This case study demonstrates how one can evaluate the behavior of different ASFs in Olympus. We consider the redoxmers dataset, in which Agarwal et al. reported a computational screen of 1408 benzothiadiazole derivatives for application as redox-active materials in nonaqueous flow batteries (Fig. ). The three objectives are the DFT-computed reduction potential E red , solvation free energy G solv and maximum absorption wavelength λ abs . We optimize the three objectives simultaneously using the BoTorch planner and each ASF supported in Olympus. The aim is to identify candidates that (i) have an maximum absorption wavelength as close as possible to 375 nm, (ii) have a minimal reduction potential against a Li/Li + reference electrode, and (iii) provide the lowest possible solvation free energy, understood as a proxy for solubility.