Overall, whilst the rate of improvement in the highest observed yields in the earlier iterations did not significantly vary between the different ML models, the required number of iterations to find the best-performing conditions (=99.9% yield) highlighted the differences between the models. Although the ANN model started initially with the lowest yield, the model achieved the optimal conditions within approximately 60 iterations, the fastest of all models. Tree based models such as AdaBoost and RF required approximately 100 iterations and GP/SVR achieved the ideal conditions within 110 iterations.