Deformation mechanisms in micron-sized PST TiAl compression samples: Experiment and model
Source abstract
Abstract
Abstract Titanium aluminides are the most promising intermetallics for use in aerospace and automotive applications. Consequently, it is of fundamental interest to explore the deformation mechanisms occurring in this class of materials. One model material which is extensively used for such studies are polysynthetically twinned (PST) TiAl crystals, which consist predominantly of parallel γ-TiAl and, fewer, α 2 -Ti 3 Al lamellae. In the present study, PST TiAl crystals with a nominal composition of Ti–50 at.% Al were machined by means of the focused ion beam (FIB) technique into miniaturized compression samples with a square cross-section of approximately 9 μm × 9 μm. Compression tests on the miniaturized samples were performed in situ inside a scanning electron microscope using a microindenter equipped with a diamond flat punch. After deformation, thin foils were cut from the micro-compression samples and thinned to electron transparency using a FIB machine in order to study the deformation structure by transmission electron microscopy (TEM). The TEM studies reveal mechanical twinning as the main deformation mechanism at strains of 5.4%, while at strains of 8.3% dislocation glide becomes increasingly important. The experimentally observed twins scale in size with the width of the γ-TiAl lamella. A kinematic and thermodynamic model is developed to describe the twin-related length change of the micro-compression sample at small strains as well as the relationship of an increase of twin width with increasing γ-TiAl lamella thickness. The developed twin model predicts a width of the twins in the range of a few nanometers, which is in agreement with experimental findings.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Intermetallics and Advanced Alloy Properties · MXene and MAX Phase Materials · Semiconductor materials and interfaces
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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