Optimal catalyst texture in macromolecule conversion: A computational and experimental study

V. S. Semeykina, E. G. Malkovich, Ya V. Bazaikin, A. I. Lysikov, E. V. Parkhomchuk

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Evolution of alumina catalyst texture during macromolecule conversion with an emphasis on heavy oil hydroprocessing was theoretically estimated using geometrical characteristics of the porous media that were in turn calculated via Monte-Carlo methods and methods of the graph theory. Two types of alumina texture have been modeled: unimodal mesoporous structure of conventional catalyst and bimodal meso-macroporous structure of the catalyst, which can be prepared by hard-templating method. To estimate the decreasing of the effectiveness coefficient for these two types of catalysts, a solution for the diffusion equation on the cylinder pellet was found. Deactivation was modeled by the most simple way of monotonic increase of alumina grain radius, which represented deposition of coke and metal species onto the surface of grains. The comparison of theoretical predictions with experimental results on heavy oil conversion under conditions close to industrial ones showed the correlation between the experiment and the model – hierarchical texture prolonged the catalyst lifetime in both cases. Nevertheless, to obtain accurate predictions of the necessary properties of the catalyst texture, the deactivation model should be complicated.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalChemical Engineering Science
Volume188
DOIs
Publication statusPublished - 12 Oct 2018

Keywords

  • Deactivation
  • Diffusion modeling
  • Hierarchical catalyst
  • Macromolecule
  • Macropores
  • Percolation theory
  • HYDROTREATING REACTIONS
  • HYDRODEMETALATION
  • DIFFUSION
  • DEACTIVATION

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