Here we use the DFT-SCAN dataset for molten KCl-ThCl 4 corresponding to the AL4GAP run for the composition space defined in Listing 6. The BO code and the datasets can be found in the Github folder 'HyperparameterOptimization/'. The BO script that utilizes the GPyOpt library is implemented in the 'BayesOpt_SOAP.py'. This Python script performs BO to find the optimal values for the following hyperparamters: cutoff, scaling of kernel (2B, SOAP), number of representative sparse points (2B, SOAP), and number of angular and radial basis functions for SOAP. The best optimal hyperparameters found in the search range are written to the 'hyperparam_quip.json' file. More details can be found in the Github repository. The optimal BO hyperparameters are preserved through the iterative retraining discussed in the next subsection.