Ab initio based kinetic modeling for the simulation of industrial chemical processes

Many industrial processes are based on radical gas phase chemistry. Detailed kinetic models are the most versatile way to model the chemistry for this processes, which is necessary for an optimal chemical reactor optimization and design. Due to the highly reactive nature of radicals however, the reaction networks easily contain up to hundreds of species and thousands of reactions. Providing these networks with the required thermodynamic and kinetic data is one of the largest challenges in chemical reaction engineering. Since experimental data are only available for a limited number of reactions, typically a mixture of experimental and predicted data is used, optimizing the kinetics of key reactions to fit the observed conversions and selectivities. The parameter fitting can obscure possible deficiencies in the reaction network and/or description of the transport phenomena, which hampers a general application of the developed kinetic model.