5 Werkstofftechnik
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Paper des Monats
- ja (11)
For the precise determination of orientations in polycrystalline materials, electron backscatter diffraction (EBSD) requires a consistent calibration of the diffraction geometry in the scanning electron microscope (SEM). In the present paper, the variation of the projection center for the Kikuchi diffraction patterns which are measured by EBSD is calibrated using a projective transformation model for the SEM beam scan positions on the sample. Based on a full pattern matching approach between simulated and experimental Kikuchi patterns, individual projection center estimates are determined on a subgrid of the EBSD map, from which least-square fits to affine and projective transformations can be obtained. Reference measurements on single-crystalline silicon are used to quantify the orientation errors which result from different calibration models for the variation of the projection center.
We discuss a refined simulation approach which treats Kikuchi diffraction patterns in electron backscatter diffraction (EBSD) and transmission Kikuchi diffraction (TKD). The model considers the result of two combined mechanisms: (a) the dynamical diffraction of electrons emitted coherently from point sources in a crystal and (b) diffraction effects on incoherent diffuse intensity distributions. Using suitable parameter settings, the refined simulation model allows to reproduce various thickness- and energy-dependent features which are observed in experimental Kikuchi diffraction patterns. Excess-deficiency features are treated by the effect of gradients in the incoherent background intensity. Based on the analytical two-beam approximation to dynamical electron diffraction, a phenomenological model of excess-deficiency features is derived, which can be used for pattern matching applications. The model allows to approximate the effect of the incident beam geometry as a correction signal for template patterns which can be reprojected from pre-calculated reference data. As an application, we find that the accuracy of fitted projection centre coordinates in EBSD and TKDcan be affected by changes in the order of 10−3–10-2 if excess-deficiency features are not considered in the theoreticalmodel underlying a best-fit pattern matching approach. Correspondingly, the absolute accuracy of simulation-based EBSD strain determination can suffer frombiases of a similar order of magnitude if excess-deficiency effects are neglected in the simulation model.
We discuss a refined simulation approach which treats Kikuchi diffraction patterns in electron backscatter diffraction (EBSD) and transmission Kikuchi diffraction (TKD). The model considers the result of two combined mechanisms: (a) the dynamical diffraction of electrons emitted coherently from point sources in a crystal and (b) diffraction effects on incoherent diffuse intensity distributions. Using suitable parameter settings, the refined simulation model allows to reproduce various thickness- and energy-dependent features which are observed in experimental Kikuchi diffraction patterns. Excess-deficiency features are treated by the effect of gradients in the incoherent background intensity. Based on the analytical two-beam approximation to dynamical electron diffraction, a phenomenological model of excess-deficiency features is derived, which can be used for pattern matching applications. The model allows to approximate the effect of the incident beam geometry as a correction signal for template patterns which can be reprojected from pre-calculated reference data. As an application, we find that the accuracy of fitted projection centre coordinates in EBSD and TKDcan be affected by changes in the order of 10−3–10−2 if excess-deficiency
features are not considered in the theoreticalmodel underlying a best-fit pattern matching approach. Correspondingly, the absolute accuracy of simulation-based EBSD strain determination can suffer frombiases of a similar order of magnitude if excess-deficiency effects are neglected in the simulation model.
A glass of the composition 37BaO·16CaO·47SiO2 wt% produced on an industrial scale is crystallized at 970 °C for times ranging from 15 min to 2 h. The crystallization at the immediate surface as well as the crystal growth into the bulk are analyzed using scanning electron microscopy (SEM) including energy dispersive X-ray spectroscopy (EDXS) and electron backscatter diffraction (EBSD) as well as X-ray diffraction in the Θ–2Θ setup (XRD). The immediate surface shows the oriented nucleation of walstromite as well as the formation of wollastonite and an unknown phase of the composition BaCaSi3O8. All three phases also grow into the bulk where walstromite ultimately dominates the kinetic selection and grows throughout the bulk due to a lack of bulk nucleation. Walstromite shows systematic orientation changes as well as twinning during growth. A critical analysis of the XRD-patterns acquired from various crystallized samples indicates that their evaluation is problematic and that phases detected by XRD in this system should be verified by another method such as EDXS.
Technically relevant P92 steel (9% Cr) was coated with a micron-thick porous alumina layer prepared by sol-gel technique and treated with flue gas (60 CO2-30 H2O-2 O2-1 SO2-7 N2 (mole fraction in %)) at 650 ° to mimic an oxyfuelcombustion process. Local defects in the coating were marked using focused ion beam (FIB) technique and were inspected after exposition to hot flue gas atmosphere at 300, 800, and 1300 h, respectively. Local defects like agglomerated alumina sol particles tend to spall off from the coating uncovering the underlying dense chromia scale. Re-coating was found to restore the protection ability from oxidation when repeatedly treated with hot flue gas. Cracks and voids did not promote the local oxidation due to the formation of crystalline Mn/S/O species within and on top of the coating. The protective character of the steel-coating system is a result of (i) the fast formation of a dense chromia scale at the surface of sol-gel alumina-coated P92 steel bars in combination with (ii) the porous alumina coating acting as diffusion barrier, but also as diffusion partner in addition with (iii) fast Mn outward diffusion capturing the S species from flue gas.
In this paper, columnar cellular growth with kinetic effects including kinetic undercooling and solute trapping in rapid directional solidification of alloys was investigated by using a recent quantitative phase-field model for rapid solidification. Morphological transition and primary spacing selection with and without kinetic effects were numerically investigated. Numerical results show that doublon structure is an intermediate state in the primary spacing adjustment of cellular arrays. It was found that the inclusions of kinetic effects result in the increase of the solute in the solid phase and the solute enrichment in the interdendritic liquid channel. Moreover, predicted results indicate that the growth directions of the cellular arrays in rapid directional solidification with and without kinetic effects are independent of the Péclet number. Therefore, the kinetic effects play important roles in numerical simulations of the growth pattern selection and solute distribution during rapid solidification. Neglecting them will result in the inaccurately predicted results.
Bioactive glass ceramics have excellent biocompatibility and osteoconductivity; and can form direct chemical bonds with human bones; thus, these ceramic are considered as “Smart” materials. In this study, we develop a new type of bioactive glass ceramic (AP40mod) as a scaffold containing Endothelial progenitor cells (EPCs) and Mesenchymal stem cells (BMSCs) to repair critical-sized bone defects in rabbit mandibles. For in vitro experiments:
AP40mod was prepared by Dgital light processing (DLP) system and the optimal ratio of EPCs/BMSCs was screened by analyzing cell proliferation and ALP activity, as well as the influence of genes related to osteogenesis and angiogenesis by direct inoculation into scaffolds. The scaffold showed suitable mechanical properties, with a Bending strength 52.7 MPa and a good biological activity. Additionally, when EPCs/BMSCs ratio were combined at a ratio of 2:1 with AP40mod, the ALP activity, osteogenesis and angiogenesis were significantly increased. For in vivo experiments: application of AP40mod/EPCs/BMSCs (after 7 days of in vitro spin culture) to repair and reconstruct critical-sized mandible defect in rabbit showed that all scaffolds were successfully accurately implanted into the defect area. As revealed by macroscopically and CT at the end of 9 months, defects in the AP40mod/EPCs/BMSCs group were nearly completely covered by normal bone and the degradation rate was 29.9% compared to 20.1% in the AP40mod group by the 3D reconstruction. As revealed by HE and Masson staining analyses, newly formed blood vessels, bone marrow and collagen maturity were significantly increased in the AP40mod/EPCs/BMSCs group compared to those in the AP40mod group. We directly inoculated cells on the novel material to screen for the best inoculation ratio. It is concluded that the AP40mod combination of EPCs/BMSCs is a promising approach for repairing and reconstructing large load bearing bone defect.
Trace elements play an important role in the fine-tuning of complex material properties. This study focuses on the correlation of microstructure, lattice misfit and creep properties. The compositionally complex alloy Al10Co25Cr8Fe15Ni36Ti6 (in at. %) was tuned with high melting trace elements Hf and W. The microstructure consists of a γ matrix, γ' precipitates and the Heusler phase and it is accompanied by good mechanical properties for high temperature applications. The addition of 0.5 at.% Hf to the Al10Co25Cr8Fe15Ni36Ti6 alloy resulted in more sharp-edged cubic γ′ precipitates and an increase in the Heusler phase amount. The addition of 1 at.% W led to more rounded γ′ precipitates and the dissolution of the Heusler phase. The shapes of the γ' precipitates of the alloys Al9.25Co25Cr8Fe15Ni36Ti6Hf0.25W0.5 and Al9.25Co25Cr8Fe15Ni36Ti6Hf0.5W0.25, that are the alloys of interest in this paper, create a transition from the well-rounded precipitates in the alloy with 1% W containing alloy to the sharp angular particles in the alloy with 0.5% Hf. While the lattice misfit has a direct correlation to the γ' precipitates shape, the creep rate is also related to the amount of the Heusler phase. The lattice misfit increases with decreasing corner radius of the γ' precipitates. So does the creep rate, but it also increases with the amount of Heusler phase. The microstructures were investigated by SEM and TEM, the lattice misfit was calculated from the lattice parameters obtained by synchrotron radiation measurements.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
Understanding the mechanical behavior of silicon nanowires is essential for the implementation of advanced nanoscale devices. Although bending tests are predominantly used for this purpose, their findings should be properly interpreted through modeling. Various modeling approaches tend to ignore parts of the effective parameter set involved in the rather complex bending response. This oversimplification is the main reason behind the spread of the modulus of elasticity and strength data in the literature. Addressing this challenge, a surface-based nanomechanical model is introduced in this study. The proposed model considers two important factors that have so far remained neglected despite their significance: (i) intrinsic stresses composed of the initial residual stress and surface-induced residual stress and (ii) anisotropic implementation of surface stress and elasticity. The modeling study is consolidated with molecular dynamics-based study of the native oxide surface through reactive force fields and a series of nanoscale characterization work through in situ threepoint bending test and Raman spectroscopy. The treatment of the test data through a series of models with increasing complexity demonstrates a spread of 85 GPa for the modulus of elasticity and points to the origins of ambiguity regarding silicon nanowire properties, which are some of the most commonly employed nanoscale building blocks. A similar conclusion is reached for strength with variations of up to 3 GPa estimated by the aforementioned nanomechanical models. Precise consideration of the nanowire surface state is thus critical to comprehending the mechanical behavior of silicon nanowires accurately. Overall, this study highlights the need for a multiscale theoretical framework to fully understand the size-dependent mechanical behavior of silicon nanowires, with fortifying effects on the design and reliability assessment of future nanoelectromechanical systems.
Spherical mesoporous bioactive glasses in the silicon dioxide (SiO2)-phosphorus pentoxide (P2O5)–calcium oxide (CaO) system with a high specific surface area of up to 300m2/g and a medium pore radius of 4 nm were synthesized by using a simple one-pot surfactant-assisted sol–gel synthesis method followed by calcination at 500–700°C. The authors were able to control the particle properties by varying synthesis parameters to achieve microscale powders with spherical morphology and a particle size of around 5–10 mm by employing one structure-directing agent. Due to a high Calcium oxide content of 33·6mol% and a phosphorus pentoxide content of 4·0mol%, the powder showed very good bioactivity up to 7 d of immersion in simulated Body fluid. The resulting microspheres are promising materials for a variety of life science applications, as further processing – for example, granulation – is unnecessary. Microspheres can be applied as materials for powder-based additive manufacturing or in stable suspensions for drug release, in bone cements or fillers.
This third part of the review on defects as root cause of fatigue failure addresses cavities (pores, micro-shrinkages, unmelted regions), defective microstructures and microcracks as material defects and defects due to local damage during manufacturing, service and maintenance such as dents, scratches and localized corrosion. In addition, damage due to contact fatigue and the effect of surface roughness are discussed in the context of fatigue failure. Also addressed is the competition between different kinds of defects in controlling the initiation and early growth of fatigue cracks.
According to the definition of the ASM handbook [1,3], a defect is "an imperfection. that can be shown to cause failure by a quantitative analysis and that would not have occurred in the absence of the imperfection". The topic of the present three-part review is a discussion of defects which can cause failure in cyclically loaded structures. The features discussed comprise material defects such as non-metallic inclusions, pores or micro-shrinkages, etc. and geometric defects such as surface roughness and secondary notches which have their origin in manufacturing, and defects such as surface damage due to scratches, impact events or contact fatigue as well as corrosion pits which arise in service. In this first part, the discussion is prefaced by an introduction to basic aspects which are essential for a deeper understanding of the characteristics and mechanisms how the defects influence fatigue crack initiation and propagation. These include the life cycle of a fatigue crack from initiation up to fracture, crack arrest, multiple crack initiation and coalescence, and the material and geometrical properties affecting these.
Defects as a root cause of fatigue failure of metallic components. II: Non-metallic inclusions
(2019)
This second part of the review on defects as root cause of fatigue failure comprises the origin, the nature and the effects of non-metallic inclusions. Topics addressed are the different kinds of inclusions formed during the manufacturing process, various types of mis-match causing local stresses and, as a consequence, fatigue crack initiation, and effects of characteristics such as size, morphology, localization, spatial distribution and orientation of the defects on the fatigue behavior. Methods for inclusion counting and sizing are discussed along with statistical aspects necessary to be considered when evaluating structural components.
Effects of various geometrical and physical factors, as well as the method of data reduction (analysis of
experimental forceedisplacement curves) on the values of local interfacial strength parameters (local IFSS, td, and critical energy release rate, Gic) determined by means of a single fiber pull-out test are discussed. Experimental results of our pull-out tests on several fiberepolymer matrix systems showed that td and Gic weakly depended on geometrical factors. However, the pull-out test appeared to be sensitive to the conditions of specimen formation and testing, such as changing the nature of the contacting surfaces (fiber sizing) and the fiber pull-out rate. Of several methods of td and Gic Determination from a forceedisplacement curve, the most reliable and reproducible one is the approach based on the values of the maximum force recorded in a pull-out test and the interfacial frictional force immediately after fiber debonding.
Upconverting nanoparticles are essential in modern photonics due to their ability to convert infrared light to visible light. Despite their significance, they exhibit limited brightness, a key drawback that can be addressed by combining them with plasmonic nanoparticles. Plasmon-enhanced upconversion has been widely demonstrated in dry environments, where upconverting nanoparticles are immobilized, but constitutes a challenge in liquid media where Brownian motion competes against immobilization.
This study employs optical tweezers for the three-dimensional manipulation of an individual upconverting nanoparticle, enabling the exploration of plasmon-enhanced upconversion luminescence in water. Contrary to expectation, experiments reveal a long-range (micrometer scale) and moderate (20%) enhancement in upconversion luminescence due to the plasmonic resonances of gold nanostructures. Comparison between experiments and numerical simulations evidences the key role of Brownian motion. It is demonstrated how the three-dimensional Brownian fluctuations of the upconverting nanoparticle lead to an “average effect” that explains the magnitude and spatial extension of luminescence enhancement.
For more than half a century, spinodal decomposition has been a key phenomenon in considering the formation of secondary phases in alloys. The most prominent aspect of the spinodal phenomenon is the lack of an energy barrier on its transformation pathway, offering an alternative to the nucleation and growth mechanism. The classical description of spinodal decomposition often neglects the influence of defects, such as grain boundaries, on the transformation because the innate ability for like-atoms to cluster is assumed to lead the process. Nevertheless, in nanocrystalline alloys, with a high population of grain boundaries with diverse characters, the structurally heterogeneous landscape can greatly influence the chemical decomposition behavior. Combining atom-probe tomography, precession electron diffraction and density-based phase-field simulations, we address how grain boundaries contribute to the temporal evolution of chemical decomposition within the miscibility gap of a Pt-Au nanocrystalline system. We found that grain boundaries can actually have their own miscibility gaps profoundly altering the spinodal decomposition in nanocrystalline alloys. A complex realm of multiple interfacial states, ranging from competitive grain boundary segregation to barrier-free low-dimensional interfacial decomposition, occurs with a dependency upon the grain boundary character.
Grain boundaries (GBs) are planar lattice defects that govern the properties of many types of polycrystalline materials. Hence, their structures have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the atomic length scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability to quantify chemical characteristics at near-atomic scale. Using APT data sets, we present here a machine-learning-based approach for the automated quantification of chemical features of GBs. We trained a convolutional neural network (CNN) using twenty thousand synthesized images of grain interiors, GBs, or triple junctions. Such a trained CNN automatically detects the locations of GBs from APT data. Those GBs are then subjected to compositional mapping and analysis, including revealing their in-plane chemical decoration patterns. We applied this approach to experimentally obtained APT data sets pertaining to three case studies, namely, Ni-P, Pt-Au, and Al-Zn-Mg-Cu alloys. In the first case, we extracted GB specific segregation features as a function of misorientation and coincidence site lattice character. Secondly, we revealed interfacial excesses and in-plane chemical features that could not have been found by standard compositional analyses. Lastly, we tracked the temporal evolution of chemical decoration from early-stage solute GB segregation in the dilute limit to interfacial phase separation, characterized by the evolution of complex composition patterns. This machine-learning-based approach provides quantitative, unbiased, and automated access to GB chemical analyses, serving as an enabling tool for new discoveries related to interface thermodynamics, kinetics, and the associated chemistry-structure-property relations.
Aero-engine turbine disks are safety-relevant components which are operated under high thermal and mechanical stress conditions. The actual part qualification and certification procedures make use of spin-tests conducted on production-similar disks. While these tests provide, on the one hand, a reliable definition of the critical conditions for real components, on the other hand they represent a relevant cost item for engine manufacturers. The aim of this work is to present two alternative burst speed assessment methods under development based on the Failure Assessment Diagram (FAD) and a global stability criterion, respectively. In the scope of the fracture mechanics assessment, the failure modes hoop-burst and rim-peeling are investigated with semicircular surface cracks modelled at the critical regions on the turbine disk. The comparison of the predicted critical rotational speed shows good agreement between the assessment methods.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.