For a coal-fired power plant, we observe that the ranking of the materials is little affected by the method we use (Spearman coefficient larger than 0.85). Only if we lack isotherm data below 5 and 25 mbar and impose the fitting of the Henry coefficient, errors in our ranking become apparent (Spearmann coefficient of 0.79 and 0.74, respectively). This is for cases for which we impose an incorrect Henry coefficient as the data for 5 and 25 mbar are already outside the Henry regime. For the natural gas case and confined spaces, the concentration of CO 2 is so low that purity values are very sensitive to the method we use. However, the ranking of the material does not show significant deviations (Spearman coefficient larger than 0.8). Only in the case of confined spaces, if we lack isotherm data below 5 and 25 mbar, errors in our ranking become apparent (Spearmann coefficient of 0.78 and 0.77 respectively) Table : The Spearman coefficient comparing the ranking of materials between DSL fitting and IAST for a coal-fired power plant (CF-PP), natural gas-fired power plant (NG-PP), and confined spaces (CS). The subscripts "5" and "25" indicate that the isotherm data below 5 and 25 mbar, respectively, have been removed from the data set to mimic the experimental limitations. The subscript "Henry" indicates that the fitting is done to ensure that the fits capture the Henry coefficient. The differences between DSL and IAST can cause some of the top-performing materials, as predicted by IAST, to not appear at the top for DSL. Table summarizes the number of structures that appear in the top 40 performing materials as predicted by IAST for the different case studies using the DSL fitting. It is evident that one can miss from 10% in the best-case scenario to 33% of the top-performing structures when using extended DSL compared to IAST. An interesting question is whether IAST has similar difficulties if we remove the data at very low pressure. In figure , we make a similar comparison for IAST with computational data removed below 5 and below 25 mbar. In this comparison, one has to realize that we now have IAST predictions on both sides. Hence we are only comparing the effect of omitting the low-pressure data. Whereas, in such a comparison for DSL, we have a convoluted effect as we see the differences between IAST and DSL and, on top of this, the effect of omitting low-pressure data. Yet, the effect is surprisingly small, and even for the confined spaces case, one can obtain a decent ranking. If one uses DSL, one needs to fit the coefficients.