Embedded Mean-Field Theory for Solution-Phase Transition-Metal Polyolefin Catalysis

Decreasing
the wall-clock time of quantum mechanics/molecular mechanics
(QM/MM) calculations without sacrificing accuracy is a crucial prerequisite
for widespread simulation of solution-phase dynamical processes. In
this work, we demonstrate the use of embedded mean-field theory (EMFT)
as the QM engine in QM/MM molecular dynamics (MD) simulations to examine
polyolefin catalysts in solution. We show that employing EMFT in this
mode preserves the accuracy of hybrid-functional DFT in the QM region,
while providing up to 20-fold reductions in the cost per SCF cycle,
thereby increasing the accessible simulation time-scales. We find
that EMFT reproduces DFT-computed binding energies and optimized bond
lengths to within chemical accuracy, as well as consistently ranking
conformer stability. Furthermore, solution-phase EMFT/MM simulations
provide insight into the interaction strength of strongly coordinating
and bulky counterions.