Modelling distonic radical ion kinetics: a systematic investigation of phenyl-type radical addition to unsaturated hydrocarbons Oisin J. Shiels 1 , Jack A. Turner 1 , P. D. Kelly 1 , Stephen J. Blanksby 2 , Gabriel da Silva 3 , and Adam J. Trevitt 1 1 Molecular Horizons and School of Chemistry and Molecular Bioscience, Australia, 2 Central Analytical Research Facility and the School of Chemistry and Physics, Australia, 3 Department of Chemical Engineering, Australia Gas–phase ion–molecule reactions are important contributors to many chemical environments including Earth’s atmosphere, combustion, and the interstellar medium, and are also relevant to plasma technology and ionic propellants. The long-range and short-range interactions of ion–molecule reactions manifests in multistep energy pathways that in uence the reaction rate and product yield(s). We are developing a modelling framework using a Rice-Ramsperger-Kassel-Marcus theory Master Equation (RRKM-ME) approach to predict second-order rate coefficients, focusing on a comprehensive set of eighteen experimentally measured phenyl-type sigma-radical cation ion–molecule reactions. The reaction rates predicted by this 4-point statistical reaction rate model were in good agreement with these experimental values, in the best case providing an average root mean square deviation of only 37% across the entire data set. These results provide evidence that the formation of the pre- reactive complex is the key gatekeeper for the reaction kinetics of these ion−molecules reactions. In this poster presentation, this newly developed RRKM-ME model is explored in detail. Firstly, this new framework is compared to the predictions of two other historical paradigms, the ionic curve crossing and the relative barrier energy models. The 37% average root mean square deviation of this 4-point model model compares favourably to both the relative barrier energy (41% RMS) and the curve crossing (42% RMS) models. Additionally, the maximum deviation for the two historical paradigms is over two times larger than the new RRKM- ME model. Secondly, one of the major benefits of this model is the ability to model reactions under different experimental conditions. As this RRKM-ME approach is completely derived from first principles, simply changing the initial conditions of the input file should allow for predictions across different temperature and pressure regimes. To explore this, the temperature dependency for three ion–molecule reactions are investigated. In particular, we examine how the temperature dependency of these predicted second-order rate coefficient changes as the energy of the key rate limiting transition state is modified.
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