Sustainable gas conversion by gliding arc plasmas: a new modelling approach for reactor design improvement

Abstract

We present a new modelling approach for the design and development of gliding arc plasma reactors, revealing the fluid dynamics, the arc behaviour and the plasma chemistry by solving a unique combination of five complementary models.

Abstract

Research in plasma reactor designs is developing rapidly as plasma technology is gaining increasing interest for sustainable gas conversion applications, like the conversion of greenhouse gases into value-added chemicals and renewable fuels, and fixation of N ₂ from air into precursors of mineral fertilizer. As plasma is generated by electric power and can easily be switched on/off, these applications allows for efficient conversion and energy storage of intermittent renewable electricity. In this paper, we present a new comprehensive modelling approach for the design and development of gliding arc plasma reactors, which reveals the fluid dynamics, the arc behaviour and the plasma chemistry by solving a unique combination of five complementary models. This results in a complete description of the plasma process, which allows one to efficiently evaluate the performance of a reactor and indicate possible design improvements before actually building it. We demonstrate the capabilities of this method for an experimentally validated study of plasma-based NO _x formation in a rotating gliding arc reactor, which is gaining increasing interest as a flexible, electricity-driven alternative for the Haber–Bosch process. The model demonstrates the importance of the vortex flow and the presence of a recirculation zone in the reactor, as well as the formation of hot spots in the plasma near the cathode pin and the anode wall that are responsible for most of the NO _x formation. The model also reveals the underlying plasma chemistry and the vibrational non-equilibrium that exists due to the fast cooling during each arc rotation. Good agreement with experimental measurements on the studied reactor design proves the predictive capabilities of our modelling approach.