Ab Initio Kinetic Modeling of Gas Phase Radical Reactions

Abstract

Kinetic modeling of gas phase radical reactions plays an important role in understanding various atmospheric processes and in the design and optimization of important industrial chemical processes. Experimental kinetic studies remain challenging due to the complexity of the reacting systems and because of the short lifetime of the radical intermediates. To test the predicting capabilities of ab initio calculations for such gas phase radical reactions, we modeled the low temperature atmospheric oxidation of carboxylic acids by hydroxyl radicals and simulated the high temperature industrial steam cracking of ethane. The oxidation of formic and acetic acid by hydroxyl radicals was studied to develop an ab initio computational procedure to accurately predict reaction rate coefficients and selectivities for this family of reactions. Then using the procedure, we studied the initial rate and selectivity of the oxidation of valeric acid, C4H9COOH. The crucial role of multi-dimensional tunneling in determining the high selectivity of the acid channel in small carboxylic acids, and the importance of hydrogen-bond networks in determining the selectivity in larger organic acids is an intrinsic feature of these low temperature processes. To illustrate that the accuracy that can be obtained with standard ab initio computational chemistry methods has become sufficient to begin to predict the conversion and selectivity for a complex, high temperature gas phase radical process, the industrial steam cracking of ethane was modeled using a fully ab initio kinetic model. Our reaction network consists of 20 species smaller than C5 and 150 reversible elementary reactions and includes all possible reactions involving the 20 species. A kinetic model based entirely on high-level quantum chemical calculations was able to accurately predict yields and conversions for the industrial steam cracking of ethane and illustrates the great promise for the design and optimization of industrial processes using a fully ab initio approach.