Statistical design and modeling of the process of methane partial oxidation using V-MCM-41 catalysts and the prediction of the formaldehyde production

Guoan Du, Yanhui Yang, Wei Qiu, Sangyun Lim, Lisa Pfefferle, Gary L. Haller

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

As a simplified approach to optimize the production of formaldehyde from partial oxidation of methane, this paper illustrates the application of statistical multivariate analysis and prediction through a multi-regression model, as well as the optimization of the processing parameters in the complex reaction process. This approach is advantageous, especially when experimental evaluation and optimization of a process is time consuming and expensive. By carrying out a finite number of experiments, statistical modeling in this work shows reasonable good prediction ability in terms of methane conversion, formaldehyde selectivity, and space time yield (STYHCHO). Moreover, not only are the synergistic effects between reaction parameters revealed, but also a comprehensive understanding of the whole production process over variation of the all reaction parameters (within the phase space represented by the experimental grid) are allowed.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalApplied Catalysis A: General
Volume313
Issue number1-2
DOIs
StatePublished - 25 Sep 2006
Externally publishedYes

Keywords

  • Design of experiment
  • Multiple regression model
  • Partial oxidation of methane
  • Regression
  • V-MCM-41

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