On the identification of superdislocations in the γ′-phase of single-crystal Ni-base superalloys – An application of the LACBED method to complex microstructures

Abstract Ni-base superalloys are used for turbine blades, which operate in the creep range at temperatures above 1000 °C. One of the objectives of modern materials science is to analyze the combination of elementary deformation and microstructural coarsening processes and to identify physically based micromechanical models which allow one to predict the mechanical behavior on the macroscale. High-temperature creep of single-crystal Ni-base superalloys is governed by dislocation plasticity in the well-known γ/γ′-microstructure. For a comprehensive description of plasticity, it is important to understand the nucleation, glide and climb of superdislocations in the γ′-phase. The rate-controlling dislocation processes have to be identified and therefore a reliable Burgers vector analysis of superdislocations is essential. Superdislocations exhibit complex dislocation cores, typically comprising superpartial dislocations and planar defects. Therefore, conventional Burgers vector analysis based on the invisibility criterion often fails, due to the presence of pronounced residual contrast. In the present work, large-angle convergent-beam electron diffraction (LACBED) is employed for Burgers vector determination of two characteristic superdislocations, of the standard and the more complex type. LACBED results are compared with results obtained using the conventional invisibility analysis. While both techniques work for the standard superdislocation, the conventional analysis fails to analyze the superdislocation, which shows pronounced residual contrast even under conditions of g · b = 0 and g · b × u = 0. In contrast, the LACBED technique allows for an unambiguous determination of the Burgers vector, including its magnitude and absolute sense. In the present study, the use of LACBED to identify dislocations in the complex microstructure of an Ni-base superalloy is outlined and the better performance of LACBED as compared to the conventional gb-analysis is discussed.