Characterization and influence of deformation microstructure heterogeneity on recrystallization

Abstract

Abstract. The microstructure resulting from plastic deformation of metals typically contains heterogeneity on several length scales. This is also true for samples deformed to large strains, where an important form of heterogeneity is in the variation in microstructural refinement by high angle boundaries. A methodology for quantifying this type of heterogeneity based on the identification of areas classified as low misorientation regions (LMRs) is described, and some parameters for quantification of both the extent and length scale of LMRs are presented. It is then shown how this approach can be used to investigate the early stages of recrystallization in samples deformed to large strains, by direct comparison of electron backscatter diffraction (EBSD) maps of the same area before and after annealing. Methods for estimation of the stored energy of deformation from EBSD data are also surveyed and the problems of each for quantification of the local variation in stored energy are discussed, where it is concluded that a method based on the summation of the contributions from individual boundary segments is considered to be the best suited at present for characterization of the local variation in stored energy on the scale of the dislocation boundary features.

The influence of multiscale heterogeneity on recrystallization in nickel processed by accumulative roll bonding

“…3b), is consistent with previous observations of preferential nucleation within HMRs in other heavily deformed materials [19,24,25].…”

Crystallographic Analysis of Nucleation at Hardness Indentations in High-Purity Aluminum

“…For the present 13 grains this is validated by relating the measured hardness to the energy stored in the rolled deformation microstructures far away from indentations calculated based on the measured misorientations ≥ 2° across dislocation boundaries using the method described in [24]. As illustrated in figure 4, the grains with higher stored energies, as expected have higher hardness values.…”

“…The indenter strain direction will thus be different in the 4 parts and shift the crystallographic orientations in different directions. ② the sample was cold rolled 12% before the indentation so local variations due to this rolling deformation will be present in the microstructure [24]. The mechanism(s) leading to nucleation cannot directly be quantified from the present work.…”

Statistical analysis of dislocations and dislocation boundaries from EBSD data

“…One advantage of the above described method is that it allows estimating the measurement noise at each point of an EBSD map. As pointed out in different studies [14,[16][17][18], a lower threshold value should be used when calculating a dislocation density from the <θ(x)> values to account for the measurement noise, but then the measurement noise is considered homogenous in all conditions. This value is in general taken between 0.5° and 1.5° [18].…”

“…Then dislocation analysis from EBSD data is discussed. The main drawbacks of using EBSD data for quantitative analysis are related to the influence of the measurement noise and of the EBSD mapping step size [14][15][16][17][18][19][20]. A method based on the one originally proposed by Kamaya [21], described in the section 3.1, is applied to reduce those drawbacks.…”