4.7 Article

Correlative statistical microstructural assessment of precipitates and their distribution, with simultaneous electron backscatter diffraction and energy dispersive X-ray spectroscopy

Journal

MATERIALS CHARACTERIZATION
Volume 176, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.matchar.2021.111071

Keywords

Electron microscopy; Materials characterisation; Nickel alloys; Stress corrosion cracking

Funding

  1. EPSRC Centre for Doctoral Training in Nuclear Energy [EP/L015900/1]
  2. Rolls Royce Submarines Limited
  3. Royal Academy of Engineering
  4. ShellImperial AIMS UTC

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Modern engineering alloys have custom microstructures with precipitates used for property control. Combined EDS and EBSD were used to characterize precipitate populations and analyze chemical differences between carbides found on various boundaries. Comparisons were made between different product forms to understand the distribution of these precipitates in demanding environments.
Modern engineering alloys have bespoke microstructures, where features such as precipitates are used to control properties. In many Ni-based alloys, carbo-nitride precipitates are introduced to strengthen and improve performance. These precipitates can be distributed throughout the microstructure and niobium rich carbides are often found at grain boundaries. In this work, we used combined energy dispersive X-ray spectroscopy (EDS) and electron backscatter diffraction (EBSD) to characterise the population of these precipitates. Processing of the EDS signal is used to label the Mo/Nb-rich precipitates, and their size and location are measured from maps using a circular Hough transform. This label map is combined with the grain boundary network (from EBSD analysis). Statistical analysis, using ANOVA testing, reveals differences in chemistry between carbides found in Ni-rich matrix grain interiors, on random high angle boundaries and on special boundaries (sigma 3 and sigma 9). These results are compared between wrought and power metallurgy product forms. These distributions are discussed in the context of their performance within demanding environments, such as reactor core internals.

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