Species measurements of the particulate matter reducing additive tri–propylene glycol monomethyl ether
Somers, Kieran P.
Curran, Henry J.
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Burke, Ultan, Shahla, Roya, Dagaut, Phillippe, Dayma, Guillaume, Togbé, Casimir, Somers, Kieran P., & Curran, Henry J. (2019). Species measurements of the particulate matter reducing additive tri–propylene glycol monomethyl ether. Proceedings of the Combustion Institute, 37(1), 1257-1264. doi: 10.1016/j.proci.2018.06.225
Reducing particulate matter formation and emissions by using fuel additives is a topic of interest for the petrochemical and automotive engineering industries. A compound which has been shown to be effective in this regard is tri-propylene glycol monomethyl ether (TPGME). This molecule consists of three ether linkages, an alcoholic group and alkyl branching including primary, secondary and tertiary C-H bonds. Its exotic structural features make it challenging to accurately model its oxidation. It is these same structural features that make this molecule both an exciting additive and a challenging fuel for kinetic modelers to understand. To provide insight into the oxidation of this molecule, species measurements have been performed in a jet- stirred reactor. Species concentrations are measured at three equivalence ratios; 0.5, 1.0 and 2.0, at a constant TPGME concentration of 1000 ppm, a pressure of 1 atm, a constant residence time of 70 ms and over the temperature range of 530-1250 K. The species measured include global reactant and product species, molecular oxygen, carbon monoxide, carbon dioxide, water and molecular hydrogen. In addition, a number of soot precursor species are measured namely, ethylene, propene, acetylene, allene, 1-butene, propyne and butadiene. A literature model is used to predict the experiments and erroneous low-temperature reactivity is predicted by the model. The low-temperature reaction kinetics and the base-mechanism of the model is updated using recent kinetic insights. Despite the large uncertainties in the assignment of the kinetic parameters for this large molecule these erroneous predictions are removed and the model is capable of rationalizing the formation of all species measured. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.