Modeling and optimization of synthesis parameters in nanostructure La1-xBaxNi1-yCuyO3 catalysts used in the reforming of methane with CO2

To achieve an efficient catalyst for the production of synthesis gas by dry reforming of methane a series of LaxBa1-xNiyCu1-yO3 perovskite-type oxides were synthesized with the sol gel auto-combustion method. The reaction was carried out under continuous flow of feed stream which included CO2, CH4 and Argon as an internal standard, under atmospheric pressure. In order to design the modified catalysts and to optimize the methane conversion, an artificial neural network (ANN) model linked with genetic algorithm (GA) was applied. A high R-2 value was obtained for training, validation and test sets of data: 0.99, 0.97 and 0.96 respectively. The model predicted that the maximum methane conversion was achieved via La0.996Ba0.004Ni0.6Cu0.4O3 (T-ca = 700 degrees C). The catalysts were characterized by XRD and FE-SEM. (C) 2017 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.