In the oxidation of metal particles, iron has been considered to burn predominantly via heterogeneous reactions in the condensed phase. In this process, micron-sized metal oxide particles with a higher mass and volume than the initial particles are formed, which can be quite easily collected and recycled (reduced) using renewable energy sources.
Recent experimental studies from TU Darmstadt and TU Eindhoven have shown that particle melting, evaporation, gas-phase reactions (iron oxides), and nanoparticle formation are non-negligible. Liquid iron or iron oxides can evaporate from the particle surface, further oxidize in the gas phase and resolidify in the wake of the parent iron particle forming undesired nanoparticles. While nanoparticle formation is influenced by particle size and local thermodynamic conditions, such as temperature, particle porosity, and oxygen concentration, a comprehensive understanding is still far from being achieved.
This subproject aims to enhance the understanding of nanoparticle formation during the oxidation of iron particles using mathematical modeling and numerical simulations. The project is complementary to that of B. Böhm and A. Scholtissek , where experiments and model development are conducted for the ignition and oxidation of single iron particles. The experimental results of the project of B. Böhm on nanoparticle formation will be crucial to validate the numerical model and perform a combined experimental and numerical analysis that will facilitate a deeper understanding of the physico-chemical processes taking place. The simulation results from the detailed single particle (A. Scholtissek) will serve as a starting point for nanoparticle modeling. In addition, strong collaborations are foreseen with the projects by A. Dreizler , D. Trimis and C. Hasse , where multi-dimensional iron dust flames are experimentally and numerically investigated, respectively. In these more complex configurations, the information gained on the formation of nanoparticles in single-particle oxidation will be beneficial for estimating the interactions of the multiple physical phenomena.
