Elucidating Thermodynamically Driven Structure–Property Relations for Zeolite Adsorption Using Neural Networks

)) to within 4.71 [J/mol/K], 3.14 [kJ/mol], 1.15 [mg/(g-cat·atm)], respectively. A SHAP analysis that deconvolutes the effect of correlated features to compute their independent additive contributions showed that framework, rather than adsorbate features, was significantly more important for predicting the entropy of adsorption but equivalently important for predicting the Henry's constant. The largest pore diameter along a free sphere path was identified as the most critical framework feature, while the van der Waals volume (which captures the trend in electronegativity) was the most important adsorbate feature toward predicting the entropy of adsorption.