Combustion is imperative to our day-to-day lives, and predicting the combustion properties of novel fuels allows for simultaneous development of greener fuels and more efficient engines. To predict the detailed combustion kinetics of a single novel fuel requires the generation of a reaction mechanism consisting of thousands of elementary reactions and their kinetics. The reaction rates can be determined by performing transition state theory (TST) calculations on each elementary reaction. However, with dozens of novel biofuels being considered, and each fuel having its own reaction mechanism, these TST calculations must be automated. We present a fully-automated method to determine reaction rates via automated Transition State Theory (AutoTST) calculations, coupled to the Reaction Mechanism Generator (RMG) software [1]. We focus here on the abstraction of hydrogen by six common radicals present in combustion (·OH, H·, ·OOH, O·, ·CH
3 and O
2) from several possible biofuels being considered by the U.S. Department of Energy’s “Co-Optima†program. Hydrogen abstraction is one of the most important classes of reactions in the combustion process; therefore, accurately determining kinetic parameters for these reactions is crucial. Our approach uses RMG to determine the network of possible hydrogen abstraction reactions for each fuel, and the reaction kinetics are determined using our AutoTST method. The AutoTST method estimates the transition state geometry using a group contribution method to predict interatomic distances, coupled with distance geometry [2]; it performs DFT geometry optimization, performs intrinsic reaction coordinate calculations to verify the transition state, and uses CanTherm [3], a canonical transition state theory calculator, to determine kinetic parameters. This method has previously been applied to hydrogen abstractions and results have been compared to published values and benchmark calculations. The application of AutoTST is broad and can be applied to all families of combustion reactions given proper resources.
[1] C. W. Gao, J. W. Allen, W. H. Green, and R. H. West, Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms, Comput. Phys. Commun. 203 (2016) 212 - 225. DOI: 10.1016/j.cpc.2016.02.013.
[2] P. L. Bhoorasingh and R. H. West, Transition state geometry prediction using molecular group contributions, Phys. Chem. Chem. Phys. 17 (2015) 32173–32182.
[3] J. W. Allen and W. H. Green, CanTherm: Open-source software for thermodynamics and kinetics, Included in: Reaction Mechanism Generator, v2.0.0. 2016, URL: http://reactionmechanismgenerator.github.io.
