• Title of article

    Multicomponent Au/MgO catalysts designed for selective oxidation of carbon monoxide: Application of a combinatorial approach Original Research Article

  • Author/Authors

    Andr?s Tompos، نويسنده , , Mih?ly Heged?s، نويسنده , , J?zsef L. Margitfalvi، نويسنده , , Ervin Gy. Szab?، نويسنده , , Lajos Végv?ri، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    9
  • From page
    348
  • To page
    356
  • Abstract
    A complex combinatorial approach has been applied for the design of multicomponent Au/MgO catalysts for CO oxidation in the presence of hydrogen. The combinatorial library design led to unique earlier unknown catalyst compositions. The best catalysts contained significant amount of Pb and Sm, which had never been reported before as useful components of PROX catalysts. In order to increase the diversity of experimental space different pretreatment conditions have been applied prior to catalytic tests. Actually, two catalyst libraries have been tested after (i) a reductive, and (ii) a combined reductive pretreatment. Significantly different optimum compositions have been obtained upon using these two pretreatment procedures. The combined reductive treatment resulted in a more cost effective optimum composition with significantly less components and smaller gold content in comparison to the best catalyst obtained upon using a simple reductive treatment. Further studies showed different ways of promoting action of modifiers. After reductive pretreatment the modifiers suppress the hydrogen consumption, while after combined reductive pretreatment the modifiers lead to the promotion of both oxidation reactions.
  • Keywords
    Catalyst library design , Combinatorial catalysis , High throughput experimentation , Multicomponent catalysts , Au/MgO , Artificial neural networks , Information mining , PROX , Modification of gold
  • Journal title
    Applied Catalysis A:General
  • Serial Year
    2008
  • Journal title
    Applied Catalysis A:General
  • Record number

    1153489