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.