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ACCORDs is an Horizon Europe project working in the development of an imaging-based characterization framework (ACCORDs framework) for the holistic correlative assessment of Graphene Family Materials (GFMs) as a representative of 2D nanomaterials (NMs) to assess and predict 2D NMs health and environmental risks. The ACCORDs framework will operationalise safe and sustainable by design (SSbD) strategies proposed in past or ongoing H2020 projects or within OECD by correlating low-, medium-, and high-resolution physico-chemical-biological imaging-based methods with non-imaging methods in a tiered approach. ACCORDs will deliver the ACCORDs framework and user guidance, new imaging-based characterisation methods, reference in vitro tests, new reference 2D NMs for different matrices, a new minimum information reporting guideline for FAIR data sharing and reuse of images as well as an atlas with reference images for diagnostics of compromised safety of GFMs/GFM products. The new guidelines and standard proposals will be submitted to standardisation bodies to allow creation of regulatory ready products. The novelty of ACCORDs is in translating the principles of medical imaging-based diagnostics to 2D material hazard diagnostics. ACCORDs will accelerate industrial sectors in the area of aviation, marine construction, drone production, flexible electronics, photovoltaics, photocatalytics and print inks-based sensors. The value ACCORDs proposes to the graphene industry are practical, easy, imaging-based tools for GFM quality monitoring next to the production line with a possibility to be correlated with advanced highresolution imaging characterization methods in case hazard i.e. deviation from controls (benchmark values) are diagnosed. The ACCORDs framework and tools will contribute to the European Green Deal by addressing the topic: “Graphene: Europe in the lead” and to a new European strategy on standardization, released on 2nd February, 2022.
The stress–strain behavior of certain ceramics, such as aluminum titanate (AT, Al2TiO5), has features that are unusual for brittle material. In particular, a substantial nonlinearity under uniaxial tension, and load–unload hysteresis caused by the increase of the incremental stiffness at the beginning of unloading. These features are observed experimentally and attributed to microcracking. In this study, we investigate the mechanical response of an AT material at room and high temperature. Microstructure and microcracking are analyzed by means of electron microscopy, and both synchrotron micro computed tomography (µCT) and refraction radiography (SXRR). Synchrotron refraction radiography is combined with in-situ heating at high-temperatures (up to 1400°C) to be able to monitor the relative closure of microcracks as a function of increasing/decreasing temperatures.
In der automatisierten Ultraschallprüfung von Komponenten mit komplexen Oberflächengeometrien werden zur Führung des Prüfkopfes zunehmend 6-Achsen-Roboter erprobt. Diese stellen die notwendige Automatisierbarkeit und Flexibilität bereit, um die lokal senkrechte Einschallung sicherzustellen. Durch den Einsatz von linearen Arrays und bildgebenden Verfahren können die Bilder oder die daraus extrahierten Merkmale zu einer Rekonstruktion in 3D zusammengesetzt werden. Die Anforderungen an die Prüfbahnen für die bildgebende Array-Ultraschallprüfung gehen dabei über konventionellen Bahnplanungsprogramme hinaus. Es wird ein Prozess vorgestellt, der Roboterbahnen auf der Grundlage des 3D-Modells von Körpern mit doppelt gekrümmter Oberfläche unter Berücksichtigung der Prüfparameter erzeugt. Hierbei wird zum einen die senkrechte Prüfkopfstellung und zum anderen eine optimale Abdeckung der Oberfläche realisiert. Dabei wird die lokale Oberflächengeometrie beachtet, da diese das Reflexionsverhalten beeinflusst und sich daher auf die optimale Verteilung und Orientierung der Prüfpositionen auswirkt. Damit einhergehend erfolgt eine Ablösung von konventionellen Konzepten, die auf linearen Prüfbahnen basieren, welches spannende neue Prüfstrategien eröffnet.
Nanopipettes are a type of solid-state nanopore with needle-like geometry. Their applications range from imaging, sensing, diagnostics, and use as injectors. The response of nanopipette sensors is highly dependent on the size, geometry and chemical properties of the sensing region. As they are increasingly tuned and modified for specific analytes, a better understanding of the surface chemistry and morphology of the inner channel is necessary. With the aim of developing a comprehensive approach for characterisation of such nanopipettes, this research focuses on combining surface-sensitive analysis methods with advanced sample preparation techniques. Quartz substrates were modified by gas phase silanization, a well-utilised technique in the field to enhance performance of nanopipettes, and further functionalised with a metal bis thiolate complex, to aid in chemical analysis. The sample characterisation involved scanning electron microscopy (SEM), low-energy dispersive x-ray spectroscopy (EDX), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Auger electron spectroscopy (AES). Using focused ion beam (FIB) milling under gentle conditions, the inner surface of quartz nanopipettes was exposed whilst preserving the integrity of the overall structure (see figure). Owing to the challenging analysis conditions, modification and analysis of flat quartz substrates has been performed in parallel for optimisation purposes. The results demonstrate the first steps towards full characterisation of nanopipettes at the nanoscale, notably with access to the inner channel. The methods used here can be applied to gain further understanding of the response of these sensors to complex analytes and allow for the study of different surface functionalisations at the all-important sensing region.
Nanopipettes are a type of solid-state nanopore with needle-like geometry. Their applications range from imaging, sensing, diagnostics, and use as injectors. The response of nanopipette sensors is highly dependent on the size, geometry and chemical properties of the sensing region. As nanopipettes are increasingly tuned and modified for specific analytes, a better understanding of the surface chemistry and morphology of the inner channel is necessary. For exploring these effects, quartz nanopipettes were modified by gas phase silanization, a well-utilised technique in the field to enhance performance of nanopipettes, and further functionalised with a metal bis thiolate complex, to aid in chemical analysis. The inner channel of the sensing region was exposed with focused ion beam (FIB) milling as a dedicated sample preparation method for nanoscale surface analysis. The sample characterisation involved scanning electron microscopy (SEM), Auger electron spectroscopy (AES) and low-energy energy dispersive x-ray spectroscopy (EDX). The results demonstrate the first steps towards full characterisation of nanopipettes at the nanoscale, notably with access to the inner channel. The methods used here can be applied to gain further understanding of the response of these sensors to complex analytes, and allow for the study of different surface functionalisation at the all-important sensing region.
Revealing surface functionalities of micro- and nanoplastic particles’ surface by means of XPS
(2024)
Over the last 20 years, many researchers, politicians, and citizens themselves have become increasingly aware of the growing plastic problem of our time. Inadequate recycling concepts, collection points, and careless dumping of plastic products in the environment lead to an accumulation of plastic. External weather influences can cause these to degrade and fractionate, so that today microplastics (1-1000 µm, ISO/TR 21960:2020) [1] of different polymer materials can be detected in all parts of the world.
The precautionary principle applies to microplastics. The particles can break down further to form nanoplastics (<1 µm, ISO/TR 21960:2020) [1]. Whether microplastics or nanoplastics pose a toxicological hazard is being investigated in a variety of ways. Valid results are still pending, however, investigations into the frequency, transport, possible sinks and entry paths must be taken into account. This is why monitoring of microplastics is already required in the revision of the Drinking Water Framework Directive [2]. The same is still pending in the final version of the revision of the Waste Water Framework Directive this year, but is expected.
Nanoplastics are particularly under discussion for having a toxic effect on humans and animals, as these particles are small enough to be absorbed by cells. For targeted toxicological studies, it is important to have test and reference materials that resemble the particles found in the environment. To mimic environmental samples, these materials should also have an irregular shape and show aging at the surface, which can be detected with XPS or SEM/EDS.
BAM in collaboration with the EMPIR project "PlasticTrace" works on a reference material candidate of nano-sized polypropylene (nano-PP) [3]. The nano-PP vials were tested for homogeneity with PTA and further characterized with bulk and surface-sensitive techniques. An SEM image and a corresponding XPS spectrum are presented in Figure 1. Raman measurements as well as XPS indicate an aged surface.
Metallbasierte additive Fertigungsverfahren werden zunehmend industriell zur Anfertigung von komplex geformten Komponenten eingesetzt. In diesem Zusammenhang ist das Laser-Pulverbettschweißen von Metall (PBF-LB/M) ist ein weitläufig genutztes Verfahren. Im PBF-LB/M-Prozess werden lagenweise aufgetragene Metallpulverschichten selektiv mittels eines Lasers aufgeschmolzen. Die Entstehung von internen Fehlstellen (bspw. Porosität, Lunker oder Risse) während des Fertigungsvorgangs stellt ein ernstzunehmendes Risiko für die Bauteilsicherheit und somit für die weitere industrielle Etablierung des Verfahrens dar. Die Entstehung von Fehlstellen hängt eng mit lokalen Änderungen der thermischen Historie des Bauteils zusammen. Mit Hilfe von thermografischen Kameras zur Prozessüberwachung kann die thermische Historie bereits während der Fertigung erfasst werden. Damit eröffnet sich die Möglichkeit, die Entstehung von Fehlstellen anhand der thermografischen Daten vorherzusagen und somit potenziell Kosten für eine nachgelagerte Qualitätssicherung einzusparen.
In diesem Beitrag soll die Modellierung der Fehlstellenvorhersage anhand thermografischer Prozessdaten diskutiert werden. Hierbei liegt ein Schwerpunkt auf der Fragestellung, mit welcher Genauigkeit unterschiedliche Formen von Fehlstellen, im speziellen Anbindungsfehler und Keyhole-Porosität, auf lokaler Bauteilebene vorhergesagt werden können. Weiterhin werden verschiedenen Modelltypen aus dem Bereich des Maschinellen Lernens auf ihre Eignung für die Fehlstellenvorhersage verglichen. Ein weiterer zentraler Aspekt in diesem Zusammenhang ist die Untersuchung der Eingangsdaten des Modells auf ihre Relevanz für das Vorhersageergebnis.
Als Datengrundlage für die durchgeführten Untersuchungen dienen die Fertigungsprozesse von zwei identischen Haynes-282-Bauteilen (Nickel-Basislegierung), welche mit Hilfe einer im kurzwelligen Infrarotbereich arbeitenden Thermografiekamera überwacht wurden. Das Bauteildesign umfasste lokale Bereiche, in denen mit Hilfe einer Parametervariation die Entstehung von Fehlstellen forciert wurde. Um die Position und Größe der entstandenen Defekte zu quantifizieren, wurden beide Bauteile nach erfolgter Fertigung mittels Computertomografie (CT) geprüft. Im Rahmen der Datenvorbereitung für die Modellierung erfolgte eine Reduzierung der erhobenen Thermogramme zu physikalisch-interpretierbaren Merkmalen (bspw. Schmelzbadfläche oder Zeit-über-Schwellwert). Weiterhin erfolgte eine Registrierung der thermografischen Daten mit den Fehlstellen-Referenzdaten der CT, um eine exakte örtliche Überlagerung von thermischer Information und lokalem Fehlstellenbild zu erzielen. Zur Ermöglichung einer lokalen Fehlstellenvorhersage wurden die thermografischen Daten schichtweise in kleinteiligen Volumina angeordnet, welche als Eingangsgröße für die genutzten ML-Algorithmen dienten.
Die Ergebnisse der Untersuchungen zeigen, dass sich die Porosität auf Bauteilschichtebene mit einer hohen Genauigkeit vorhersagen lässt. Eine Vorhersage der Porosität auf lokaler Bauteilebene erweist sich noch als herausfordernd. Die erprobten ML-Algorithmen zeigen vergleichbare Ergebnisse, obwohl ihnen unterschiedliche Modellierungsannahmen zugrunde liegen und sie variierende Komplexität aufweisen. Mit Hilfe der erzielten Erkenntnisse eröffnet sich die Möglichkeit, Rückschlüsse auf die gewählte Prozessüberwachungshardware und Datenvorverarbeitung zu ziehen und somit langfristig die Leistungsfähigkeit von Modellen zur Fehlstellenvorhersage zu verbessern.
Graphene and graphene-oxide (GO) are advanced materials which – similar to other graphene-related 2D materials (GR-2M) - are already used for instance in catalysis processes, biomedical applications, in inks and resins, or as composite materials for the aviation industry. The lateral/structural characterization of graphene oxide (GO) flakes is a challenging task, with steps like sample preparation, representative image selection and exact determination of the particle size distribution of well-defined size and shape descriptors being crucial for an accurate analysis. To ensure that safe-by-design principles are met within the various application fields, the commercial material must be thoroughly characterized and specified through well-known and standardized procedures.
GO flakes with different degrees of complexity were selected to assess the requirements for an accurate evaluation of their physico-chemical properties. These samples show inherent features with complex nanoscale characteristics such as porosity and edge roughness; further, the lateral size (quantified via equivalent circular diameter (ECD), minimum Feret and maximum Feret) of isolated and overlapping particles deposited on a substrate span over several orders of magnitude (nano to micron scale). The samples showed different degrees of agglomeration (and possible aggregation) with sizes ranging between submicron to a few tens of micrometers.
One focus is the automated segmentation and evaluation of images obtained by electron microscopy. The GO samples appear translucent with well-defined contrast between single and overlapping flakes both with the secondary electron detector of type InLens as well as with SEM in the transmission mode (STEM) utilizing a dedicated sample holder. To this end it is of utmost importance for the accurate image segmentation to carefully select thresholds both manually and through semi-automatic approaches using well-known threshold algorithms such as “IsoData” and pre-defined segmentation applications such as the ParticleSizer software package.
Further specific challenges in identifying and extracting key features of selected graphene oxide flakes are being discussed and approaches towards accurate and representative characterization are presented.
Per- and polyfluoroalkyl substances (PFAS) represent a class of synthetic organofluorine chemicals extensively utilized in the manufacturing of various materials such as firefighting foams, adhesives, and stain- and oil-resistant coatings. In recent years, PFAS have been considered as emerging environmental contaminants, with particular focus on perfluoroalkyl carboxylic acids (PFCAs), the most prevalent type among PFAS. PFCAs are characterized by a fully fluorinated carbon backbone and a charged carboxylic acid headgroup. Notably, they have been designated as Substances of Very High Concern and added to the REACH Candidate List due to their persistence in the environment, non-biodegradability and toxicological effects.
Conventional techniques for the analysis of PFCA, such as GC-MS, HRMS and HPLC-based methods, are laborious, not portable, costly and require skilled personnel. In contrast, fluorescence assays can be designed as easy-to-operate, portable and cost-effective methods with high sensitivity and fast response, especially when analyte binding leads to a specific increase of a probe’s emission. Integration of such probes with a carrier platform and a miniaturized optofluidic device affords a promising alternative for PFCA monitoring.
Here, a novel guanidine BODIPY fluorescent indicator monomer has been synthesized, characterized, and incorporated into a molecularly imprinted polymer (MIP) for the specific detection of perfluorooctanoic acid (PFOA). The MIP layer was formed on tris(bipyridine)ruthenium(II) chloride doped silica core particles for optical internal reference and calibration-free assays. Such system allows selective and reliable detection of PFCA from surface water samples, with minimum interference by competitors, matrix effects and other factors. Integration of the assay into an opto-microfluidic setup resulted in a miniaturized and easy-to-operate detection system allowing for micromolar detection of PFOA in less than 15 minutes from surface water sample.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
The recently certified reference material (CRM) BAM-N012 as cubical iron oxide FeOx nanoparticles (NPs) of 8 nm area equivalent square edge length (ESL) and the RM candidate BAM-N013 as nearly spherical NPs of 22 nm size were analyzed in detail by electron microscopy (EM).
For the metrological characterization with SEM, STEM in SEM and TEM, the understanding of the imaging contrasts and sensitivities, and the correct interpretation of the (art)effects which are inherent to each detection mode is necessary.
The same sample areas with NPs deposited on a TEM grid were analyzed by two SEM acquisition modes, i. e. SE InLens and STEM in SEM using a dedicated transmission sample holder, and further, correlatively, analyzed with TEM.
With increasing kV, SE InLens shows increasing particle size (unless overcharging at the particle boundaries is filtered), as a known effect. For STEM-in-SEM the particle size decreases significantly and individual particles are identified easier (at 2 kV only a few single particles can be detected automatically).
❑ Documentation of the sample preparation and measurement conditions (including optimization process) is important for reproducibility.
❑ Plasma cleaning, analysis in the transmission mode at SEM is recommended for FeOx NPs.
❑ Selection of the threshold algorithm can significantly alter the reported ECD.
Sub-4 nm particles from FFF-3D printing measured with the TSI 1 nm CPC and the Airmodus A11 nCNC
(2024)
Concerns have been raised as Fused Filament Fabrication (FFF) desktop 3D printer emits harmful ultrafine particles (dP < 100 nm) during operation in indoor spaces. However, the vast majority of previous emission studies have neglected the possible occurrence of sub-4 nm particles by using conventional condensation particle counter (CPC) for detection. Thus, the total particle emission could be systematically underestimated. This study has compared two diethylene glycol (DEG) based instruments to evaluate their suitability for measuring organic FFF particles in the sub-4 nm size range either as particle counter or as a particle size spectrometer.
Mit der zunehmenden Relevanz der additiven Fertigung in Fertigungsbereiche mit hohen Anforderungen an Bauteilqualität, wird eine gute Prozessüberwachung unausweichlich. Eine Methode, die bereits gute Korrelation mit Bauteilfehlern gezeigt hat, ist die Temperaturüberwachung mithilfe von thermografischen Methoden. Allerdings unterliegt die Bestimmung der Realtemperaturen vielen unterschiedlichen Problemen. Ein Ansatz mit den Herausforderungen umzugehen, stellt der multispektrale Ansatz dar, der im Projekt QT-LPA untersucht und hier vorgestellt wird.
This study introduces an innovative method for efficiently determining the creep properties of high-temperature materials through high-throughput testing, employing digital image correlation [1,2]. The focus is on the AlCoCrFeNiTi alloy [3-5], synthesized by directional solidification, known for its exceptional strength and unique properties. Experimental investigations, including compression, and bending creep tests, were conducted at 750°C.
Capitalizing on the inhomogeneous stress and strain distribution within a cantilever subjected to bending, we leverage this characteristic to extract multiple creep curves from a single test. Stresses at key points were determined using existing analytical solutions [5,6]. Uniaxial tests spanning 300 to 500 MPa initial stress were complemented by bending tests designed to induce similar stress levels. A detailed comparison between bending and uniaxial creep is presented, including the results of verification studies on additional alloys.
This methodology not only expedites testing but also minimizes material usage, energy consumption, and manual labour. This research showcases a reliable and time-efficient approach to exploring the creep behavior of high-temperature materials. The technique is particularly advantageous for characterizing precious alloys with limited dimensions. Microstructural heterogeneity may exist in specimens tested under bending load, however, it can still be correlated to the mechanical properties with modern high-resolution characterization methods. Stress and resulting strain can be directly compared in a single specimen, ensuring uniform manufacturing, and heating history. This method eliminates the possible errors due to testing with different rigs, which could impair the accuracy of studies based on individual tests.
In times of digital data processing and sharing, a central challenge for the Materials Science and Engineering (MSE) community is the complete digital representation of materials, including their relevant processing and microstructure details and the resulting properties. This digital representation, supported by digital infrastructures, enables entirely new qualities of collaborative work and is central to how we will conduct MSE research and develop products in the future. The main challenges are the composition, shaping, and description of the data so that it can be easily interpreted, trusted, and re-used. This presentation introduces our current effort to develop a best practice framework for generating and distributing creep reference datasets for Ni-based superalloys, which builds on previous approaches. Researchers can use such datasets to compare their own experimental or simulation results, used, for instance, to perform simulation-based alloy design and optimization or in the verification of the own testing equipment. The concept includes building an easily accessible digital infrastructure to annotate and discover the datasets and the integration of an ontology that aligns with the necessary metadata schema. With the help of an ontology, the reference dataset for creep can be semantically described, thus enabling the digital representation and reusage of shared concepts from domain experts and the community. To achieve this, it is necessary to establish a defined vocabulary with corresponding relations and annotations. The interplay between a digital infrastructure, the agreement on the necessary metadata and related metadata schema, and an underlying ontology will ensure that data and results can be easily shared, taken up, and re-used, thus fulfilling the FAIR principles (Findable, Accessible, Interoperable, Reusable). Furthermore, we aim to develop a widely accepted definition of reference data and data quality levels and to reach a self-supported community process. We intend to motivate the discussion about reference material datasets, necessary metadata, and future collaborations within the creep community.
Since the original report in 2004 by Novoselov and Geim, Graphene gained incredible attention due to its fascinating properties. In the past 20 years, the synthesis and functionalization of graphene has evolved significantly[3]. Different synthesis techniques were developed which led to other graphenerelated materials such as graphene oxide (GO) or elemental-doped graphene. Further chemical functionalization can enhance but also alter or reduce specific properties of the graphene. To reveal the nature of these materials a proper physico‑chemical characterization with different analytical techniques is crucial.
Single-layer GO flakes kindly provided by Graphenea (Spain) were prepared for systematic image analysis. These flakes were disposed on an alignment-marked SiO2 substrate and correlatively imaged by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Raman spectroscopy. The high lateral resolution and/ or extreme surface sensitivity of the mentioned
techniques is necessary to explore monolayers. The ToF-SIMS images match well with the SEM and AFM images and provide information about the chemistry. With 2D Raman spectroscopy it is possible to differentiate between the number of stacked single-layer flakes. This is visualized in a 3D image (Figure b). Well-defined GO flakes could be used as a reference material for imaging of graphene-like structures but also of other types of 2D materials.
In addition to these monolayer GO flakes, commercial graphene-containing inks (Haydale) with a more complex morphology were also correlatively imaged. ToF-SIMS and SEM images were merged to identify the origin of different chemical fragments. The findings correlate closely with the expectation that the specific functionalizations (with fluorine and nitrogen as marker elements) are present only on the graphene flakes as presumed from the SEM images. Energy-dispersive X-ray spectroscopy (EDX) supports these results, yet with a much lower sensitivity compared to ToF-SIMS.
Since the original report in 2004 by Novoselov and Geim, Graphene gained incredible attention due to its fascinating properties. In the past 20 years, the synthesis and functionalization of graphene has evolved significantly[3]. Different synthesis techniques were developed which led to other graphenerelated materials such as graphene oxide (GO) or elemental-doped graphene. Further chemical functionalization can enhance but also alter or reduce specific properties of the graphene. To reveal the nature of these materials a proper physico‑chemical characterization with different analytical techniques is crucial.
Single-layer GO flakes kindly provided by Graphenea (Spain) were prepared for systematic image analysis. These flakes were disposed on an alignment-marked SiO2 substrate and correlatively imaged by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Raman spectroscopy. The high lateral resolution and/ or extreme surface sensitivity of the mentioned
techniques is necessary to explore monolayers. The ToF-SIMS images match well with the SEM and AFM images and provide information about the chemistry. With 2D Raman spectroscopy it is possible to differentiate between the number of stacked single-layer flakes. This is visualized in a 3D image (Figure b). Well-defined GO flakes could be used as a reference material for imaging of graphene-like structures but also of other types of 2D materials.
In addition to these monolayer GO flakes, commercial graphene-containing inks (Haydale) with a more complex morphology were also correlatively imaged. ToF-SIMS and SEM images were merged to identify the origin of different chemical fragments. The findings correlate closely with the expectation that the specific functionalizations (with fluorine and nitrogen as marker elements) are present only on the graphene flakes as presumed from the SEM images. Energy-dispersive X-ray spectroscopy (EDX) supports these results, yet with a much lower sensitivity compared to ToF-SIMS.
Bei der Versorgung von Zähnen mit dentalen Kronenrestaurationen entsteht ein Kronen-Zement-Zahn-Komplex (KZZK). Dentale Werkstoffe überzeugen mit besten Materialeigenschaften, aber wie funktionieren sie im Verbund? Unsere zentrale Annahme lautet, dass die Alterung des KZZK eine zentrale Rolle bei Misserfolgen spielt. Präsentiert werden die Methodik und Bilder der ersten Arbeitsphase.
Hybrid additive manufacturing is becoming increasingly important in the field of additive manufacturing. Hybrid approaches combine at least two different manufacturing processes. The focus of this work is the build-up of geometries onto conventionally manufactured parts using laser-based powder bed fusion of metals (PBF-LB/M). The hybrid build-up requires a precise position detection system inside the PBF-LB/M machines to determine the exact position of the existing component. For this purpose, high-resolution camera systems can be utilized. However, the use of a camera system is associated with several challenges. The captured images are subject to various distortions of the optical path. Due to these distortions, it is not possible to use the images for measurements and, therefore, it is not possible to calculate the positions of objects. In this study a homography matrix is calculated to correct keystone distortion in the images. Different calibration patterns have been tested for the calculation of the homography matrix. The influence of the number of calibration points on the precision of position detection of objects is determined. Furthermore, the influence of an additional camera calibration by using ChArUco boards is evaluated. The result is a camera calibration workflow with associated calibration pattern for a precise position detection of parts inside PBF-LB/M machines allowing a hybrid build-up with minimum physical offset between base component and build-up.