• Benchmarks are simulations of reactions. We include a base class called Experiment which is inherited by benchmarks. One noteworthy functionality is the ExperimentalEmulator which creates a benchmark from data by training a machine learning algorithm (specifically a Bayesian Neural Network). The overall process involves specifying the decision variables and objectives; importing experimental data from a CSV file and using one line of code to train the model. This process is quick and easy. We also note that the Experiment class could be used to connect Summit with automated laboratory equipment or even remote laboratories; this would enable closed-loop and self-optimisation on real case studies.