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The Influence of Anionic Species (Cl, NO3, SO42−) on the Transformation and Solubility of Platinum in Platinum/Aluminum Oxide Model Substance

  • Fathi ZereiniEmail author
  • Ilka Müller
  • Clare L. S. Wiseman
Chapter
Part of the Environmental Science and Engineering book series (ESE)

Abstract

The solubility of Pt in a platinum/aluminum oxide (Pt/Al2O3) compound as a function of substrate age (fresh vs. aged) and acid solution pH and anionic species concentration (Cl, \({\text{NO}}_{3}^{ - }\), \({\text{SO}}_{4}^{2 - }\)) was examined. The results demonstrated that solution pH strongly influenced Pt solubility, with a decrease in elemental solubility observed with increases in pH for all three solutions examined. The presence of Cl in solution had a stronger influence on Pt solubility compared to \({\text{NO}}_{3}^{ - }\) and \({\text{SO}}_{4}^{2 - }\). Solubility was also dependent on reaction time, with the highest solubility observed for the longer extraction period of 30 days. In addition, Pt solubility was also higher for “fresh” compared to the aged model substance. The examination of surface particle chemistry of the model substrate using x-ray photoelectron spectroscopy (XPS) following treatment with 1 M and 0.1 M HCl showed a transformation in Pt bound to alumina particles. After treatment, XPS confirmed the increased presence of Pt(II) on sample particle surfaces. In contrast, untreated samples consisted primarily of particles with surfaces dominated by Pt(VI). Samples which were filtered under normal atmospheric conditions contained particles with more Pt(II) on particle surfaces compared to samples which were filtered in the presence of N gas. A similar trend was also observed for samples treated with 1 M HCl. The transformation of Pt was also influenced by the presence of O which suggests that Pt can be easily changed into more soluble species under environmental conditions.

Keywords

Particle Surface Aged Sample Model Substance Platinum Group Element Catalytic Converter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Fathi Zereini
    • 1
    Email author
  • Ilka Müller
    • 2
  • Clare L. S. Wiseman
    • 3
  1. 1.Department of Environmental Analytical Chemistry, Institute for Atmospheric and Environmental SciencesGoethe UniversityFrankfurt am MainGermany
  2. 2.Taunusstraße 4GelnhausenGermany
  3. 3.School of the Environment, Earth Sciences CentreUniversity of TorontoTorontoCanada

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