Abstract
Crystallographic texture in polycrystalline materials is often developed as preferred orientation distribution of grains during thermo-mechanical processes. Texture dominates many macroscopic physical properties and reflects the histories of structural evolution, hence its measurement and control are vital for performance optimisation and deformation history interogation in engineering and geological materials. However, exploitations of texture are hampered by state-of-the-art characterisation techniques, none of which can routinely deliver the desirable non-destructive, volumetric measurements, especially at larger lengthscales. Here we report a direct and general methodology retrieving important lower-truncation-order texture and phase information from acoustic (compressional elastic) wave speed measurements in different directions through the material volume (avoiding the need for forward modelling). We demonstrate its deployment with ultrasound in the laboratory, where the results from seven representative samples are successfully validated against measurements performed using neutron diffraction. The acoustic method we have developed includes both fundamental wave propagation and texture inversion theories which are free from diffraction limits, they are arbitrarily scalable in dimension, and can be rapidly deployed to measure the texture of large objects. This opens up volumetric texture characterisation capabilities in the areas of material science and beyond, for both scientific and industrial applications.
Highlights
Crystallographic texture refers to the preferred orientation distribution of crystals in polycrystalline materials, which is normally developed during the thermo-mechanical deformation or recrystallisation processes [1,2]
The (111) and (200) pole figures of the three cubic samples by both detection techniques are plotted in Fig. 5, with the neutron results truncated to the same 4th-order for direct comparisons with ultrasound
It is evident that both the overall distribution patterns and the intensities of the pole figures generally agree well between the acoustic and truncated neutron results, confirming experimentally the postulated convolution between the lowerorder texture coefficients and wave speeds. These agreements are remarkable considering the multiple factors that could have had negative influences on them, such as inaccurate SCECs and diffraction peak intensity calculations. These factors may have contributed to the facecentred cubic (FCC)-2 sample's slightly more pronounced differences, where the texture intensities are relatively weak in the first place
Summary
Crystallographic texture refers to the preferred orientation distribution of crystals in polycrystalline materials (e.g. metals, ceramics and minerals), which is normally developed during the thermo-mechanical deformation or recrystallisation processes [1,2]. Despite the fact that experimentally observed anisotropy of wave speeds have long been associated with texture [12], the inverse extraction of texture information from wave speeds has remained a difficult problem [13] that has not been satisfactorily solved Prior pursuits of this capacity have been mainly based on guided ultrasound [14e19] (not bulk waves) in rolled plates with assumed orthorhombic sample symmetry simplifications (enforcing a number of the complex ODF coefficients to be 0 e four out of nine in the case of cubic material e and the remaining ones to be real), and the numerical optimisation procedure to obtain the reduced orientation distribution coefficients involves five-dimensional least-square fittings of a number of guided wave dispersion curves, with each point on these curves having to be iteratively searched. We discuss the significance and possible implications of the general methodology before concluding
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