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γ’-Fe4N variants on α-Fe substrates grown by gaseous nitriding

Thursday (27.09.2018)
15:30 - 15:45 S1/03 - 123
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Nitriding is a very important thermochemical surface engineering process that is performed to improve fatigue, corrosion, and/or tribological properties of the surface and near-surface region. Nitriding of ferrous alloys results in the formation of a compound layer of different types of nitrides and a diffusion layer formed in larger depths. Despite nitriding is a well-known process and the formation of the nitride phases has been the subject of extensive study over decades, nucleation and early stages of iron nitride phase formation at the surface of the alloys are still of interest, because they are often crucial for the compound layer’s microstructure and consequently effect the component service properties.

In the current study, growth of γ’-Fe4N phase obtained by gaseous nitriding of polycrystalline α-Fe plates and single crystal α-Fe whiskers, to obtain a better understanding of the phase transformation, were investigated. The nitriding process was carried out in a NH3/H2-containing gas atmosphere at 773 K - 873 K. The resulting microstructure and the identification of the phases as well as the crystallographic orientation of crystallites belonging to a particular phase were characterized by scanning electron microscopy including electron backscatter diffraction (EBSD). The crystallographic orientation of the γ’-Fe4N phase in relation to the α-Fe phase revealing a near-Kurdjumov-Sachs orientation relation. Moreover, the γ’-Fe4N phase grows as multiple-grain islands on the polycrystalline α-Fe plates, whereby the morphology is determined by the orientation of the α-Fe phase relative to the surface. The growth habits of the multiple-grain islands on the surface of ferrite grains depends on the selection of the γ‘-Fe4N variants. The nitrided iron whiskers show formation of fewer γ‘-Fe4N variants as compared to the nitrided polycrystalline α-Fe plates.


Dipl.-Ing. Helge Schumann
TU Bergakademie Freiberg
Additional Authors:
  • Dr. Gunther Richter
    Max Planck Institute for Intelligent Systems
  • Prof. Dr. Andreas Leineweber
    TU Bergakademie Freiberg