Three-dimensional modeling of silicon nanoparticles synthesis in the downstream region of a DC non-transferred arc plasma torch

Summary form only given. DC non-transferred arc plasmas are commonly used for nanoparticle production at commercial and laboratory scale. Plasma high temperature (around 10000 K) offers the possibility to vaporize a wide range of different precursors and to obtain very high cooling rates for the production of metal, oxide or composite nanoparticles. The typical approach in DC non-transferred arc torches is to inject solid, liquid or gaseous precursor materials in the tail of the plasma discharge, resulting in the formation of a vapour that is transported in a reaction chamber downstream the plasma torch. Nanoparticle nucleation occurs when vapour reaches the supersaturated state in colder regions in the reaction chamber, where additional quenching gas or carrier gas can be injected to control particle formation and to prevent nanoparticle deposition on the walls. In order to optimize the plasma synthesis process for a specific material, a series of issues must be addressed, such as: reduction of the fraction of non-vaporized precursor, reduction of precursor and nanoparticle deposition on the walls, identification of suitable quench injection conditions to obtain targeted nanoparticle. In this work, a 3D model of the DC non-transferred arc synthesis of Si nanoparticles has been developed that includes plasma flow in a conical reaction chamber with multiple inlets for quench gases, trajectory and thermal history of radially injected solid Si precursor, and transport of the nucleated nanoparticles using the Method of Moments. Plasma flow and temperature field at the chamber inlet are obtained by means of the Elenbaas-Heller equations for a 200kW plasma column of Ar-H₂ gas mixture, to simulate the outflow of a DC non-transferred torch without including it in the domain. Computations have been done for different precursor size distributions and feed rates, and for different quench and carrier gas injection conditions. Variation on the precursors particle size distribution and feed rate is shown to have an important effect on the amount of non-vaporized precursors, vapor concentration field and nanoparticle properties, whereas nanoparticle and precursor deposition on the reactor walls depends strongly on the flow patterns generated by the quenching and carrier gases. Optimal operating conditions have been identified that allow maximizing nanoparticle production while reducing material deposition on chamber walls.