Validation of three-dimensional diffraction contrast tomography reconstructions by means of electron backscatter diffraction characterization

Deep learning for improving non-destructive grain mapping in 3D

Laboratory X-ray diffraction contrast tomography (LabDCT) is a novel imaging technique for non-destructive 3D characterization of grain structures. An accurate grain reconstruction critically relies on precise segmentation of diffraction spots in the LabDCT images. The conventional method utilizing various filters generally satisfies segmentation of sharp spots in the images, thereby serving as a standard routine, but it also very often leads to over or under segmentation of spots, especially those with low signal-to-noise ratios and/or small sizes. The standard routine also requires a fine tuning of the filtering parameters. To overcome these challenges, a deep learning neural network is presented to efficiently and accurately clean the background noise, thereby easing the spot segmentation. The deep learning network is first trained with input images, synthesized using a forward simulation model for LabDCT in combination with a generic approach to extract features of experimental backgrounds. Then, the network is applied to remove the background noise from experimental images measured under different geometrical conditions for different samples. Comparisons of both processed images and grain reconstructions show that the deep learning method outperforms the standard routine, demonstrating significantly better grain mapping.

Improved grain mapping by laboratory X-ray diffraction contrast tomography

Laboratory diffraction contrast tomography (LabDCT) is a novel technique for non-destructive imaging of the grain structure within polycrystalline samples. To further broaden the use of this technique to a wider range of materials, both the spatial resolution and detection limit achieved in the commonly used Laue focusing geometry have to be improved. In this work, the possibility of improving both grain indexing and shape reconstruction was investigated by increasing the sample-to-detector distance to facilitate geometrical magnification of diffraction spots in the LabDCT projections. LabDCT grain reconstructions of a fully recrystallized iron sample, obtained in the conventional Laue focusing geometry and in a magnified geometry, are compared to one characterized by synchrotron X-ray diffraction contrast tomography, with the latter serving as the ground truth. It is shown that grain indexing can be significantly improved in the magnified geometry. It is also found that the magnified geometry improves the spatial resolution and the accuracy of the reconstructed grain shapes. The improvement is shown to be more evident for grains smaller than 40 µm than for larger grains. The underlying reasons are clarified by comparing spot features for different LabDCT datasets using a forward simulation tool.

Cyclic Deformation Induced Residual Stress Evolution and 3D Short Fatigue Crack Growth Investigated by Advanced Synchrotron Tomography Techniques

Diffraction and phase contrast tomography techniques were successfully applied to an austenitic–ferritic duplex stainless steel representing exemplarily a metallic material containing two phases with different crystal structures. The reconstructed volumes of both phases were discretized by finite elements. A crystal plasticity finite-element analysis was executed in order to simulate the development of the experimentally determined first and second order residual stresses, which built up due to the manufacturing process of the material. Cyclic deformation simulations showed the single-grain-resolved evolution of initial residual stresses in both phases and were found to be in good agreement with the experimental results. Solely in ferritic grains, residual stresses built up due to cyclic deformation, which promoted crack nucleation in this phase. Furthermore, phase contrast tomography was applied in order to analyze the mechanisms of fatigue crack nucleation and short fatigue crack propagation three-dimensionally and nondestructively. The results clearly showed the significance of microstructural barriers for short fatigue crack growth at the surface, as well as into the material. The investigation presented aims for a better understanding of the three-dimensional mechanisms governing short fatigue crack propagation and, in particular, the effect of residual stresses on these mechanisms. The final goal was to generate tailored microstructures for improved fatigue resistance and enhanced fatigue life.

Nondestructive evaluation of 3D microstructure evolution in strontium titanate

Nondestructive X-ray diffraction contrast tomography imaging was used to characterize the microstructure evolution in a polycrystalline bulk strontium titanate specimen. Simultaneous acquisition of diffraction and absorption information allows for the reconstruction of shape and orientation of more than 800 grains in the specimen as well as porosity. Three-dimensional microstructure reconstructions of two coarsening states of the same specimen are presented alongside a detailed exploration of the crystallographic, topological and morphological characteristics of the evolving microstructure. The overall analysis of the 3D structure shows a clear signature of the grain boundary anisotropy, which can be correlated to surface energy anisotropy: the grain boundary plane distribution function shows an excess of 〈100〉-oriented interfaces with respect to a random structure. The results are discussed in the context of interface property anisotropy effects.

Comparison between diffraction contrast tomography and high-energy diffraction microscopy on a slightly deformed aluminium alloy

The grain structure of an Al-0.3 wt%Mn alloy deformed to 1% strain was reconstructed using diffraction contrast tomography (DCT) and high-energy diffraction microscopy (HEDM). 14 equally spaced HEDM layers were acquired and their exact location within the DCT volume was determined using a generic algorithm minimizing a function of the local disorientations between the two data sets. The microstructures were then compared in terms of the mean crystal orientations and shapes of the grains. The comparison shows that DCT can detect subgrain boundaries with disorientations as low as 1° and that HEDM and DCT grain boundaries are on average 4 µm apart from each other. The results are important for studies targeting the determination of grain volume. For the case of a polycrystal with an average grain size of about 100 µm, a relative deviation of about ≤10% was found between the two techniques.

Characteristics of Friedel pairs and diffraction contrast tomography with non-perpendicular rotation axis

The characteristics of Friedel pairs in diffraction contrast tomography (DCT) are studied in the condition that the rotation axis of the sample is not exactly perpendicular to the incident X-ray direction. For the rotation axis approximately aligned along the vertical direction, the Friedel pairs close to the horizontal plane are insensitive to the non-perpendicularity of the rotation axis, and can be used to refine the sample-to-detector distance and X-ray energy, while the Friedel pairs close to the vertical direction are sensitive to the non-perpendicularity of the rotation axis, and can be used to determine the rotation axis orientation. The correct matching proportion of Friedel pairs decreases with increasing non-perpendicularity of the rotation axis. A method of data processing considering rotation axis misalignment is proposed, which significantly increases the correct matching and indexing proportions of the diffraction spots. A pure aluminium polycrystalline sample is investigated using DCT at beamline 4W1A of Beijing Synchrotron Radiation Facility. Based on the analysis of Friedel pairs, the sample-to-detector distance and X-ray energy are refined to be 8.67 mm and 20.04 keV, respectively. The non-perpendicular angle of the rotation axis is calculated to be 0.10°. With these refined geometric parameters, the matching proportion of the spatial position of diffraction spots is 90.62%. Three-dimensional reconstruction of the sample with 13 grains is realised using the algebraic reconstruction technique. It is demonstrated that the precise correction of the orientation of the sample rotation axis is effective in DCT suffering from rotation axis misalignment, and the higher accuracy in determining the rotation axis is expected to improve the reconstruction precision of grains.

Quantitative voxel-to-voxel comparison of TriBeam and DCT strontium titanate three-dimensional data sets

Recently, techniques for the acquisition of three-dimensional tomographic and four-dimensional time-resolved data sets have emerged, allowing for the analysis of mm3volumes of material with nm-scale resolution. The ability to merge multi-modal data sets acquiredviamultiple techniques for the quantitative analysis of structure, chemistry and phase information is still a significant challenge. Large three-dimensional data sets have been acquired by time-resolved diffraction contrast tomography (DCT) and a new TriBeam tomography technique with high spatial resolution to address grain growth in strontium titanate. A methodology for combining three-dimensional tomographic data has been developed. Algorithms for the alignment of orientation reference frames, unification of sampling grids and automated grain matching have been integrated, and the resulting merged data set permits the simultaneous analysis of all tomographic data on a voxel-by-voxel and grain-by-grain basis. Quantitative analysis of merged data sets collected using DCT and TriBeam tomography shows that the spatial resolution of the DCT technique is limited near grain boundaries and the sample edge, resolving grains down to 10 µm diameter for the reconstruction method used. While the TriBeam technique allows for higher-resolution analysis of boundary plane location, it is a destructive tomography approach and can only be employed at the conclusion of a four-dimensional experiment.

Cold neutron diffraction contrast tomography of polycrystalline material

Traditional neutron imaging is based on the attenuation of a neutron beam through scattering and absorption upon traversing a sample of interest. It offers insight into the sample's material distribution at high spatial resolution in a non-destructive way. In this work, it is expanded to include the diffracted neutrons that were ignored so far and obtain a crystallographic distribution (grain mapping). Samples are rotated in a cold neutron beam of limited wavelength band. Projections of the crystallites formed by the neutrons they diffract are captured on a two dimensional imaging detector. Their positions on the detector reveal their orientation whereas the projections themselves are used to reconstruct the shape of the grains. Indebted to established synchrotron diffraction contrast tomography, this 'cold neutron diffraction contrast tomography' is performed on recrystallized aluminium for experimental comparison between both. Differences between set-up and method are discussed, followed by the application range in terms of sample properties (crystallite size and number, mosaicity and typical materials). Neutron diffraction contrast tomography allows to study large grains in bulky metallic structures.

Comparison between a near-field and a far-field indexing approach for characterization of a polycrystalline sample volume containing more than 1500 grains

A comparison of the performance of X-ray diffraction tomography, a near-field diffraction technique, and a far-field diffraction technique for indexing X-ray diffraction data of polycrystalline materials has been carried out by acquiring two sets of diffraction data from the same polycrystalline sample volume. Both approaches used in this study are variants of the three-dimensional X-ray diffraction (3DXRD) methodology, but they rely on different data-collection and analysis strategies. Previous attempts to assess the quality of 3DXRD indexing results from polycrystalline materials have been restricted to comparisons with two-dimensional electron backscatter diffraction cross sections containing a limited number of grains. In the current work, the relative performance of two frequently used polycrystalline-material indexing algorithms is assessed, comparing the indexing results obtained from a three-dimensional sample volume containing more than 1500 grains. The currently achievable accuracy of three-dimensional grain maps produced with these algorithms has been assessed using a statistical analysis of the measurement of the size, position and orientation of the grains in the sample. The material used for this comparison was a polycrystalline commercially pure titanium grade 2 sample, which has a hexagonal close-packed crystal structure. The comparison of the two techniques shows good agreement for the measurements of the grain position, size and orientation. Cross-validation between the indexing results shows that about 99% of the sample volume has been indexed correctly by either of these indexing approaches. The remaining discrepancies have been analysed and the strengths and limitations of both approaches are discussed.