Modeling study of the anti-knock tendency of substituted phenols as additives: an application of the reaction mechanism generator (RMG)
Literature Information
Peng Zhang, Nathan W. Yee, Sorin V. Filip, Casey E. Hetrick, Bin Yang, William H. Green
This work presents kinetic modeling efforts to evaluate the anti-knock tendency of several substituted phenols if used as gasoline additives. They are p-cresol, m-cresol, o-cresol, 2,4-xylenol, 2-ethylphenol, and guaiacol. A detailed kinetic model was constructed to predict the ignition of blends of the phenols in n-butane with the help of reaction mechanism generator (RMG), an open-source software package. The resulting model, which has 1465 species and 27 428 reactions, was validated against literature n-butane ignition data in the low-to-intermediate temperature range. To rank the anti-knock tendency of the additives, engine-like simulations were performed in a closed adiabatic homogenous batch reactor with a volume history derived from the pressure profile of a real research octane number (RON) engine test. The ignition timings of the additive blends were compared to that of primary reference fuels (PRFs) to quantitatively predict the anti-knock ability. The model predictions agree well with experimental determinations of the changes in RON induced by the additives. This study explains the chemical mechanism by which methyl-substituted phenols increase RON, and demonstrates how fundamental chemical kinetics can be used to evaluate practical fuel additive performance.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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