Low-temperature plasma chemical kinetic models are particularly important to the plasma community. These models typically require dozens of inputs, especially rate coefficients. The latter are not always precisely known and… Click to show full abstract
Low-temperature plasma chemical kinetic models are particularly important to the plasma community. These models typically require dozens of inputs, especially rate coefficients. The latter are not always precisely known and it is not surprising that the error on the rate coefficient data can propagate to the model output. In this paper, we present a model that uses N = 400 different combinations of rate coefficients based on the uncertainty attributed to each rate coefficient, giving a good estimation of the uncertainty on the model output due to the rate coefficients. We demonstrate that the uncertainty varies a lot with the conditions and the type of output. Relatively low uncertainties (about 15%) are found for electron density and temperature, while the uncertainty can reach more than an order of magnitude for the population of the vibrational levels in some cases and it can rise up to 100% for the CO2 conversion. The reactions that are mostly responsible for the largest uncertainties are identified. We show that the conditions of pressure, gas temperature and power density have a great effect on the uncertainty and on which reactions lead to this uncertainty. In all the cases tested here, while the absolute values may suffer from large uncertainties, the trends observed in previous modeling work are still valid. Finally, in accordance with the work of Turner, a number of 'good practices' is recommended.
               
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