Structure-Based Relative Energy Prediction Model: A Case Study of Pd(II)-Catalyzed Ethylene Polymerization and the Electronic Effect of Ancillary Ligands

Rapidly
mapping a reaction energy profile to understand the reaction
mechanism is of great importance and highly desired for the discovery
of new chemical reactions. Herein, a combination of density functional
theory (DFT) calculations and regression analysis has been applied
to construct quantitative structures-based energy prediction models,
considering Pd­(II)-catalyzed ethylene polymerization as an example,
for rapid construction of the reaction energy profile. It is inspiring
that only geometrical parameters of the reaction center of one species
are capable of predicting the whole energy profile with high accuracy.
The reaction energies of ethylene insertion and β-H elimination,
which directly correlate with polymerization activity and the possibility
of branch formation, were studied to elucidate the electronic effects
of ancillary ligands. Further analyses of these models from the statistical
and chemical points of view afforded useful information on the design
of the catalyst ligand. The current work is expected to methodologically
shed new light on rapidly mapping the energy profile of chemical reactions
and further provide useful information for the development of the
reactions.