To assess the different surrogate model performances within this iterative optimization strategy and identify their ability to operate under an initial low data regime, we compared 5 different models: RF, ANN, GP, SVR and AdaBoost. In Figure the yield distribution of the dataset is shown, demonstrating that data is well distributed between 0% and 100% yield, despite of a peak at 0% yield. The learning curves of the single surrogate models within the closed-loop optimization (Figure ), in which the maximum yield observed in each active learning iteration is presented, illustrates the different performances of the models when finding the optimum conditions. The experiments were conducted using sequential sampling such that one datapoint was sampled during each iteration using an exploitative acquisition function.