Screening of additives to ni-based methanation catalyst for enhanced anti-sintering performance

Abstract

The resistance to sintering of Ni/Al2O3 catalysts with different additives for methanation reaction was modeled and predicted by data mining. In the screening, the resistance to sintering of Na, Ca, Ce, Mg, La, Cu, Zn, Zr, In, Mo, and Ti promoted Ni/Al2O3 catalyst were measured in terms of the increased rate of the size of the metallic nickel particles. The resistance to sintering of catalysts, described by the increased rate of Ni particle size as well as basic physicochemical properties of the 11 selected elements, was adopted for optimization model construction by data mining. Through regression model prediction and experimental verification, Cs was found to be an additive, and promotes the resistance to sintering mostly for Ni/Al2O3 catalysts. This result provides further evidence that data mining techniques can be employed as a highly efficient tool for the discovery of new catalysts in comparison with the traditional experimental method.