Reactive oxygen and hydrogen species generation in radio-frequency atmospheric pressure plasmas - Experimental and numerical investigations

Atmospheric pressure plasmas (APPs) are known to be effective sources for reactive oxygen and nitrogen species (RS), making them potentially suitable for applications in biomedicine, where these species are believed to play a crucial role. However, in order to fully establish plasma sources in biomedicine, detailed characterisation of the RS produced is required. This is particularly challenging at atmospheric pressure, because of high collision rates among particles leading to fast de-excitation of excited states (quenching), complex gas mixing, and the small physical dimensions of the investigated systems, which effectively limits the accurate application of several commonly used diagnostic techniques applicable in low pressure systems. The motivation of this work is therefore to investigate the chemical kinetics in APPs, using a combination of simulations and experimental diagnostics, which are able to overcome the above-mentioned challenges. Experimentally, absolute RS species densities such as O, OH, H2O2, N, and NO, are determined using absorption spectroscopy in the UV and VUV spectral range, a technique independent on quenching and providing high spectral resolution. Spatially resolved two-photon absorption laser-induced fluorescence with sub-nanosecond temporal resolution enables the determination of atomic species densities (O and H) in the plasma effluent. Experimental values are benchmarked against zero-dimensional plasma-chemical kinetics simulations, which are used to investigate the principal reaction mechanisms leading to the formation and consumption of the investigated species. It is generally found that formation pathways depend strongly on the concentration of molecules in the feed gas, and the position in the plasma jet, as well as potential impurities being present in the feed gas, which is an important aspect for consideration for the applications of APPs. The results are used to propose possible tailoring schemes to optimise RS productions in APPs.