(710c) Predicting Surface Structure Sensitive Reactivity across All Cu(hkl) Surface Orientations: Tartaric Acid Decomposition

The enantiospecific interactions between chiral pharmaceuticals and human physiology require the production of enantiomerically pure drugs. An understanding of structure sensitive reactivity on chiral surfaces is vital for the design of enantioselective chiral catalysts and chiral adsorbent materials for enantioselective separations. The distribution of surface atom coordination numbers and generalized coordination numbers were computed across the entire space of crystallographic directions. Machine learning regression techniques revealed the relationship between calculated coordination numbers and kinetic parameters derived from measurements of tartaric acid decomposition on surface structure spread single crystals. The structure spread single crystals expose a continuous distribution of surface orientations. The decomposition kinetics of D-tartaric acid are enantiospecific, depending on the chirality of the surface orientation. The regression model provides insight into the origins of the enantioselectivity of tartaric acid on copper. The model enables us to predict the most enantioselective surface orientation providing a general screening tool for identifying optimal chiral catalysts or separation materials.