In the work above, alchemical adsorbates were adequately represented by four features, which were explored in a somewhat exhaustive fashion. Expansion of the training data to include molecules with more diverse sizes, shapes, polarity, and flexibility would require representing the adsorbates with more features, increasing the dimensionality of the adsorbate space, whose exhaustive exploration would imply an intractable number of GCMC simulations. Thus, a critical bottleneck that needs to be overcome to truly open the path towards a universal adsorption model is to gain the ability to efficiently explore the adsorbate (plus adsorbent) space.