Atmospheric pressure plasma sources are novel tools commonly used for a variety of technological purposes mostly due to the high chemical efficacy. They uniquely create necessary conditions for an efficient production of required reactive species that are essential for the applications. The states of the reactive species are delicately defined by a complex network of interactions between various plasma species as well as the ambient environment in contact with the plasma. These plasmas are already subject of scientific investigation, but they furthermore impose a set of challenges in the computational description of the physical system. A number of modelling approaches already exist in literature with a detailed description of the system; however, they often suffer from excessive numerical load mostly due to the large number of plasma species interacting over a wide range of time-scales. The consequent large simulation durations complicate the detailed plasma investigation and the model validation, hence a series of estimations are used. The estimation depends
on the specific plasma source and it is commonly either on the spatial resolution or on the chemical
description of the system for a pre-set electron energy distribution function (EEDF). However, both of These aspects play a significant role in the considered plasma sources and an investigation of the EEDF is also required. Furthermore, existing models ignore an important part of the chemical composition spanned by the vibrationally excited molecules and a detailed chemical description including the complete vibrational kinetics is still missing. The project addresses the aforementioned issues in two consecutive phases to probe the atmospheric pressure surface dielectric barrier discharges and plasma jets of N2/O2/H2O, He/O2 as well as He/CO2 admixtures in each possible aspect. In the first phase, a global model will be developed to describe the plasma volume and
surface chemical kinetics self-consistently coupled to the non-equilibrium electron phase space. The model will provide a detailed investigation of the composition space with a cost of spatial resolution. In the second phase, chemical reduction techniques will be implemented on this composition space and they will be used in spatially resolved models to reduce the numerical load.
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