Experimental and numerical study of the evolution of soot primary particles in a diffusion flame
Proceedings of the Combustion Institute
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Botero, M., Eaves, N., Dreyer, J., Sheng, Y., Akroyd, J., Yang, W., & Kraft, M. (2019). Experimental and numerical study of the evolution of soot primary particles in a diffusion flame. Proceedings of the Combustion Institute, 37 (2), 2047-2055. https://doi.org/10.1016/j.proci.2018.06.185
© 2018 The Combustion Institute. The evolution of primary soot particles is studied experimentally and numerically along the centreline of a co-flow laminar diffusion flame. Soot samples from a flame fueled with C2H4are taken thermophoretically at different heights above the burner (HAB), their size and nano-structure are analysed through TEM. The experimental results suggest that after inception, the nascent soot particles coagulate and coalesce to form larger primary particles (~5 to 15 nm). As these primary particles travel along the centreline, they grow mainly due coagulation and condensation and a layer of amorphous hydrocarbons (revealed by HRTEM) forms on their surface. This amorphous layer appears to promote the aggregation of primary particles to form fractal structures. Fast carbonisation of the amorphous layer leads to a graphitic-like shell around the particles. Further graphitization compacts the primary particles, resulting in a decrease of their size. Towards the flame tip the primary particles decrease in size due to rapid oxidation. A detailed population balance model is used to investigate the mechanisms that are important for prediction of primary particle size distributions. Suggestions are made regarding future model development efforts. Simulation results indicate that the primary particle size distributions are very sensitive to the parameterization of the coalescence and particle rounding processes. In contrast, the average primary particle size is less sensitive to these parameters. This demonstrates that achieving good predictions for the average primary particle size does not necessarily mean that the distribution has been accurately predicted.
External DOI: https://doi.org/10.1016/j.proci.2018.06.185
This record's URL: https://www.repository.cam.ac.uk/handle/1810/284755