Post plasma catalytic removal of methanol over Mn Ce catalysts in an atmospheric dielectric barrier discharge
Abstract A post plasma catalysis system has been developed for the removal of methanol over Mn Ce oxide catalysts with different Mn/Ce molar ratios at low temperatures. The Mn50Ce50 oxide catalyst (Mn/Ce 1:1) shows the best performance in terms of methanol removal efficiency and energy efficiency of the plasma catalytic process. The maximum methanol removal efficiency of 95.4% can be achieved at a discharge power of 15 W and a gas flow rate of 1 L/min, while the highest energy efficiency of the plasma catalytic process is 47.5 g/kW h at 1.9 W. The combination of plasma and Mn Ce catalysts significantly reduces the formation of major by products (methane, formaldehyde and formic acid) based on the Fourier transform infrared spectra. Possible reaction mechanisms and pathways of the post plasma catalytic removal of methanol are also proposed. A three layer back propagation artificial neural network (ANN) model has been developed to get a better understanding of the roles of different process parameters on methanol removal efficiency and energy efficiency in the post plasma catalytic process. The predicted data from the ANN model show a good agreement with the experimental results. Catalyst composition (i.e. Mn/Ce ratio) is found to be the most important factor affecting methanol removal efficiency with a relative importance of 31.53% while the discharge power is the most influential parameter for energy efficiency with a relative weight of 30.40% These results indicate that the well trained ANN model provides an alternative approach for accurate and fast prediction of the plasma catalytic chemical reactions.