More than 90% of industrially produced nanoparticles are made by flame synthesis. Spray flame synthesis is a more specific class of a synthesis process that allows for a vast variety of particle precursors and solvents and may be suited for the production of tailor-made nanoparticles with well-defined properties. However, the complex interaction of spray, turbulence, phase change, precursor consumption, chemistry and particle formation in spray flame synthesis hampers our fundamental understanding of the underlying physics, which is required for further process optimisation. In this project a detailed model for spray flame synthesis shall be derived and a reliable simulation program for nanoparticle spray synthesis shall be developed and validated. It is crucial that the model is capable of capturing the interactions of flame chemistry, precursors and turbulence, which is inherently difficult due to the wide range of time scales involved in the process. The model relies on the recently proposed multiple mapping conditioning (MMC) approach, which is an accurate model for turbulence-chemistry interactions and has recently been extended to spray combustion. The MMC model will describe the gas phase chemistry, precursor consumption and particle formation using a sparse set of stochastic particles. Turbulence will be modelled using the accurate large eddy simulation (LES) methodology. The joint MMC-LES model will be validated by comparison to results from novel state-of-the-art laser diagnostics, namely laser- induced fluorescence (LIF), particle image velocimetry (PIV) and phase-doppler anemometry (PDA), conducted on a well-defined experimental setup for spray flame synthesis. The project has a strong focus on the interactive development of both the predictive model and the experimental diagnostics, such that both methods are improved in a collaborative approach.
This project is part of SPP1980 which is a wider research initiative to improve our understanding of the different aspects of spray flame synthesis and to develop an integrated approach for the process design.
- J. Kirchmann, F. J. W. A. Martins, A. Kumar, A. Kronenburg, and F. Beyrau, “Assessment of a Stochastic Particle Approach for IPC Spray Flame Synthesis using Synthetic ELS Signals,” in 30. Deutscher Flammentag 2021, 28-29 Sept, Hannover-Garbsen, Germany, Hannover-Garbsen, (2021).
- F. J. W. A. Martins, J. Kirchmann, A. Kronenburg, and F. Beyrau, “Quantification and mitigation of PIV bias errors caused by intermittent particle seeding and particle lag by means of large eddy simulations,” Measurement Science and Technology, vol. 32, no. 10, p. 104006, (2021).
- F. J. W. A. Martins, A. Kronenburg, and F. Beyrau, “Single-shot two-dimensional multi-angle light scattering (2D-MALS) technique for nanoparticle aggregate sizing,” Applied Physics B, vol. 127, no. 4, p. 51, (2021).
- J. Kirchmann, A. Kronenburg, O. T. Stein, and M. J. Cleary, “Two-phase sparse-Lagrangian MMC-LES of dilute ethanol spray flames,” Proc. Combust. Inst., vol. 38, pp. 3343–3350, (2021).
- F. J. W. A. Martins, J. Kirchmann, A. Kronenburg, and F. Beyrau, “Experimental investigation of axisymmetric, turbulent, annular jets discharged through the nozzle of the SPP1980 SpraySyn burner under isothermal and reacting conditions,” Experimental Thermal and Fluid Science, vol. 114, p. 110052, (2020).
- J. Kirchmann, A. Kronenburg, O. T. Stein, and M. J. Cleary, “Sparse-Lagrangian MMC-LES of dilute ethanol spray flames,” in 29. Deutscher Flammentag 2019, 17-18 June, Bochum, Germany, (2019).
- G. Neuber, A. Kronenburg, O. T. Stein, and M. J. Cleary, “MMC-LES modelling of droplet nucleation and growth in turbulent jets,” Chem. Eng. Sci., vol. 167, pp. 204–218, (2017).