KAUST DepartmentClean Combustion Research Center
Chemical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberOSR-2019-CRG7-4077
Permanent link to this recordhttp://hdl.handle.net/10754/676849
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AbstractAccurate thermochemical properties for chemical species are of vital importance in combustion research. Empirical group additivity approaches are extensively used to generate thermochemistry data used in chemical kinetic models, but the accuracy is limited. In this work, we performed electronic structure calculations to determine reliable thermochemistry data for an extensive set of molecules that were taken from a large and well-established chemical kinetic model. The developed database consists of 1340 species that contain up to 18 and 5 carbon and oxygen atoms, respectively. The M06-2X/aug-cc-pVTZ level of theory was used for the geometry optimizations, vibrational frequency calculations, and dihedral angle scans. The potential energy of the different species was further refined with different composite methods, and the G3 method, together with the atomization reaction approach, was selected to calculate the enthalpy of formation at 0 K. This information was then used in statistical thermodynamics to calculate standard enthalpies of formation and entropy, as well as heat capacities at different temperatures. Our thermochemistry data exhibit good agreement with existing values in the literature, verifying the accuracy of our approach. The group additivity (GA) method is also examined based on the calculated values and significant differences are found, which indicates that GA values of relevant functional groups need to be updated. The database of thermochemistry quantities developed in this study is of particular interest not only for the update of GA values, but also to develop machine learning models for predicting the data of new species, which can assist in the development of combustion models. The impact of the developed dataset is illustrated by examining the variation in ignition delay times with the updated thermochemistry values.
CitationYalamanchi, K., Li, Y., Wang, T., Monge-Palacios, M., & Sarathy, M. (2022). Large-Scale Thermochemistry Calculations for Combustion Models. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4075603
SponsorsSupported by King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research under the award number OSR-2019-CRG7-4077.