Dislocation model of strain anisotropy

Abstract

Dislocation model of strain anisotropy is presented. The dislocation theorem of strain broadening is suggested which means that strain broadening can only be caused by dislocation-type lattice defects. Based on this theorem strain anisotropy is modeled and accounted for by assuming that strain broadening is caused by dislocations or dislocation-type lattice defects. The effect of strain anisotropy is summarized in hkl dependent dislocation contrast factors, which can be either averaged over the permutations of hkl indices or are different for each different reflection. The dislocation model of strain anisotropy provides a powerful tool to analyze slip activity, Burgers vector populations, and plasticity on the basis of line profile analysis.

Characterization of the microstructure in random and textured polycrystals and single crystals by diffraction line profile analysis

“…The h k l dependence of strain broadening is known as strain anisotropy [27][28][29][30][31][32]. The determination of dislocation types, Burgers vector populations and dislocation densities can done in line profile analysis on the basis of the dislocation model of strain anisotropy [1][2][3][4]16,17,33].…”

The influence of liners with Ti, Ta or Ru finish on thin Cu films

“…According to XRD and SEM analysis, the grain sizes in the initial state range between 200 nm and 300 nm and do not vary significantly between the different samples. As a consequence, the differences in the resistivity can be solely attributed to the severely varying microstrain which is a result of inhomogeneous lattice strain originating from dislocations, grain interactions and defects such as impurities and interstitials [26]. Due to the high purity of the Cu films, the microstrain can be predominantly attributed to dislocations.…”

Atomistic Model of Metal Nanocrystals with Line Defects: Contribution to Diffraction Line Profile

“…The Krivoglaz-Wilkens approach, using Eq. 1 or similar approximations, is useful and easily implemented in the experimental data analysis; it has been extensively used in materials science (e.g., see work by Klimanek and Kuzel (1988), Kuzel and Klimanek (1988), Kuzel and Klimanek (1989), Ungar et al (1998), Ungar (2008), Scardi and Leoni (2002), Scardi et al (2007)] even if, as a matter of fact, it has never been fully validated. A few studies (Kamminga and Delhez, 2000;Kaganer and Sabelfeld, 2011;Kaganer and Sabelfeld, 2014) have tested Eq.…”