4.1 Article

Predicting polycyclic aromatic hydrocarbon formation with an automatically generated mechanism for acetylene pyrolysis

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出版社

WILEY
DOI: 10.1002/kin.21421

关键词

acetylene; detailed mechanism; Reaction Mechanism Generator; polycyclic aromatic hydrocarbon; pyrolysis

资金

  1. SaudiBasic Industries Corporation
  2. DFG Research Fellowship [JO 1526/1-1]

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The RMG-generated model accurately predicts major species profiles but underestimates the formation of anthracene, phenanthrene, and pyrene, with PAHs beyond pyrene not captured.
Using Reaction Mechanism Generator (RMG), we have automatically constructed a detailed mechanism for acetylene pyrolysis, which predicts formation of polycyclic aromatic hydrocarbons (PAHs) up to pyrene. To improve the data available for formation pathways from naphthalene to pyrene, new high-pressure limit reaction rate coefficients and species thermochemistry were calculated using a combination of electronic structure data from the literature and new quantum calculations. Pressure-dependent kinetics for the C4H4potential energy surface calculated by Zador et al. were incorporated to ensure accurate pathways for acetylene initiation reactions. After adding these new data into the RMG database, a pressure-dependent mechanism was generated in a single RMG simulation which captures chemistry from C2to C16. In general, the RMG-generated model accurately predicts major species profiles in comparison to plug-flow reactor data from the literature. The primary shortcoming of the model is that formation of anthracene, phenanthrene, and pyrene are underpredicted, and PAHs beyond pyrene are not captured. Reaction path analysis was performed for the RMG model to identify key pathways. Notable conclusions include the importance of accounting for the acetone impurity in acetylene in accurately predicting formation of odd-carbon species, the remarkably low contribution of acetylene dimerization to vinylacetylene or diacetylene, and the dominance of the hydrogen abstraction C2H2addition (HACA) mechanism in the formation pathways to all PAH species in the model. This work demonstrates the improved ability of RMG to model PAH formation, while highlighting the need for more kinetics data for elementary reaction pathways to larger PAHs.

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