Towards a high-accuracy kinetic database informed by theoretical and experimental data: CH3 + HO2 as a case study
2020
Abstract The reliability of predictive simulations for advanced combustion engines depends on the availability of accurate data and models for thermochemistry, chemical kinetics, and transport. In that regard, accurate data are critically important for both their direct use in predictive simulations and for benchmarking improved theoretical methodologies that can similarly produce accurate data for predictive simulations. The use of informatics-based strategies for the determination of accurate thermochemical data with well-defined uncertainties, e.g. the Active Thermochemical Tables (ATcT), has revolutionized the field of thermochemistry-providing thermochemical data of unprecedented accuracy for predictive combustion simulations and has served as a key enabler of ab initio electronic structure methodologies of equally impressive accuracy. Clearly, pursuit of informatics-based analogs in chemical kinetics would be similarly worthwhile. Here, we present results and analyses for the kinetics of CH3 + HO2 reactions that demonstrate some key elements of any approach to developing analogs for kinetics, including: the importance of raw data for quantifying the information content of experimental data, the utility of theoretical kinetics calculations for constraining experimental interpretations and providing an independent data source, and the subtleties of target data selection for avoiding unphysical parameter adjustments to match data affected by structural uncertainties. Notably, we find the optimization performed here using the MultiScale Informatics (MSI) approach applied to carefully selected (mostly raw) experimental data yields an opposite temperature dependence for the channel-specific CH3 + HO2 rate constants as compared to a previous rate-parameter optimization. While both optimization studies use the same theoretical calculations to constrain model parameters, only the present optimization, which incorporates theory directly into the model structure, yields results that are consistent with theoretical calculations.
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