For multi-objective BO we use TSEMO, Thompson-Sampling for efficient multi-objective, proposed by Bradford et al. It works by training a Gaussian Process (GP) to predict each objective given reaction conditions. Since GPs output a distribution instead of a point estimate, the GP itself cannot be optimised. TSEMO takes the approach of spectral sampling a deterministic function from the GP and optimizing that using NSGA-II. From the feasible points suggested by NSGA-II, the one(s) with maximum hypervolume improvement are selected.