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- X-ray refraction (2)
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- 3D imaging (1)
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- Anisotropy (1)
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- BAM SynthCOND (1)
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- Biomaterials (1)
- Calcium phosphate (1)
- Coating (1)
- Contour scan strategy (1)
- Convolutional Neural Network (DCNN) (1)
- Convolutional neural networks (1)
- Crack propagation (1)
- Deep Convolutional Neural Network (DCNN) (1)
- Deep convolutional neural network (DCNN) (1)
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- Denoising Deblurring Sharpening (1)
- Deviatoric (1)
- Diffraction elastic constants (1)
- Dimensional metrology (1)
- Elastic constants (1)
- Electron beam powder bed fusion (1)
- Functionally graded porous structure (1)
- Geometrical magnification (1)
- Grating interferometry (1)
- Helium (1)
- Hot isostatic pressing (1)
- Imaging (1)
- In situ alloying (1)
- In-situ neutron diffraction (1)
- Industrial CT (1)
- Intergranular strain (1)
- Intermetallics (1)
- Internal stress (1)
- Irradiation (1)
- Laser beam melting (1)
- Laser methods (1)
- Lattice structure (1)
- Lightweight structures (1)
- Load transfer (1)
- Macroscopic stress (1)
- Maskinteknik (1)
- Material science (1)
- Mechanical Engineering (1)
- Medical implants (1)
- Melt pool monitoring (1)
- Metal Matrix Composite (MMC) (1)
- Metal matrix composite (1)
- Metal matrix composite (MMC) (1)
- Metal matrix composites (MMC) (1)
- Metamaterials (1)
- Micromechanical modeling (1)
- Micromechanics (1)
- Modified U-Net architectures (1)
- Modified U-net architectures (1)
- Multi-phase (1)
- Multiple-layered scaffold (1)
- Nanostructured powder (1)
- Neutron diffraction (1)
- Piston alloy (1)
- Polycaprolactone (1)
- Powder analysis (1)
- Powder bed fusion Laser beam (1)
- Powder methods (1)
- Powder removal (1)
- Process atmosphere (1)
- Radiation shielding (1)
- Radiography (1)
- Refraction (1)
- Residual powder removal (1)
- Roughness analysis (1)
- Scaffold (1)
- Segmentations (1)
- Strengthening mechanisms (1)
- Stress concentration tensor (1)
- Surface roughness (1)
- Synchrotron Radiation (1)
- Synchrotron computed tomography (1)
- Synchrotron, BAMline (1)
- TPMS structures (1)
- Talbot-Lau interferometer (1)
- Texture (1)
- Ti6Al4V alloy (1)
- Tiatanium (1)
- Tomography (1)
- Triple UNet (1)
- Triply periodic minimal surface structures (1)
- Voxel size (1)
- X-ray caustics (1)
- X-ray diffraction (1)
- X-ray phase contrast (1)
- XCT (1)
- XCT Data Conditioning (1)
- Zirconium (1)
- i.S.Sy.Da.T.A. (1)
Organisationseinheit der BAM
The paper is motivated by some inconsistencies and contradictions present in the literature on the calculation of the so-called diffraction elastic constants. In an attempt at unifying the views that the two communities of Materials Science and Mechanics of Materials have on the subject, we revisit and define the terminology used in the field. We also clarify the limitations of the commonly used approaches and Show that a unified methodology is also applicable to textured materials with a nearly arbitrary grain shape. We finally compare the predictions based on this methodology with experimental data obtained by in situ synchrotron radiation diffraction on additively manufactured Ti-6Al4V alloy. We show that (a) the transverse isotropy of the material yields good agreement between the best-fit isotropy approximation (equivalent to the classic Kröner’s model) and the experimental data and (b) the use of a general framework allows the calculation of all components of the tensor of diffraction elastic constants, which are not easily measurable by diffraction methods. This allows us to extend the
current state-of-the-art with a predictive tool.
Explaining Deviatoric Residual Stresses in Aluminum Matrix Composites with Complex Microstructure
(2020)
The residual stresses in multiphase metal Matrix composites with both random planar-oriented short fibers and particles were studied by neutron diffraction and by a model based on the reformulation of classic Maxwell’s homogenization method. Contrary to common understanding and state-of-the-art models, we experimentally observed that randomly oriented phases possess non-hydrostatic residual stress. The recently developed modeling Approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses Accounting for the interaction of random oriented phases with fibers having preferential orientation.
Connecting Diffraction-Based Strain with Macroscopic Stresses in Laser Powder Bed Fused Ti-6Al-4V
(2020)
The laser powder bed fusion (LPBF) production process often results in large residual stress (RS) in the parts. Nondestructive techniques to determine RS are badly needed. However, a reliable quantification of macro-RS (i.e., stress at the component level) by means of diffraction-based techniques is still a great challenge, because the link between diffraction-based strain and macro-RS is not trivial. In this study, we experimentally determine (by means of in-situ synchrotron radiation diffraction) this link for LPBF Ti-6Al-4V. We compare our results with commonly used models to determine the so-called diffraction elastic constants (DECs). We show that LPBF materials possess different DECs than wrought alloys, simply because their microstructural and mechanical properties are different. We also show that the existing models can be used to calculate DECs only if high accuracy of the RS values is not required. If the peculiarities of the microstructure have to be taken into account (as is the case of additively manufactured materials), a radically new approach is desirable.
This study reports the results of the preliminary assessment to fabricate Ti-10at% Nb alloy by electron beam melting (EBM®) from a blend of elemental Nb and Ti powders. The microstructure of the EBM-manufactured Ti-10at% Nb alloys is sensitive to the following factors: different sintering properties of Nb and Ti powders, powder particle properties, material viscosities at varying melt pool temperatures, β-stabilizer element content and the EBM® process parameters. Three phases were observed in as-manufactured Ti-10at% Nb alloy: μm-size Nb phase, a Nb-rich β-solid solution surrounding Nb phase, lamellar structured α-phase and β-solid solution with different distribution and volume fraction. Thus, the combination of powder particle characteristics, very short time material spends in molten condition and sluggish kinetics of mixing and diffusional process in Ti-Nb alloy results in heterogeneous microstructures depending on the local Nb content in the powder blend and the EBM® process conditions.
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.
While there is a large body of literature on the micro-mechanical behavior of metal matrix composites (MMCs) under uniaxial applied stress, very little is available on multi-phase MMCs. In order to cast light on the reinforcement mechanisms and damage processes in such multi-phase composites, materials made by an Al-based piston alloy and containing one and two ceramic reinforcements (planar-random oriented alumina fibers and SiC particles) were studied. In-situ compression tests during neutron diffraction experiments were used to track the load transfer among phases, while X-ray computed tomography on pre-strained samples was used to monitor and quantify damage. We found that damage progresses differently in composites with different orientations of the fiber mat. Because of the presence of intermetallic network, it was observed that the second ceramic reinforcement changed the load transfer scenario only at very high applied load, when also intermetallic particles break. We rationalized the present results combining them with previous investigations and using a micromechanical model.
The performance of grating interferometers coming up now for Imaging interfaces within materials depends on the efficiency (visibility) of their main component, namely the phase grating. Therefore, experiments with monochromatic synchrotron radiation and corresponding simulations are carried out. The visibility of a Phase grating is optimized by different photon energies, varying detector to grating distances and continuous rotation of the phase grating about the grid lines. Such kind of rotation changes the projected grating shapes, and thereby the distribution profiles of phase shifts. This yields higher visibilities than derived from ideal rectangular shapes. By continuous grating rotation and variation of the propagation distance, we achieve 2D visibility maps. Such maps provide the visibility for a certain combination of grating orientation and detector position. Optimum visibilities occur at considerably smaller distances than in the standard setup.
In this paper we report on the characterization by X-ray computed tomography of calcium phosphate (CaP) and polycaprolactone (PCL) coatings on Ti-6Al-4V alloy scaffolds used as a material for medical implants. The cylindrical scaffold has greater porosity of the inner part than the external part, thus, mimicking trabecular and cortical bone, respectively. The prismatic scaffolds have uniform porosity. Surface of the scaffolds was modified with calcium phosphate (CaP) and polycaprolactone (PCL) by dip-coating to improve biocompatibility and mechanical properties. Computed tomography performed with X-ray and synchrotron radiation revealed the defects of structure and morphology of CaP and PCL coatings showing small platelet-like and spider-web-like structures, respectively.
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.
Load partitioning between phases in a cast AlSi12CuMgNi alloy was investigated by in-situ compression test during neutron diffraction experiments. Computed tomography (CT) was used to determine volume fractions of eutectic Si and intermetallic (IM) phases, and to assess internal damage after ex-situ compression tests. The CT reconstructed volumes showed the interconnectivity of IM phases, which build a 3D network together with eutectic Si. Large stresses were found in IMs, revealing their significant role as a reinforcement for the alloy. An existing micromechanical model based on Maxwell scheme was extended to the present case, assuming the alloy as a three-phase composite (Al matrix, eutectic Si, IM phases). The model agrees well with the experimental data.
Moreover, it allows predicting the principal stresses in each phase, while experiments can only determine stress differences between the axial and radial sample directions. Finally, we showed that the addition of alloying elements not only allowed developing a 3D interconnected network, but also improved the strength of the Al matrix, and the ability of the alloy constituents to bear mechanical load.
X-ray refraction related interaction has received rising interest since about two decades in the field of imaging, beam shaping and analysis although being discovered a century ago. Due to refraction at interfaces in inhomogeneous media X-rays undergo natural focusing (or defocusing) of waves, revealing caustics. Such Kind of intensity patterns are well-known for visible light, but have been sparsely discussed for X-rays. The Variation of irradiation density may be predicted in case of known shapes. Analogously to light optics, the intensity distributions cover several orders of magnitude including complete extinction. The partly convergent (and divergent) caustic stripes originate from narrow zones of typical size of some 10−6 of the boundary curvature radius. For the deflection of plane wave synchrotron radiation (energy in the range of some keV to some ten keV) at rods and tubes of several μm diameter, we find good Agreement between experiments and modeling by ray tracing according to Snell’s law without additional diffraction contributions. Apart from Basic Research implications, caustics may influence the performance of irradiation technologies such as sterilization or molecular cross-linking.
This study addressed a 7017 Al-alloy tailored for powder bed fusion – laser beam (PBF-LB) process. The alloy was prepared by mixing 3 wt% Zr and 0.5 wt% TiC powder to standard pre-alloyed 7017 grade aluminium powder. This made printing of the alloys possible avoiding solidification cracking in the bulk and achieving high relative density (99.8 %). Such advanced alloys have significantly higher Young’s modulus (>80 GPa) than conventional Al-alloys (70–75 GPa), thus making them attractive for applications requiring high stiffness. The resulting microstructure in as-printed condition was rich in particles originating from admixed powders and primary precipitates/inclusions originating from the PBF-LB process. After performing a T6-like heat treatment designed for the PBF-LB process, the microstructure changed: Zr-nanoparticles and Fe- or Mg/Zn- containing precipitates formed thus providing 75 % increase in yield strength (from 254 MPa to 444 MPa) at the cost of decreasing ductility (∼20 % to ∼9 %). In-situ tensile testing combined with SXCT, and ex-situ tensile testing combined with fracture analysis confirmed that the fracture initiation in both conditions is highly dependent on defects originated during printing. However, cracks are deflected from decohesion around Zr-containing inclusions/precipitates embedded in the Al-matrix. This deflection is seen to improve the ductility of the material.
In the present study, in-situ observation of Hot Isostatic Pressure (HIP) procedure of laser powder bed fusion manufactured Ti-6Al-4V parts was performed to quantitatively estimate the densifcation rate of the material and the infuence of the defect initial size and shape on such rate. The observations were performed in-situ using the Ultrafast Tomography Paris-Edinburgh Cell and the combination of fast phase-contrast synchrotron X-ray tomography and energy dispersive difraction. With this strategy, we could quantify how the efectiveness of HIP depends on the characteristics of a defect. Smaller defects showed a higher densifcation rate, while the defect shape did not have signifcant efect on such rate.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
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.
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.
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.