Orientation dependent pinning of (sub)grains by dispersoids during recovery and recrystallization in an Al-Mn alloy

The recrystallized grain size and texture in alloys can be controlled via the microchemistry state during thermomechanical processing. The influence of concurrent precipitation on recovery and recrystallization is here analyzed by directly correlating (sub)grains of P, CubeND or Cube orientation with second-phase particles in a cold-rolled and non-isothermally annealed Al-Mn alloy. The recrystallized state is dominated by coarse elongated grains with a strong P, weaker CubeND and even weaker Cube texture. The correlated data enables orientation dependent quantification of the density and size of dispersoids on sub-boundaries and subgrains in the deformation zones around large constituent particles. A new modified expression for the Smith-Zener drag from dispersoids on sub-boundaries is derived and used. The results show that the drag on (sub)grain boundaries from dispersoids is orientation dependent, with Cube subgrains experiencing the highest drag after recovery and partial recrystallization. The often observed size advantage of Cube subgrains in Al alloys is not realized due to the increased drag, thereby promoting particle-stimulated nucleation (PSN). Relatively fewer and larger dispersoids in deformation zones around large particles give a reduced Smith-Zener drag on PSN nuclei, thus further strengthening the effect of PSN. Observations substantiating the stronger P texture compared to the CubeND texture are a higher frequency of P subgrains and a faster growth of these subgrains. The applied methodology enables a better understanding of the mechanisms behind the orientation dependent nucleation and growth behavior during recovery and recrystallization with strong concurrent precipitation in Al-Mn alloys. In particular, the methodology gives new insights into the strong P and CubeND textures compared to the Cube texture

Correlated subgrain and particle analysis of a recovered Al-Mn alloy by directly combining EBSD and backscatter electron imaging

Correlated analysis of (sub)grains and particles in alloys is important to understand transformation processes and control material properties. A multimodal data fusion workflow directly combining subgrain data from electron backscatter diffraction (EBSD) and particle data from backscatter electron (BSE) images in the scanning electron microscope is presented. The BSE images provide detection of particles smaller than the applied step size of EBSD down to 0.03 $\mu$m in diameter. The workflow is demonstrated on a cold-rolled and recovered Al-Mn alloy, where constituent particles formed during casting and dispersoids formed during subsequent heating affect recovery and recrystallization upon annealing. The multimodal dataset enables statistical analysis including subgrains surrounding constituent particles and dispersoids' location with respect to subgrain boundaries. Among the subgrains of recrystallization texture, Cube{001}\left subgrains experience an increased Smith-Zener drag from dispersoids on their boundaries compared to CubeND{001}\left and P{011}\left subgrains, with the latter experiencing the lowest drag. Subgrains at constituent particles are observed to have a growth advantage due to a lower dislocation density and higher boundary misorientation angle. The dispersoid size per subgrain boundary length increases as a function of misorientation angle. The workflow should be applicable to other alloy systems where there is a need for analysis correlating grains and grain boundaries with secondary phases smaller than the applied EBSD step size but resolvable by BSE imaging

The evolution of precipitate crystal structures in an Al-Mg-Si(-Cu) alloy studied by a combined HAADF-STEM and SPED approach

This work presents a detailed investigation into the effect of a low Cu addition (0.01 at.%) on precipitation in an Al-0.80Mg-0.85Si alloy during ageing. The precipitate crystal structures were assessed by scanning transmission electron microscopy combined with a novel scanning precession electron diffraction approach, which includes machine learning. The combination of techniques enabled evaluation of the atomic arrangement within individual precipitates, as well as an improved estimate of precipitate phase fractions at each ageing condition, through analysis of a statistically significant number of precipitates. Based on the obtained results, the total amount of solute atoms locked inside precipitates could be approximated. It was shown that even with a Cu content close to impurity levels, the Al-Mg-Si system precipitation was significantly affected with overageing. The principal change was due to a gradually increasing phase fraction of the Cu-containing Q'-phase, which eventually was seen to dominate the precipitate structures. The structural overtake could be explained based on a continuous formation of the thermally stable Q'-phase, with Cu atomic columns incorporating less Cu than what could potentially be accommodated.Comment: 13 pages, 10 figures, 2 table

Optimizing compositional and atomic-level information of oxides in atom probe tomography

Atom probe tomography (APT) is a 3D analysis technique that offers unique chemical accuracy and sensitivity with sub-nanometer spatial resolution. Recently, there is an increasing interest in the application of APT to complex oxides materials, giving new insight into the relation between local variations in chemical composition and emergent physical properties. However, in contrast to the field of metallurgy, where APT is routinely applied to study materials at the atomic level, complex oxides and their specific field evaporation mechanisms are much less explored. Here, we perform APT measurements on the hexagonal manganite ErMnO3 and systematically study the effect of different experimental parameters on the measured composition and atomic structure. We demonstrate that both the mass resolving power (MRP) and compositional accuracy can be improved by increasing the charge-state ratio (CSR) working at low laser energy (< 5 pJ). Furthermore, we observe a substantial preferential retention of Er atoms, which is suppressed at higher CSRs. We explain our findings based on fundamental field evaporation concepts, expanding the knowledge about the impact of key experimental parameters and the field evaporation process in complex oxides in general

Characterization of ferroelectric domain walls by scanning electron microscopy

Ferroelectric domain walls are a completely new type of functional interface, which have the potential to revolutionize nanotechnology. In addition to the emergent phenomena at domain walls, they are spatially mobile and can be injected, positioned, and deleted on demand, giving a new degree of flexibility that is not available at conventional interfaces. Progress in the field is closely linked to the development of modern microscopy methods, which are essential for studying their physical properties at the nanoscale. In this article, we discuss scanning electron microscopy (SEM) as a powerful and highly flexible imaging technique for scale-bridging studies on domain walls, continuously covering nano- to mesoscopic length scales. We review seminal SEM experiments on ferroelectric domains and domain walls, provide practical information on how to visualize them in modern SEMs, and provide a comprehensive overview of the models that have been proposed to explain the contrast formation in SEM. Going beyond basic imaging experiments, recent examples for nano-structuring and correlated microscopy work on ferroelectric domain walls are presented. Other techniques, such as 3D atom probe tomography, are particularly promising and may be combined with SEM in the future to investigate individual domain walls, providing new opportunities for tackling the complex nanoscale physics and defect chemistry at ferroelectric domain walls