Agarwal et al. applied multi-objective Bayesian optimisation to the discovery of benzothiadiazole (BzNSN) redoxmers, with the goal of simultaneously optimising the reduction potential, solvation-free energy, and absorption wavelength. They applied their approach to a dataset of 1,400 BzNSN molecules, where properties were calculated using density functional theory calculations. They demonstrated at least 15 times increased efficiency compared to randomly selecting materials highlighting the flexibility for the discovery of functional materials.