Abstract
Predicted by stochastic models and observed experimentally in a number of isomerization reactions, viscosity-induced solvent effects manifest themselves in a significant departure of the reaction rates from the values expected on the basis of transition state theory. These effects are well understood within the framework of stochastic models; however, the predictive power of such models is limited by the fact that their parameters are not readily available. Experiment and molecular dynamics (MD) simulations can provide such information and can serve as the testing grounds for various stochastic models. In real solvents, a change in viscosity is inevitably associated with variation of at least one of the three factors – temperature, pressure, or solvent identity, resulting in different solvent–solvent and solvent–solute interactions. A model is proposed in which solvent viscosity is manipulated through mass scaling, which allows one to maintain other factors constant for a series of viscosities. This approach was tested on MD simulations of the kinetics of two model isomerization reactions in Lennard–Jones solvents, whose viscosity was varied over three orders of magnitude. The results reproduce the Kramers turnover and a strong negative viscosity dependence of the reaction rates in the high viscosity limit, somewhat weaker than η −1.
Acknowledgements
Financial support of the National Sciences and Engineering Council of Canada (NSERC) and the University of the Fraser Valley is greatly appreciated. This research has been enabled by the use of WestGrid computing resources, which are funded in part by the Canada Foundation for Innovation, Alberta Innovation and Science, BC Advanced Education, and the participating research institutions. WestGrid equipment is provided by IBM, Hewlett Packard and SGI. The authors would also like to thank the reviewer for useful critical comments.