TY - CONF A1 - Kuchenbecker, Petra A1 - Hodoroaba, Vasile-Dan A1 - Lindemann, Franziska A1 - Wohlleben, W. T1 - Advanced screening method using volume-specific surface area (VSSA) for nanomaterial identification of powders N2 - The EC’s recommendation for a definition of nanomaterial (2011/696/EU) should allow the identification of a particulate nanomaterial based on the number-based metric criterion according to which at least 50% of the constituent particles have the smallest dimension between 1 and 100 nm. However, it has been recently demonstrated that the implementation of this definition for regulatory purposes is conditioned by the large deviations between the results obtained by different sizing methods or due to practical reasons such as high costs and time-consuming (SEM, TEM). Within the European project NanoDefine (www.nanodefine.eu) a two-tier approach has been developed, whereby firstly a screening method is applied for the rough classification as a nano-/non-nanomaterial, and for borderline cases a confirmatory method (imaging methods or field flow fractionation) must be considered. One of the measurement methods well suited to particulate powder is the determination of volume-specific surface area (VSSA) by means of gas adsorption as well as skeletal density. The value of 60 m2/cm3 corresponding to spherical, monodisperse particles with a diameter of 100 nm constitutes the threshold for decisioning if the material is a nano- or non-nanomaterial. The correct identification of a nanomaterial by VSSA method is accepted by the EU recommendation. However, the application of the VSSA method is associated also by some limitations. The threshold of 60 m2/cm3 is dependent on the particle shape, so that it changes considerably with the number of nano-dimensions of the particles. For particles containing micro-pores or having a microporous coating false positive results will be produced. Furthermore, broad particle size distributions make necessary to adjust the threshold. Based on examples of commercially available ceramic powders, the applicability of the VSSA approach will be tested (in relation with SEM and TEM measurements) in order to expand the actual knowledge and to improve this good available and agglomeration tolerant method. T2 - Workshop on Reference Nanomaterials CY - Berlin, Germany DA - 14.05.2018 KW - VSSA KW - Nanomaterial screening KW - Nano-powder characterization PY - 2018 AN - OPUS4-45099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kupsch, Andreas A1 - Trappe, Volker A1 - Müller, Bernd R. A1 - Bruno, Giovanni T1 - Evolution of CFRP stress cracks observed by in situ X-ray refractive imaging N2 - Modern air-liners and rotor blades of wind turbines are basically made of fiber reinforced plastics (FRP). Their failure heavily impairs the serviceability and the operational safety. Consequently, knowledge of the failure behavior under static and cyclic loads is of great interest to estimate the operational strength and to compare the performance of different materials. Ideally, the damage evolution under operational load is determined with in-situ non-destructive testing techniques. Here, we report on in-situ synchrotron X-ray imaging of tensile stress induced cracks in carbon fiber reinforced plastics (CFRP) due to inter fiber failure. An in-house designed compact-tensile testing machine with a load range up to 15 kN was integrated into the beam path. Since conventional radiographs do not reveal sufficient contrast to distinct cracks due to inter fiber failure and micro cracking from fiber bundles, the Diffraction Enhanced Imaging technique (DEI) is applied in order to separate primary and scattered (refracted) radiation by means of an analyzer crystal. In the laboratory, scanning X-ray refraction topography of CFRP has been applied long before but it comes along with several disadvantages: the long total measuring time hampers real time (in-situ) measurements and the required small beam size hinders end-to-end imaging. The introduced technique overcomes both drawbacks. Imaging and tensile test rig are run unsynchronized at the greatest possible frame rate (0.7 s-1 at 28.8 µm pixel size) and smallest possible strain rate (5.5∙10-4 s-1). For 0°/90° non-crimped fabrics (ncf) the first inter fiber cracks occurred at 380 MPa (strain 0.7 %). Prior to failure at about 760 MPa (strain 2.0 %) we observe the evolution of a nearly equidistant 1 mm grid of cracks running across the entire sample in the fully damaged state before total failure. T2 - 41st Risø International Symposium on Materials Science - Materials and Design for Next Generation Wind Turbine Blades CY - Online meeting DA - 07.09.2020 KW - X-ray refraction KW - Diffraction Enhanced Imaging KW - Carbon Fiber Reinforced Plastics KW - In situ tensile test KW - Crack evolution PY - 2020 AN - OPUS4-51223 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mrkwitschka, Paul A1 - Mieller, Björn A1 - Rabe, Torsten A1 - Markötter, Henning ED - Petzow, G. ED - Mücklich, F. T1 - Machine learning assisted characterization of a Low Temperature Cofired Ceramic (LTCC) module measured by synchrotron computed tomography N2 - The 5G technology promises real time data transmission for industrial processes, autonomous driving, virtual and augmented reality, E-health applications and many more. The Low Temperature Co-fired Ceramics (LTCC) technology is well suited for the manufacturing of microelectronic components for such applications. Still, improvement of the technology such as further miniaturization is required. This study focuses on the characterization of inner metallization of LTCC multilayer modules, especially on the vertical interconnect access (VIA). Critical considerations for this characterization are delamination, pore clustering in and at the edge of the VIA, deformation, and stacking offset. A LTCC multilayer consisting of a glassy crystalline matrix with silver based VIAs was investigated by synchrotron x-ray tomography (CT). The aim of this study is to propose a multitude of structural characteristic values to maximize the information gained from the available dataset. Data analysis has been done with the open source software ImageJ as well as several additional plugins. The high-resolution CT data was evaluated through 2D slices for accessibility reasons. The segmentation of all 2000 slices to assess the different regions e.g. pores, silver and glass ceramic was done by a supervised machine learning algorithm. A quantitative evaluation of shape, deformation, and porosity of the VIA with respect to its dimensions is presented and the suitability of the characterization approach is assessed. T2 - 54. Metallographie Taagung CY - Online meeting DA - 16.09.2020 KW - Machine Learning KW - LTCC KW - Synchrotron Tomography PY - 2020 SN - 978-3-88355-422-8 VL - 54 SP - 136 EP - 141 PB - Deutsche Gesellschaft für Materialkunde e.V CY - Sankt Augustin AN - OPUS4-51298 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Mrkwitschka, Paul A1 - Mieller, Björn A1 - Rabe, Torsten A1 - Markötter, Henning T1 - Machine learning assisted characterization of a Low Temperature Co-fired Ceramic (LTCC) module measured by synchrotron computed tomography. N2 - The 5G technology promises real time data transmission for industrial processes, autonomous driving, virtual and augmented reality, E-health applications and many more. The Low Temperature Co-fired Ceramics (LTCC) technology is well suited for the manufacturing of microelectronic components for such applications. Still, improvement of the technology such as further miniaturization is required. This study focuses on the characterization of inner metallization of LTCC multilayer modules, especially on the vertical interconnect access (VIA). Critical considerations for this characterization are delamination, pore clustering in and at the edge of the VIA, deformation, and stacking offset. A LTCC multilayer consisting of a glassy crystalline matrix with silver based VIAs was investigated by synchrotron x-ray tomography (CT). The aim of this study is to propose a multitude of structural characteristic values to maximize the information gained from the available dataset. Data analysis has been done with the open source software ImageJ as well as several additional plugins. The high-resolution CT data was evaluated through 2D slices for accessibility reasons. The segmentation of all 2000 slices to assess the different regions e.g. pores, silver and glass ceramic was done by a supervised machine learning algorithm. A quantitative evaluation of shape, deformation, and porosity of the VIA with respect to its dimensions is presented and the suitability of the characterization approach is assessed. T2 - 54. Metallographie Tagung CY - Online meeting DA - 16.09.2020 KW - Machine Learning KW - LTCC KW - Synchrotron Tomography PY - 2020 AN - OPUS4-51299 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wilbig, Janka A1 - Borges de Oliveira, F. A1 - Obaton, A.-F. A1 - Schwentenwein, M. A1 - Rübner, Katrin A1 - Günster, Jens T1 - Defect detection in additively manufactured lattices N2 - This paper investigates fast and inexpensive measurement methods for defect detection in parts produced by Additive Manufacturing (AM) with special focus on lattice parts made of ceramics. By Lithography-based Ceramic Manufacturing, parts were built both without defects and with typical defects intentionally introduced. These defects were investigated and confirmed by industrial X-ray Computed Tomography. Alternative inexpensive methods were applied afterwards on the parts such as weighing, volume determination by Archimedes method and gas permeability measurement. The results showed, that defects resulting in around 20% of change in volume and mass could be separated from parts free of defects by determination of mass or volume. Minor defects were not detectable as they were in the range of process-related fluctuations. Permeability measurement did not allow to safely identify parts with defects. The measurement methods investigated can be easily integrated in AM process chains to support quality control. KW - Additive manufacturing KW - Quality assurance KW - Defect detection KW - Lattices KW - Ceramics PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-513547 DO - https://doi.org/10.1016/j.oceram.2020.100020 VL - 3 SP - 100020 PB - Elsevier Ltd. AN - OPUS4-51354 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Charmi, Amir A1 - Falkenberg, Rainer A1 - Skrotzki, Birgit T1 - Virtual-lab-based determination of a macroscopic yield function for additively manufactured parts N2 - This work aims for a yield function description of additively manufactured parts of S316L steel at the continuum-mechanical macro-scale by means of so-called virtual experiments using a crystal plasticity (CP) model at meso-scale. Additively manufactured parts require the consideration of the specific process-related microstructure, which prevents this material to be macroscopically treated as isotropic, because of crystallographic as well as topological textures. From virtual experiments, yield loci under various loading conditions are simulated. The scale bridging from meso- to macro-scale is realised by the identification of the simulated yield loci as a modified anisotropic Barlat-type yield model representation. T2 - Workshop on Additive Manufacturing, BAM CY - Berlin, Germany DA - 13.05.2019 KW - Virtual experiments KW - Additive manufacturing KW - Anisotropy KW - Crystal plasticity KW - Scale-bridging PY - 2019 AN - OPUS4-48064 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kuchenbecker, Petra A1 - Lindemann, Franziska A1 - Hodoroaba, Vasile-Dan T1 - Nano Powder - a Challenge for Granulometry N2 - If the particle size decreases, the ratio of surface area to volume increases considerably. This provides benefits for all surface-driven processes that run faster or at lower temperatures than larger particles. However, handling and characterization of the nanopowders are much more difficult. Particularly polydisperse powders with irregular shape, as grinding products, represent a challenge. Granulometry in the submicron and nanoscale often leads to incorrect results without knowledge of particle morphology. This presentation demonstrates potentials of using the volume-specific surface area (SV or VSSA) in the granulometric characterization of nanopowders, for instance, correlations between the volume-specific surface area and the median particle size are discussed considering the particle morphology and the model of the logarithmic normal distribution. Moreover, the presentation deals with the optimal dispersion of nanopowders during sample preparation. Indirect ultrasound device with defined cooling was developed to prevent both contamination by sonotrode abrasion and sample changes by heat. Successful granulometric characterization of nanopowders demands both improved dispersion technology and very often an effective combination of two or more measurement methods. T2 - Jahrestagung der Deutschen Keramischen Gesellschaft CY - Leoben, Austria DA - 06.05.2019 KW - Nano screening KW - VSSA KW - Nano particle KW - Particle size PY - 2019 AN - OPUS4-47976 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Geyler, Paul A1 - Rabe, Torsten A1 - Mieller, Björn A1 - Léonard, Fabien T1 - Machine learning assisted evaluation of the shape of VIAs in a LTCC multilayer N2 - The introduction of the 5G technology and automotive radar applications moving into higher frequency ranges trigger further miniaturization of LTCC technology (low temperature co-fired ceramics). To assess dimensional tolerances of inner metal structures of an industrially produced LTCC multilayer, computer tomography (CT) scans were evaluated by machine learning segmentation. The tested multilayer consists of several layers of a glass ceramic substrate with low resistance silver-based vertical interconnect access (VIA). The VIAs are punched into the LTCC green tape and then filled with silver-based pastes before stacking and sintering. These geometries must abide by strict tolerance requirements to ensure the high frequency properties. This poster presents a method to extract shape and size specific data from these VIAs. For this purpose, 4 measurements, each containing 3 to 4 samples, were segmented using the trainable WEKA segmentation, a non-commercial machine learning tool. The dimensional stability of the VIA can be evaluated regarding the edge-displacement as well as the cross-sectional area. Deviation from the ideal tubular shape is best measured by aspect ratio of each individual layer. The herein described method allows for a fast and semi-automatic analysis of considerable amount of structural data. This data can then be quantified by shape descriptors to illustrate 3-dimensional information in a concise manner. Inter alia, a 45 % periodical change of cross-sectional area is demonstrated. T2 - DKG Jahrestagung 2019 CY - Leoben, Austria DA - 06.05.2019 KW - Machine Learning KW - LTCC multilayer KW - 5G PY - 2019 AN - OPUS4-48289 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Höhne, Patrick A1 - Kuchenbecker, Petra A1 - Rabe, Torsten T1 - Superior granule properties by spray drying controlled destabilized slurries with ultrasound N2 - Homogeneous introduction of organic additives is a key of ceramic powder processing. Addition of organics to ceramic slurries holds advantages compared to dry processing like organic content reduction and a more homogeneous additive distribution on the particle surface. Investigations of the alumina slurries were primarily based on zeta potential measurements and sedimentation analysis by optical centrifugation. Both methods were combined to determine a suitable additive type, amount and composition, whereas the spray drying suitability has been ensured by viscosity measurements. Granules, yielded by spray drying of such ideally dispersed alumina slurries, are mostly hollow and possess a hard shell. Those granules cannot easily be processed and can only hardly be destroyed in the following shaping step, leading to sinter bodies with many defects and poor strength and density. The precise slurry destabilization, carried out after ideally dispersing the ceramic powder, shows a strong influence on the drying behavior of the granules and hence on the granule properties. A promising degree of destabilization and partial flocculation was quantified by optical centrifugation and resulted in improved granule properties. Spray drying the destabilized alumina slurries yielded homogeneous “non-hollow” granules without the above mentioned hard shell. Sample bodies produced of these granules exhibited a reduction of defect size and number, leading to better results for sinter body density and strength. The positive effect of the slurry destabilization has been further improved, by exchanging the atomizing unit from a two-fluid one to an ultrasound atomizer with only minor slurry adjustments necessary. The controlled destabilization and ultrasound atomization of the ceramic slurry show excellent transferability for zirconia and even ZTA (zirconia toughened alumina) composite materials. T2 - Partec 2019 CY - Nuremberg, Germany DA - 09.04.2019 KW - Destabilization KW - Slurry KW - Ultrasound KW - Atomization PY - 2019 AN - OPUS4-48291 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Höhne, Patrick A1 - Mieller, Björn A1 - Rabe, Torsten T1 - Small batch preparation of ready-to-press powder for systematic studies N2 - Efficient studies of scarce or expensive materials require material saving processes. Therefore, a high yield concept for small batch preparation of ready-to-press powder is exemplarily presented for yttria stabilized nano-zirconia (d50 < 50 nm). The concept involves small batch preparation in an ultrasound resonator, dispersant selection based on zeta potential measurements, evaluation of slurry stability using an analytical centrifuge, and preparation of ready-to-press powder by freeze drying. Freeze drying offers key advantages. Process efficiency and high yield above 95 % are independent of sample size. The dried product does not require further mechanical treatment like milling or grinding. Side effects like migration of additives are avoided. An optimized freeze drying process tolerates slurries with moderate stability. Thus, efforts for slurry development can be reduced. Generally, identifying a suitable dispersing agent requires only 3-5 zeta potential measurements. Slurry stability is rechecked using an analytical centrifuge, which also accounts for steric stabilization. An ultrasound resonator is used to disperse the powder without contamination, which becomes critical for small batches. The described route is exemplarily presented for the development of an additive recipe for nano-sized zirconia powder, targeting for good pressing behavior and high green density. Therefore, a variety of binding and lubricating agents were tested. Following the presented route, 80 g zirconia powder were sufficient to conduct a study including slurry development and five sample sets with varying composition, each set comprising five discs (d = 20 mm and h = 2 mm). T2 - 94. DKG Jahrestagung CY - Leoben, Austria DA - 05.05.2019 KW - Fine Powder KW - Slurry KW - Freeze Drying PY - 2019 AN - OPUS4-48293 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -