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Bony materials are biogenic composites of protein fibers and mineral that create hierarchical structures. In the case of teeth, dentin is the main component and similar to other bones, it contains porosity at multiple length scales. It is traversed by micron-sized hollow channels known as dentinal tubules, essential for temperature and pain sensation. Tubule density and thus porosity vary throughout the macroscopic three-dimensional (3D) structure, with porosity increasing toward the pulp. The different densities in teeth are easily revealed non-destructively in 3D by X-ray imaging using computer tomography (CT). Yet elemental composition analysis is more difficult to obtain from within the centimeter-sized heterogeneous bulk material. We describe an approach of merging CT measurements of healthy, intact bovine teeth with micro-X-ray fluorescence (micro-XRF) images of matching serially sectioned slices. Through the combination of multi-resolution quantitative CT measurements with elemental mass fraction derivation, gradients in density and element distributions such as calcium (Ca), phosphorus (P), and zinc (Zn) are revealed across entire teeth in 3D. While the main constituents (Ca and P) are homogeneously distributed in the matrix, Zn concentration increases significantly and exponentially toward the pulp. We find an inverse association between dentin tissue density and Zn concentration localizing this element in or around tubules. Our data serve as a quantitative reference for density and Zn mass fractions in healthy, neither carious nor hypermineralized dentin, as a basis for comparisons across species in health and disease states.
A critical amount of industrial energy input is lost as waste heat, and this amount peaks just above room temperature. The aim of this work is to develop a technology to convert this low-grade waste heat into electricity through a thermomagnetic generator based on Faraday's law of induction. To this end, water-flowable thermomagnetic elements are developed by the industrial partner to be used as heat exchanger components in the demonstrator. The 3D extrusion and post heat treatment process of the developed fine parts may introduce various defects that have an impact on their heat transfer efficiency, magnetic and mechanical properties.
Here, the non-destructive characterisation technique of X-ray computed tomography (XCT) is used to evaluate the morphology of the developed components and to identify trends that contribute to the improvement of material performance in the demonstrator. In specific, XCT image analysis enables the 3D visualisation of the developed 3D-printed structures. Using DragonFly software, scalar quantities such as volume, total surface area and void fraction are estimated for each sample. More specifically, image segmentation using Otsu’s thresholding method, combined with morphological operations on the reconstructed 3D XCT volume, contributes to the estimation of the mean filament diameter, mean channel width and distribution of internal porosity along the printing direction. In addition, the repeatability and dimensional accuracy of the printing process are evaluated through slice analysis of each 3D-printed block, both along and perpendicular to the water-flow direction.
Synchrotron X-ray computed tomography (SXCT) is regularly used in materials science to correlate structural properties with macroscopic properties and to optimize manufacturing processes. The X-ray beam energy must be adapted to the sample properties, such as size and density. If both strongly and weakly absorbing materials are present, the contrast to the weakly absorbing materials is lost, resulting in image artifacts and a poor signal-tonoise ratio (SNR). One particular example is a low-temperature co-fired ceramics (LTCC), in which metal connections are embedded in a ceramic matrix and form 3-dimensional conducting structures. This article describes a method of combining SXCT scans acquired at different beam energies, significantly reducing metal artifacts, and improving image quality. We show how to solve the difficult task of merging the scans at low and high beam energy. Our proposed merging approach achieves up to 35 % improvement in SNR within ceramic regions adjacent to metallic conductors. In this way, previously inaccessible regions within the ceramic structure close to the metallic conductors are made accessible. The paper further discusses methodological requirements, limitations, and potential extensions of the presented multi-energy SXCT merging technique.
Laser powder bed fusion (PBF-LB/M) is a metal additive manufacturing process. Due to the complex nature of the layer-wise, repeated heating and cooling cycles, it tends to generate high-magnitude residual stresses. If not correctly understood and mitigated through in- or post-process approaches, these residual stresses can be detrimental as they are often tensile at the surface. However, determining the magnitude and location of peak tensile residual stresses is not trivial as they are often located subsurface. This work focuses on determining the magnitude and location of these deleterious tensile residual stresses in a PBF-LB/316L specimen. Two diffraction-based Methods are used to reveal the relationship between the residual stresses and the underlying microstructure. On the one hand, high spatial resolution Neutron diffraction is used to determine triaxial stresses from the bulk to a depth of 0.15 mm. On the other hand, laboratory X-ray diffraction coupled with electrolytical layer removal allows the biaxial residual stress depth profile to be probed from the surface to a depth of about 0.6 mm. The results show a good agreement between the two methods. The peak residual stress is shown to be 500 MPa, which appears as a plateau between 0.08 and 0.35 mm in depth.
In the field of additive manufacturing, the ability to uniquely identify and authenticate parts is crucial for certification, logistics, and anti-counterfeiting efforts. This study introduces a novel methodology that leverages the intrinsic microstructural features of additively manufactured components for their identification, authentication, and traceability. Unlike traditional tagging methods, such as embedding QR codes on the surface [1] or within the volume of parts, this approach requires no alteration to the printing process, as it utilizes naturally occurring microstructural characteristics.
The proposed workflow [2] involves the analysis of 3D micro-computed tomography data to identify specific voids that meet predefined identification criteria. This method is demonstrated on a batch of 20 parts manufactured with identical process parameters, proving capable of achieving unambiguous identification and authentication. By establishing a tamper-proof link between the physical part and its digital counterpart, this methodology effectively bridges the physical and digital realms. This not only enhances the traceability of additively manufactured parts but also provides a robust tool for integrating digital materials, parts databases, and product passports with their physical counterparts.
The international research community is currently devoting extensive resources to the development of digital material data spaces and the associated digital twins and product passports of materials and components. A common weak link in these projects to date has been the connection between physical components / samples and their digital data and documents. This is where the concept of the unique identification comes in. Components produced using additive manufacturing can be marked for unique identification and secure authentication [1,2]. Serial numbers and machine-readable codes can be used to identify the component, and link digital product-related data (i.e., a digital product passport) to the actual components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface or the internal cavity of hollow components. However, local manipulation of components may alter the properties, and external tagging features can be altered or even removed by post-processing treatments.
This work provides a new methodology for identification, authentication, and traceability of additively manufactured (AM) components using microstructural features that are unique to each part. X-ray computed tomography (XCT) was employed to image the microstructural features of a batch of AlSi10Mg parts. Based on size and geometry, the most prominent features were selected to create a unique digital authenticator. We implemented a framework in Python using open-access modules that can successfully create a digital object authenticator using the segmented microstructure information from XCT. We show that this method allows to authenticate individual parts from the build job based on its microstructural fingerprint. This is our contribution to enhancing the security and product protection of additively manufactured components.
Components produced using additive manufacturing can be marked for unique identification and secure authentication [1,2]. Serial numbers and machine-readable codes can be used to identify the component, and link digital product-related data (i.e., a digital product passport) to the actual components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface of the internal cavity of hollow components. However, local manipulation of components may alter the properties, and external tagging features can be altered or even removed by post-processing treatments. This work therefore aims to provide a new methodology for identification, authentication, and traceability of additively manufactured (AM) components using microstructural features that are unique to each part. X-ray computed tomography (XCT) was employed to image the microstructural features of AlSi10Mg parts. Based on size and geometry, the most prominent features were selected to create a unique digital authenticator. We implemented a framework in Python using open-access modules that can successfully create a digital object authenticator using the segmented microstructure information from XCT. The authenticator is stored as a QR code, along with the 3D information of the selected features.
Dental crown restorations are the most common type of indirect restoration in Germany, with over 5 million crowns placed annually. Clinical complications such as debonding and crown fractures cannot yet be adequately correlated with cement ageing processes. The SimuCrown project systematically investigates the ageing mechanisms of the crown–cement–tooth complex (CCTC) while also validating the in vitro methodology itself. This interdisciplinary cooperation combines experimental ageing simulation (Charité), computer-aided finite element method based simulation (TU Berlin), and high-resolution structural analysis using synchrotron-based X-ray refraction radiography (SXRR) on BAMline at BESSY II (BAM).
In additive manufacturing, any change of the process parameters, such as scanning strategy, directly affects the cooling rates, heat accumulation, and overall thermal history of the build. Consequently, parts built with different process parameters tend to have different levels of crystallographic texture, residual stress, and dislocation density. These features can influence the properties of the material and their development during post-processing operations. In this study, IN718 prisms were built by laser powder bed fusion (PBF-LB/M) using two different scanning strategies (continuous 67° rotations around the build direction, ROT, and alternating 0°/67° scans, ALT) to provide two different as-built conditions. In situ time-resolved synchrotron diffraction was performed during a solution heat treatment at 1027 °C for 1 h. Ex situ scanning electron microscopy was used to support and complement the in situ observations. An approach to quantify the effect of elemental microsegregation at the cell walls is developed based on the deconvolution of asymmetric γ-nickel matrix peaks. Following this approach, the scanning strategies are shown to affect the as-built fraction of cell walls in the material, resulting in a difference of approximately 5 %, in weight fraction, between ROT and ALT (19 % vs. 24 %, respectively). This microsegregation was observed to be rapidly homogenized during the heating ramp, and no significant changes to the peak shape in the γ peaks occurred during the isothermal part of the heat treatment, regardless of the scanning strategy.
The actual environmental challenges require a huge effort from all industrial sectors to reduce their emissions of greenhouse gasses and pollutants. In this context, aeronautics is deeply concerned as one of the most emissive industrial sectors (cf. EU Green Deal). The answer to this pressing challenge is complex and involves new fuels and engine concepts, new aerostructures with higher weight-savings, as well as new, energy-efficient, and sustainable manufacturing technologies and materials. Two technologies may contribute particularly to achieving the goals: (i) new and more energy-efficient processes such as additive manufacturing (AM) can be used for part production; (ii) the engine efficiency of airplanes can be significantly improved to save fuel and reduce gas emissions. The latter can be achieved by increasing the engine thermal efficiency, i.e., increasing the turbine inlet temperature. Currently, only single-crystalline cast materials are available to be used for the thermally highest-loaded parts in the gas turbine engine, i.e., the turbine blades in the high-pressure turbine just behind the combustion chamber. These materials rely on a special casting technology, although they lose these original material performances when additive manufactured. In addition, current materials suitable for metal additive manufacturing have a limited range of temperature application. Therefore, the focus is on the development of new materials targeting higher in-service operation temperatures and durability. Recently, a new Ni-based superalloy (VDM 780) has been developed to ensure microstructural stability up to 800 °C. The goal of this work is to provide a deeper understanding of the high temperature fatigue properties of this alloy. This will enable the identification of the maximum operating temperature of this alloy and assess its performance in order to establish its potential in view of a new generation of more efficient aero-engines.