data-based modelling. Competing energy storage technologies are only comparable when using the levelized-cost-of-storage (LCOS) as a global metric, accounting for the complex interrelations between factors like CAPEX, lifetime and performance. SONAR will thus develop a screening framework to determine LCOS, starting from the automatic generation of candidate structures for the electroactive material, then iterating through molecular-, electrochemical interface-, porous electrodes-, cell-, stack-, system- and techno-economic-level models. For the iterative traversal of the different scales, exclusion criteria like solubility, standard potentials and kinetics will be defined, and the results for individual candidates will be stored in a database for further processing. To increase the throughput of the screening, SONAR will exploit advanced data integration, analysis and machine-learning techniques, drawing on the growing amount of data produced during the project. The models will be validated e.g. by comparison with measurements of redox potentials for known chemistries, or measurement data of RFB half-cells and lab-sized test cells.
SONAR will work closely with industrial partners (incl. JenaBatteries, Volterion) to ensure the commercial viability of the results. The models will be exploited individually and in a comprehensive screening service offered by Fraunhofer SCAI, facilitating the rapid assessment of the technical and economic potential of a new technology in its earliest development stages. This will reduce the cost and time-to-market, thus strengthening the competitiveness of the EU’s battery industry in the emerging field of organic RFBs.

Call for proposal

H2020-LC-BAT-2019-2020

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Sub call

H2020-LC-BAT-2019

Coordinator

FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV
Net EU contribution
€ 918 900,00
Address
HANSASTRASSE 27C
80686 Munchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
Links
Total cost
€ 918 900,00

Participants (6)