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Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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An extensible framework for capturing solvent effects in computer generated kinetic models.

Amrit Jalan1, Richard H West, William H Green

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.

The Journal of Physical Chemistry. B
|January 11, 2013
PubMed
Summary
This summary is machine-generated.

This study presents a new method for automatically generating chemical kinetic models in solution, improving accuracy by estimating solvent effects on reaction rates. This advances automated chemical mechanism generation for complex systems.

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Area of Science:

  • * Computational Chemistry
  • * Chemical Kinetics
  • * Physical Chemistry

Background:

  • * Manual construction of detailed kinetic models is time-consuming and prone to errors.
  • * Automated methods for exploring chemical pathways require rapid estimation of thermochemistry and kinetics.
  • * Extending automated methods to solution-phase systems necessitates accounting for solvent effects on reaction rates and equilibria.

Purpose of the Study:

  • * To develop a methodology for extending automatic mechanism generation to solution-phase chemical systems.
  • * To estimate solvent effects on reaction rates and equilibria using computational methods.
  • * To model the liquid-phase oxidation of tetralin in various solvents.

Main Methods:

  • * Combined the linear solvation energy relationship (LSER) method with Mintz correlations to estimate Gibbs free energy of solvation (ΔG(solv)°(T)).
  • * Utilized solute descriptors estimated from group additivity for over 30 solvents.
  • * Employed polarizable continuum quantum chemistry methods to model solvent dependence for radical reactions.
  • * Applied simple corrections for radical sites, validated against experimental data.

Main Results:

  • * Successfully estimated ΔG(solv)°(T) in over 30 solvents.
  • * Developed kinetic models for liquid-phase oxidation of tetralin, showing increased oxidation rates with solvent polarity.
  • * Demonstrated consistency between computational modeling and experimental observations.
  • * Presented performance of scaled particle theory for enthalpic-entropic decomposition of ΔG(solv)°(T).

Conclusions:

  • * The proposed methodology effectively extends automatic mechanism generation to solution-phase systems.
  • * The approach accurately models solvent effects on reaction kinetics, particularly for radical reactions.
  • * Computational methods, like polarizable continuum models, offer a viable alternative for estimating solvent effects where experimental data is scarce.
  • * Further research is needed to enhance the general applicability of this approach.