Cyclic and aromatic hydrocarbons are important components of usual commercial fuels, with C 6 -rings being among the most abundant cyclic structures. The combustion chemistry of C 6ff f h c ( m c ph …) during through the intermediates formed during their combustion. In this work the ignition delays of cyclohexane, cyclohexene, 1,3-cyclohexadiene and 1,4-cyclohexadiene are systematically studied using experiments and kinetic modeling. Shock tube experiments were performed at high-temperature (above 1200K) and for mean pressures of 6 atm. A detailed chemical kinetic model was developed that includes the combustion chemistry of the four cyclo-C 6 fuels. Electronic structure calculations were performed at the CCSD(T)/CBS//B2PLYP-D3 level of theory on the pericyclic reactions of the unsaturated fuels. Pressure-dependent rate coefficients were computed by solving the master equation, and include in the mechanism. The model was validated against the new ignition data and against data of the literature. It was able to reproduce the experimental ranking of reactivity: cyclohexene > 14-CHD > cyclohexane > benzene ≈13-CHD. Kinetic analyses were performed to explain this difference of reactivity. It is shown that pericyclic reactions play a major role in the initial decomposition of the unsaturated fuels.
The chemistry underlying liquid-phase oxidation of organic compounds, the main cause of their aging, is characterized by a free radical chain reaction mechanism. The rigorous simulation of these phenomena requires the use of detailed kinetic models that contain thousands of species and reactions. The development of such models for the liquid-phase remains a challenge as solvent-dependent thermo-kinetic parameters have to be provided for all the species and reactions of the model. Therefore, accurate and high-throughput methods to generate these data are required. In this work, we propose new methods to generate these data and we apply them for the development of a detailed chemical kinetic model for n-butane autoxidation, which is then validated against literature data. Our approach for model development is based on the work of Jalan et al. [J.
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