During the optimisation, most of the points sampled by NEMO (orange points) were on or around the Pareto front, highlighting the learning efficiency of NEMO. This was reflected on the hypervolume learning over experiment number (Figure , ESI). After 20+ sampled points, hypervolume improvement had converged, suggesting that NEMO maximised the hypervolume learning. In the second benchmark, NEMO was trained using 14 data points, two points per each of the seven solvents, excluding DCM to avoid the presence of any points on the Pareto front (Figure ).