Experimental and kinetic study on aromatic formation in counterflow diffusion flames of methane and methane/ethylene mixtures

Peng Jiang, Lei Xu, Qianlei Wang, Zhen Wang, Suk Ho Chung, Yu Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Aromatics are molecular soot precursors, yet detailed kinetic mechanisms describing their formation in flame environments are insufficient even for the simplest hydrocarbon fuel of methane. Considering the building roles of methane-related chemistry in current hierarchically-structured mechanisms, the present study is devoted to the chemistry of aromatic formation in CH4 flames. We established a series of incipiently sooting methane counterflow diffusion flames (CDF) and characterized their thermochemical structures including the scalar fields of temperature, concentrations of major species, C2–C4 minor intermediates, benzene, large aromatic species, and soot volume fraction. The measurement techniques include tunable diode laser absorption spectroscopy (TDLAS), gas chromatography–mass spectrometer (GC–MS) and laser induced incandescence (LII). The experimental dataset was then used to assess various recently proposed kinetic mechanisms. The results showed that the literature mechanisms tested would significantly overpredict benzene formation in CH4 CDFs (up to a factor of 10). In addition, none of the tested mechanisms could capture the experimentally observed suppressing effects of CH4 addition on the formation of aromatic species in C2H4 CDFs. Potential reactions responsible for the model failures are discussed. The main contributions of this study are to: 1) identify the limitations of existing aromatic mechanisms when applied to methane CDFs; 2) clarify potential reactions/pathways related to model deficiencies; 3) provide novel experimental dataset covering both gas-phase speciation and soot for methane CDFs. It is our hope that the present data and analysis would deepen our understanding on benzene formation chemistry, and contribute to the refinement of aromatic formation predictive models.
Original languageEnglish (US)
Pages (from-to)129304
JournalFuel
Volume354
DOIs
StatePublished - Jul 28 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-09-06
Acknowledgements: This work was supported by National Natural Science Foundation of China (51976142) and Hubei Provincial Natural Science Foundation (2021CFA074). SHC was supported by King Abdullah University of Science and Technology. We also gratefully acknowledge Dr. Kevin Gleason and Prof. Alessandro Gomez of Yale University for providing the raw data that was used to validate our GC experiments.

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Organic Chemistry
  • General Chemical Engineering
  • Fuel Technology

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