Feature Analysis in High-Dimensional Data: Structure-Activity Relationships of Lewis Acid-Transition-Metal...

Lewis acid-transition metal (LA-TM) catalysts have been proven to have an advantage in catalyzing hydrogen activation. Herein, a high-dimensional structure-activity relationship study is performed for LA-TM-catalyzed hydrogen activation by density functional theory calculations. The DPB-Ni complex is taken as the representative catalyst, and the explored Lewis acid sites and transition-metal centers include B, Al, Ga and Ni, Pd, Pt, respectively. Totally, four general hydrogen activation mechanisms are systematically studied among the nine catalytic systems. The Ga-Ni system undergoes the lowest free energy of activation (11.0 kcal/mol), which is considered to be the optimal combination of the Lewis acid site and transition-metal center. Furthermore, more than 100 parameters are used to analyze the structure-activity relationship, including the physical structure, the bond order, the atom charge, and many other properties. Key parameters of important structures are dug out to show a high correlation with the activity of the LA-TM systems, including the M-H₂ distance, the H-H bond length, the second-order perturbation stabilization energy of M-H₂, the bond order of the LA-TM, and so on. The multivariable analysis indicates that the feature related to the basic elemental properties and the global feature codetermine the activity of the catalyst. In the LA-TM system, the combination of Ip_LA/Ip_TM (Ip, the first ionization energy, the feature related to basic elemental properties) and the chemical hardness (the global feature) can better explain the activity of the catalyst. The Ip_LA/Ip_TM reflects the difficulty of breaking the LA-TM bond, affecting the reaction site of activating hydrogen. The hardness reflects the stability and reactivity of LA-TM-RC complexes. The above two features with the addition of the LA-TM bond length (the local feature) can better reflect the activity of the LA-TM system-catalyzed H₂ activation. The feature combinations and the method of multidimensional data analysis should be informative guidance for the rational design of efficient LA-TM catalysts for H₂ activation.