10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
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Monte Carlo Simulations of Particle Production and Processing: The Role of Evaporation and the Applied Nucleation Theories
GREGOR KOTALCZYK, Ivan Skenderovic, Frank Einar Kruis, University Duisburg-Essen
Abstract Number: 710 Working Group: Aerosol Modeling
Abstract The correct prediction of the properties of produced (or processed) aerosol particles makes complex modelling approaches necessary. Many simultaneous processes, such as coagulation, nucleation, condensation and evaporation have to be considered in a population balance modelling (PBM) approach, which makes the solution of the corresponding equations difficult.
Many simplifications are therefore applied, commonly, the evaporation of newly formed particles is not considered. Such an approach is justified in the cases of a chemical decomposition of a chemical precursor (e.g. (Lindackers et al., 1997)), but it might lead to grave deviations in the cases of physically induced nucleation, like it is encountered in condensation-evaporation reactors, during laser-ablation, or in the process of spark or arc discharges.
We present a Monte Carlo (MC) method based on weighted simulation particles (Zhao et al., 2009) for the solution of the PBM equations, which describes all the processes mentioned above including the evaporation. The recently proposed stochastic methodology (Kotalczyk and Kruis, 2017) for coagulation and nucleation is thereby coupled to a deterministic simulation of the growth and evaporation equations by means of an operator splitting approach (Celnik et al., 2007).
Recent studies have shown that the incorporation of the evaporation leads to severe deviations from the simulations without the evaporation for certain metallic systems under isothermal conditions (Kotalczyk et al., 2017). In this study, similar findings are presented for Fe and Ag systems, under typical non-isothermal conditions, which are encountered during particle production processes.
It is found, that the inclusion of the evaporation processes is necessary for certain applied temperature profiles. The deviation of the evaporation containing results from the non-evaporation containing results are discussed in dependency of the applied temperature gradient.
We also discuss the role of the applied nucleation theory, several classical approaches (differing in several orders of magnitude for the nucleation rates, as described in (Girshick and Chiu, 1990)) are compared with each other. It is found, that under certain temperature profiles, the inclusion of the evaporation process is of more significance than the choice of the nucleation theory.
This work was supported by the Deutsche Forschungsgemeinschaft in the scope of the priority programs SPP 1679 and SPP 1980.
References 1. Celnik, M., Patterson, R.I.A., Kraft, M., Wagner, W., 2007. Coupling a stochastic soot population balance to gas-phase chemistry using operator splitting. Combust. Flame 148 (3), 158–176. 2. Girshick, S.L., Chiu, C.-P., 1990. Kinetic nucleation theory: A new expression for the rate of homogeneous nucleation from an ideal supersaturated vapor. J. Chem. Phys. 93 (2), 1273–1277. 3. Kotalczyk, G., Kruis, F.E., 2017. A Monte Carlo method for the simulation of coagulation and nucleation based on weighted particles and the concepts of stochastic resolution and merging. J. Comput. Phys. 340, 276–296. 4. Kotalczyk, G., Skenderovic, I., Kruis, F.E., 2017. Modeling of Particle Formation in Arc Discharges by Monte-Carlo Based Population Balance Modeling. MRS Adv. 148, 1–8. 5. Lindackers, D., Strecker, M.G.D., Roth, P., Janzen, C., Pratsinis, S.E., 1997. Formation and growth of SiO2 particles in low pressure H2/O2/Ar flames doped with SiH4. Combustion Science and Technology 123 (1-6), 287–315. 6. Zhao, H., Kruis, F.E., Zheng, C., 2009. Reducing statistical noise and extending the size spectrum by applying weighted simulation particles in Monte Carlo simulation of coagulation. Aerosol Sci. Technol. 43 (8), 781–793.