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

Leanne D ChenJames J LawniczakFeizhi DingPeter J BygraveSaleh RiahiFrederick R ManbySukrit MukhopadhyayThomas F Miller Iii
Published in: Journal of chemical theory and computation (2020)
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.
Keyphrases
  • molecular dynamics
  • density functional theory
  • transition metal
  • solid state
  • computed tomography
  • molecular dynamics simulations
  • dna binding