where 𝑦(𝑥) is the underlying function that we observe via experiments. We use the expected improvement (EI) acquisition function for in silico experiments or q-noisy expected improvement (qNEI) acquisition function for flow chemistry experiments. In BO with EI as an acquisition function, the aim is to choose the point that is expected to improve the most upon the existing best observed point 𝑦 * ≥ 𝑦(𝑥 & )∀𝑖 ∈ (1, … , 𝑡) where 𝑡 is the number of observations thus far. Therefore, we create an improvement function 𝐼(𝑥) describing the improvement of the posterior of the GP over the best observed point. If there is no improvement, 𝐼(𝑥) = 0. 𝐼(𝑥) = max (𝑓 M (𝑿) -𝑦 * , 0)