Using a single complex to predict the reaction energy profile: a case study of Pd/Ni-catalyzed ethylene polymerization.

Mechanism-driven catalyst screening could be greatly accelerated by quantitative prediction models of the reaction energy profile. Here, we propose a novel method for molecular representation, taking palladium- and nickel-catalyzed ethylene polymerization as model reactions. The geometric parameters (GPfra) and electron occupancies (EOfra) from the non-ligand fragment of the η 3 -complex were extracted as the molecular descriptors, followed by constructing the reaction energy profile prediction models on the basis of various regression algorithms. The models showed great accuracy with respect to both theoretical and experimental data. More importantly, the models are convenient for training and utilization. On one hand, all the features were easily captured from the single η 3 -complex. On the other hand, further investigation also demonstrated that the models could be constructed with a small training sample size. We believe that our featurization method could possibly be generalized to more organometallic reactions and paves the way to efficient catalyst design.