Decision tree analysis of past publications on catalytic steam reforming to develop heuristics for high performance: A statistical review

Abstract

In this study, a database containing 5508 experimental data points was constructed for the steam reforming of methane using 81 papers (out of 453 initially screened) published between 2004 and 2014. The database was reviewed and analyzed with the help of decision trees to extract trends, heuristics and correlations, which are not visible to the naked eyes, through the vast experimental works accumulated in the literature over the years. The performance variable was selected as CH4 conversion while 21 variables related to catalyst preparation and operational conditions were used as input variables. It was found from a simple analysis of the literature that Ni, Rh, Ru and Pt are the most frequently used active metals, and they are generally applied over the supports of Al(2)0(3), CeO2 and ZrO2 usually using impregnation methods. A decision tree analysis was also applied to the database to determine the ranges of the catalyst preparation and operational conditions leading to high CH4 conversion. It was found for the Ni based catalysts that, even though the reaction temperature higher than 970 K is always required to achieve high CH4 conversion, some additional set of conditions are also needed; the combination of other variables especially support type and the feed composition seems to determine the catalytic performance. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.