To systematically investigate the impact of including additional descriptors on the model's performance, we incrementally expanded the descriptor set. This stepwise augmentation allowed us to assess how the inclusion of a higher number of descriptors influences the accuracy and predictive power of our model. As we progressed, we continually introduced new descriptors into our feature space, each chosen to capture specific chemical attributes and properties. The step-bystep expansion of our descriptor set provided insights into the optimal feature space for our hyperparameters of all models can be found in the SI.