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Fractal analysis of X-ray diffraction patterns of zirconia–alumina mixed oxides

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  • Gordillo-Cruz, E.
  • Alvarez-Ramirez, J.
  • González, F.
  • de los Reyes, J.A

Abstract

X-ray diffractograms of amorphous material commonly exhibit complex shapes with broad background noise. The X-ray diffraction signal of amorphous material possesses order only at the firsts neighbors (i.e., at the sub-nanometric level). Extracting patterns from such complex signal can provide valuable information on the crystalline structure of amorphous material. In this regard, the aim of this study was explore the use of fractal analysis for extracting structural features of amorphous material from X-ray diffraction signals containing strong background fluctuations To this end, well-characterized mixtures of ZrO2-Al2O3 were prepared by the sol–gel method and calcined at the relative low temperature of 500 °C during 5 h. The fractal analysis carried out with detrended fluctuation analysis for samples with different ZrO2/Al2O3 relative content suggested the presence of long-term correlations. This means that the background noise is not random, containing patterns related to the incipient crystallinity of the mixed oxides. The analysis was complemented with Rietveld refinement using monoclinic and tetragonal symmetries of ZrO2. Despite pure ZrO2 synthesized in the same conditions as those compounds of the mixture ZrO2-Al2O3 is mostly monoclinic, consistent results were found when modeling specimens of the mixture as ZrO2-Al2O3 being tetragonal. Thus, adding Al2O3 has a similar effect in retarding the formation of monoclinic ZrO2 in the mixture compounds. Overall, the results showed that fractal analysis can be a useful tool for extracting valuable information on the structure of semi-crystalline materials from X-ray diffraction signals.

Suggested Citation

  • Gordillo-Cruz, E. & Alvarez-Ramirez, J. & González, F. & de los Reyes, J.A, 2018. "Fractal analysis of X-ray diffraction patterns of zirconia–alumina mixed oxides," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 635-643.
  • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:635-643
    DOI: 10.1016/j.physa.2018.08.057
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    References listed on IDEAS

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    1. Alvarez-Ramirez, Jose & Alvarez, Jesus & Rodriguez, Eduardo & Fernandez-Anaya, Guillermo, 2008. "Time-varying Hurst exponent for US stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6159-6169.
    2. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
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    Cited by:

    1. Rodríguez-Cuadrado, Javier & San Martín, Jesús, 2022. "Shielding material distributions and associated fractals," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).

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