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The combination of microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on porous material properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of porosity in ceramics.
Moreover, I will show how not-so-novel 2D characterization techniques, based X-ray refraction, can allow a great deal of insights in the damage evolution in microcracked (and porous) ceramics. I will show how X-ray refraction can detect objects (e.g. microcracks) below its own spatial resolution.
Finally, I will discuss the link between the microstructural findings and the mechanical properties of porous microcracked ceramics.
The combination of microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on porous material properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of porosity in ceramics.
Moreover, I will show how not-so-novel 2D characterization techniques, based X-ray refraction, can allow a great deal of insights in the damage evolution in microcracked (and porous) ceramics. I will show how X-ray refraction can detect objects (e.g. microcracks) below its own spatial resolution.
Finally, I will discuss the link between the microstructural findings and the mechanical properties of porous microcracked ceramics.
Layer-by-layer additive manufacturing (AM) by means of laser-powder bed Fusion (L-PBF) offers many prospects regarding the design of lattice structures used, for example, in gas turbines. However, defects such as bulk porosity, Surface roughness, and re-entrant features are exacerbated in nonvertical structures, such as tilted struts. The characterization and quantification of these kinds of
defects are essential for the correct estimation of fracture and fatigue properties.
Herein, cylindrical struts fabricated by L-PBF are investigated by means of X-ray computed tomography (XCT), with the aim of casting light on the dependence of the three kinds of defects (bulk porosity, surface roughness, and re-entrant features) on the build angle. Innovative analysis methods are proposed to correlate shape and position of pores, to determine the angular-resolved Surface roughness, and to quantify the amount of re-entrant surface features, q. A meshing of the XCT surface enables the correlation of q with the classical Surface roughness Pa. This analysis leads to the conclusion that there is a linear correlation between q and Pa. However, it is conjectured that there must be a threshold of surface roughness, below which no re-entrant features can be build.
The quality of components made by laser beam melting (LBM) additive manufacturing is naturally influenced by the quality of the powder bed. A packing density <1 and porosity inside the powder particles lead to intrinsic voids in the powder bed. Since the packing density is determined by the particle size and shape distribution, the determination of these properties is of significant interest to assess the printing process. In this work, the size and shape distribution, the amount of the particle’s intrinsic porosity, as well as the packing density of micrometric powder used for LBM, have been investigated by means of synchrotron X-ray computed tomography (CT). Two different powder batches were investigated: Ti–6Al–4V produced by plasma atomization and stainless steel 316L produced by gas atomization. Plasma atomization particles were observed to be more spherical in terms of the mean anisotropy compared to particles produced by gas atomization. The two kinds of particles were comparable in size according to the equivalent diameter. The packing density was lower (i.e., the powder bed contained more voids in between particles) for the Ti–6Al–4V particles. The comparison of the tomographic results with laser diffraction, as another particle size measurement technique, proved to be in agreement.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
As opposed to reviewing results on experimental determination of residual stress by diffraction, this paper discusses the open issues when dealing with residual stress determination in additive manufactured parts, in particular those manufactured with laser powder bed fusion techniques. Three points are addressed in detail: (a) the proper determination of the strain-free reference d0, (b) the problem of the determination of the principal axes, and (c) the use of the correct diffraction elastic constants. It is shown that all methods to determine the strain-free reference d0 suffer from caveats, and care must be taken in evaluating the most suitable for the problem being tackled. In addition, it is shown that, in some systems, the principal axes do correspond to the geometrical axes of the specimen, but this needs to be systematically checked, especially in the case of uni- or bidirectional hatching strategies. Finally, the need to experimentally determine the proper diffraction elastic constants is underlined, especially in the case of strongly textured specimens, which again depends on the deposition strategy.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
A paradigm shift in the description of creep in metals can only occur through multi-scale imaging
(2022)
The description of creep in metals has reached a high level of complexity; fine details are revealed by all sorts of characterization techniques and different theoretical models. However, to date virtually no fully microstructure-driven quantitative description of the phenomenon is available. This has brought to interesting inconsistencies; the classic description of (secondary) creep rests on the so-called power law, which however: a- has a pre-factor spanning over 10 orders of magnitude; b- has different reported exponents for the same material; c- has no explanation for the values of such exponents.
Recently, a novel description (the so-called Solid State Transformation Creep (SSTC) Model) has been proposed to tackle the problem under a different light. The model has two remarkable features: 1- it describes creep as the accumulation of elementary strains due to dislocation motion; 2- it predicates that creep is proceeding by the evolution of a fractal arrangement of dislocations. Such description, however, needs a great deal of corroborating evidence, and indeed, is still incomplete.
To date, we have been able to observe and somehow quantify the fractal arrangement of microstructures through Transmission Electron Microscopy (TEM), observe the accumulation of dislocations at grain boundaries by EBSD-KAM (Electron Back-Scattered Diffraction-Kernel Angular Misorientation) analysis, quantify the kinetic character (solid state transformation) of experimental creep curves, and estimate the sub-grain size of the fractal microstructure through X-ray refraction techniques. All pieces of the mosaic seem to yield a consistent picture: we seem being on the right path to reconstruct the whole elephant by probing single parts of it. What is still missing is the bond between the various scales of investigation.
The hard X-ray beamline BAMline at BESSY II (Berlin, Germany) has now been in service for 20 years. Several improvements have been implemented in this time, and this review provides an overview of the imaging methods available at the BAMline. Besides classic full-field synchrotron X-ray computed tomography (SXCT), also absorption edge CT, synchrotron X-ray refraction radiography (SXRR), and synchrotron X-ray refraction tomography (SXRCT) are used for imaging. Moreover, virtually any of those techniques are currently coupled in situ or operando with ancillary equipment such as load rigs, furnaces, or potentiostats. Each of the available techniques is explained and both the current and the potential usage are described with corresponding examples. The potential use is manifold, the examples cover organic materials, composite materials, energy-related materials, biological samples, and materials related to additive manufacturing. The article includes published examples as well as some unpublished applications.
Additive manufacturing (AM) techniques have risen to prominence in many industrial sectors. This rapid success of AM is due to the freeform design, which offers enormous possibilities to the engineer, and to the reduction of waste material, which has both environmental and economic advantages. Even safety-critical parts are now being produced using AM. This enthusiastic penetration of AM in our daily life is not yet paralleled by a thorough characterization and understanding of the microstructure of materials and of the internal stresses of parts. The same holds for the understanding of the formation of defects during manufacturing. While simulation efforts are sprouting and some experimental techniques for on-line monitoring are available, still little is known about the propagation of defects throughout the life of a component (from powder to operando/service conditions). This Issue was aimed at collecting contributions about the advanced characterization of AM materials and components (especially at large-scale experimental facilities such as Synchrotron and Neutron sources), as well as efforts to liaise on-line process monitoring to the final product, and even to the component during operation. The goal was to give an overview of advances in the understanding of the impacts of microstructure and defects on component performance and life at several length scales of both defects and parts.
The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a five-phase MMC is performed by synchrotron X-ray computed tomography (SXCT). A workflow for advanced deep learning-based segmentation of all individual phases in SXCT data is shown using a fully convolutional neural network with U-net architecture. High segmentation accuracy is achieved with a small amount of training data. This enables extracting unprecedently precise microstructural parameters (e.g., volume fractions and particle shapes) to be input, e.g., in micromechanical models.
The additive manufacturing of low elastic modulus alloys that have a certain level of porosity for biomedical needs is a growing area of research. Here, we show the results of manufacturing of porous and dense samples by a laser powder bed fusion (LPBF) of Ti-Nb alloy, using two distinctive fusion strategies. The nanostructured Ti-Nb alloy powders were produced by mechanical alloying and have a nanostructured state with nanosized grains up to 90 nm. The manufactured porous samples have pronounced open porosity and advanced roughness, contrary to dense samples with a relatively smooth surface profile. The structure of both types of samples after LPBF is formed by uniaxial grains having micro- and nanosized features. The inner structure of the porous samples is comprised of an open interconnected system of pores. The volume fraction of isolated porosity is 2 vol. % and the total porosity is 20 vol. %. Cell viability was assessed in vitro for 3 and 7 days using the MG63 cell line. With longer culture periods, cells showed an increased cell density over the entire surface of a porous Ti-Nb sample. Both types of samples are not cytotoxic and could be used for further in vivo studies.
Having been introduced almost two decades ago, Additive Manufacturing (AM) of metals has become industrially viable for a large variety of applications, including aerospace, automotive and medicine. Powder bed techniques such as Selective Laser Melting (SLM) based on layer-by-layer deposition and laser melt enable numerous degrees of freedom for the geometrical design. Developing during the manufacturing process, residual stresses may limit the application of SLM parts by reducing the load bearing capacity as well as induce unwanted distortion depending on the boundary conditions specified in manufacturing.
The residual stress distribution in IN718 elongated prisms produced by SLM was studied non-destructively by means of neutron (bulk) and laboratory X-ray (surface) diffraction. The samples with different scanning strategies, i.e. hatching length, were measured in as-built condition (on a build plate) and after removal from the build plate.
While surface stress fields seem constant for AB condition, X-ray diffraction shows stress gradients along the hatch direction in the RE condition. The stress profiles correlate with the distortion maps obtained by tactile probe measurements.
Neutron diffraction shows bulk stress gradients for all principal components along the main sample directions. We correlate the observed stress patterns with the hatch length, i.e. with its effect on temperature gradients and heat flow. The bulk stress gradients partially disappear after removal from the baseplate.
Together with surface scan utilizing a coordinate-measuring machine (CMM), it is possible to link the stress release to the sample distortion.
We finally propose an explanation of those stress profiles based on the deposition strategy.
Additive Manufacturing (AM) of metals has become industrially viable for a large variety of applications, including aerospace, automotive and medicine. Powder bed techniques such as Selective Laser Melting (SLM) based on layer-by-layer deposition and laser melt enable numerous degrees of freedom for the geometrical design. Developing during the manufacturing process, residual stresses may limit the application of SLM parts by reducing the load bearing capacity as well as induce unwanted distortion depending on the boundary conditions specified in manufacturing.
The residual stress distribution in the bulk of IN718 elongated prisms produced by SLM was studied non-destructively by means of neutron diffraction. The samples with different scanning strategies, i.e. hatching length, were measured in as-build condition (on a build plate) and after removal from the build plate.
The absolute values of all stress components decreased after removal from the build plate. Together with surface scan utilizing a coordinate-measuring machine (CMM), it is possible to link the stress release to the sample distortion. Obtained results indicated different residual stress states for each of the transversal, longitudinal and normal component depending on the thermal gradient in the respective direction.
Ein Nachteil der klassischen Durchstrahlungstechnik mit Röntgenstrahlen ist die, in der Abbildung des Untersuchungsobjektes, fehlende Tiefeninformation. Die Anwendung von radiografischen Verfahren, die das Objekt unter zwei oder mehreren Winkelpositionen durchstrahlen, erlauben die Rekonstruktion räumlicher Abbildungen. Dazu zählen Stereoradiografie, Translations- und Rotationslaminographie. Bei der Computertomographie erfolgt die Durchstrahlung unter einem Winkelbereich von 180° oder 360°. Die dabei aufgenommenen Projektionen werden anschließend durch Anwendung der Fourier Transformation und der gefilterten Rückprojektion zu einem 3D-Bilddatensatz rekonstruiert. Verschiedene systembedingte Artefakte, die das Ergebnis negativ beeinflussen können, lassen sich durch geeignete Meß- und Rekonstruktionsparameter, sowie einer nachfolgende Bildverarbeitung eliminieren oder reduzieren.
In this talk the basics of X-ray computed tomography (XCT) are presented, together with a description of complementary techniques such as Laminography and Stereoradiography.
A overview of the common reconstruction approach and of the artifacts that can occur during reconstruction or acquisition of XCT images is also given.
Finally, application examples in the field of construction materials are given, whereby several experimental techniques (Region of Interest Approach) and data analysis methods (e.g. Digital volume correlation) are explained. Such techniques and algorithms are used to extract quantitative information from ex- and in-situ experiments.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda’s approach combined with the SD method.
The creep strengthening mechanisms in (age-hardenable) aluminum alloys are analyzed on the basis of a new microstructural study of powder samples, an analysis of a comprehensive revision of creep data from the literature, and a new modeling approach. A strategy based on the strength difference (SD) method to separate the contributions of solid solution atoms and precipitates to creep strengthening is proposed. The new methodology considers the combination of the two contributions avoiding the need of a threshold stress term in the creep equation. The contribution of both precipitates and solid solution is taken into account by means of the analysis of the lattice parameter variation with aging time. For this study, powders of two commercial AA2xxx alloys have been analyzed using diffraction methods. The experimental results are modeled using Lubarda's approach combined with the SD method.