According to the authors, this approach can sample the most favorable sites of the structure without wasting computational time on unfavorable ones. However, the sampled points being at the center of the cages, they may not always be the most attractive sites especially for large pores. This approximate approach makes this sampling interesting for quickly producing an energy-based ML descriptor, but it could not replace a Widom insertion for assessing the adsorption performance. Other biased sampling methods that calculate the integrals of the adsorption enthalpy and the Henry constant could be applied, instead. In this work we propose one way of exploiting prior chemical knowledge of adsorption -the fact that it occurs near the surface of the pores -to efficiently sample the nanoporous space.