In this work, we used the Gaussian Process (GP) regressor as the surrogate model. GPs are Gaussian distributions over functions and serve as probabilistic ML models that can capture uncertainties associated with the black-box function. This is implemented in BoTorch 32 with a Matern5/2 kernel 33 , with independent models for each objective (𝑇 𝑔 and styrene incorporation).