Chemie und Prozesstechnik
Filtern
Dokumenttyp
- Zeitschriftenartikel (1171)
- Vortrag (1069)
- Posterpräsentation (442)
- Beitrag zu einem Tagungsband (174)
- Forschungsdatensatz (55)
- Sonstiges (43)
- Buchkapitel (24)
- Forschungsbericht (23)
- Dissertation (15)
- Beitrag zu einem Sammelband (13)
- Handbuch (5)
- Video (5)
- Zeitschriftenheft (Herausgeberschaft für das komplette Heft) (3)
- Sammelband (Herausgeberschaft für den kompletten Band) (2)
- Tagungsband (Herausgeberschaft für den kompletten Band) (1)
- Newsletter (1)
Sprache
- Englisch (3046) (entfernen)
Schlagworte
- Nanoparticles (114)
- Fluorescence (112)
- Concrete (89)
- LIBS (81)
- Mechanochemistry (72)
- Quantum yield (71)
- Ultrasound (71)
- SAXS (69)
- Non-destructive testing (68)
- XPS (61)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (1085)
- 6 Materialchemie (973)
- 8 Zerstörungsfreie Prüfung (774)
- 6.1 Oberflächen- und Dünnschichtanalyse (348)
- 6.3 Strukturanalytik (322)
- 1.1 Anorganische Spurenanalytik (277)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (232)
- 8.0 Abteilungsleitung und andere (224)
- 1.2 Biophotonik (210)
- 4 Material und Umwelt (186)
Paper des Monats
- ja (26)
Gold-based nanoparticles below 2 nm in size are promising as luminescent probes for in vivo bioimaging, owing to their brightness and rapid renal clearance. However, their use as contrast agents in the near-infrared II (NIR-II, 1000–1700 nm) range remains challenging due to their low photoluminescence (PL) quantum yield. To address this, PL enhancement can be achieved by either rigidifying the ligand-shell structure or increasing the size of the ligand shell. In this study, we synthesized ultra-small gold nanoparticles stabilized by co-ligands, namely monothiol and short dithiol molecules. By precisely controlling the amount of reducing agent used during particle preparation, we successfully modulated the physicochemical properties of the co-ligand shell, including its size, composition, and structure. Consequently, we achieved a remarkable 60-fold increase in the absorption cross-section at 990 nm while maintaining the small size of the 1.5-nm metal core. The analytical and optical characterization of our thiol-capped gold nanoparticles indicates that the ligand shell size is governed by the quantity of the reducing agent, which, in turn, impacts the balance between radiative and non-radiative processes, thereby influencing the PL quantum yield.
Tailor-made nanoparticles are of increasing interest in e.g. catalysis, as sensor materials, analytical assays, or can have superior photophysical properties. A major issue concerning the preparation of high-quality and functional nanoparticles is a good control of particle size, shape, polydispersity, and composition.
Small Angle X-ray Scattering (SAXS) is a non-destructive method for the analysis of nanostructures in a wide variety of materials. This method allows determining averaged structural parameters on a length scale from just above atomic sizes up to several 100 nanometers such as sizes, size distributions, volume fractions, and inner surface sizes. Moreover, anomalous Small Angle X-ray Scattering (ASAXS) exploits the anomalous dispersion of the scattering amplitudes near the X-ray absorption edges of the elements contained in the sample. These element sensitive contrast variations can be used to analyse average composition fluctuations on the nm scale. Two kinds of nanoparticles are chosen here to elaborate the advantages of ASAXS in the analysis of complex materials.
A facile and efficient methodology is developed for the thermal synthesis of size-tunable, stable, and uniform bimetallic NiCu core–shell nanoparticles (NPs) for various application in catalysis. Their diameter can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio is adjustable in a wide range from 1:1 to 30:1. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering (ASAXS), X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Here, we focus on the ASAXS method and its ability to analyses nanostructure parts and their compositions at once. As a result, a NiCu alloyed core surrounded by a Ni enriched shell and an outer NiO shell was found.
Semiconductor nanocrystals (quantum dots, QDs) are well known for their superior photophysical properties and enabled advancements in several key technologies of the 21st century and numerous technological applications like in photovoltaics, LED displays, photocatalysis, and biosensing. To achieve high photoluminescence quantum yields (PLQY) and enhanced photostability the QD core needs to be passivated by a second semiconductor, which possess a larger band gap to confine the charges within the QD core. An important parameter is thereby the lattice mismatch between the core and shell. To avoid strong lattice strain, which would alter the photophysical properties, an intermediary shell can be used as a lattice adapter between the core and the outer shell leading to core/shell/shell systems. These systems have shown to possess high PLQYs combined with a strong long-term stability and can be found in modern QLED displays. ASAXS was used here to better understand the core/shell/shell structure of InP/ZnSe/ZnS QDs to enable a correlation between their structural and photophysical properties.
Detaillierte Kenntnisse der elastischen Materialeigenschaften sind in vielen ingenieurtechnischen Bereichen von grundlegender Bedeutung. Insbesondere für die Anwendung von Predictive Maintenance und Structural- Health-Monitoring Methoden mit Ultraschall ist die genaue Kenntnis der elastischen Materialkonstanten eine Grundvoraussetzung. Die von den Herstellern zur Verfügung gestellten Angaben zu den elastischen Materialkonstanten, insbesondere für Polymere und faserverstärkte Kunststoffe, sind jedoch oft unzureichend, da diese vom Produktionsprozess abhängig sind und sich zusätzlich aufgrund von Materialabbauprozessen oder Ermüdung ändern können. In der Praxis liegen polymere Werkstoffe, faserverstärkte Kunststoffe und Metalle oft als dünne, plattenförmige Strukturen vor, in welchen sich geführte Ultraschallwellen (UGWs) ausbreiten können. In der aktuellen Forschung sind bereits verschiedene Neuronale Modelle zur Bestimmung der elastischen Konstanten und der Materialcharakterisierung mittels UGWs bekannt. Ein einfaches neuronales Netz, mit aus Dispersionsbildern extrahierten Werten für Frequenz und Wellenzahl ausbeutungsfähiger Moden als Eingabe, zur Vorhersage der elastischen Konstanten wird in verwendet. Ein rekurrentes Neuronales Netz mit einem Zeit-Frequenz Vektor als Eingabe wird in angewandt, während in ein 1D- Convolutional-Neuronal-Networks (CNN) unter Verwendung der zeitlichen Auslenkung der Grundmoden und in ein 2D-CNN unter Verwendung einer polaren Gruppengeschwindigkeitsdarstellung zur Bestimmung der elastischen Konstanten verwendet wird. In diesem Vortrag wird ein Ansatz zur Bestimmung der isotropen elastischen Konstanten von dünnen Platten auf der Grundlage von UGWs unter Verwendung von Dispersionsbildern und 2D-CNNs vorgestellt. Dispersionsabbildungen aus numerischen Simulationen werden mithilfe verschiedener Methoden vorverarbeitet, um realistische Messdaten zu simulieren. Mit den modifizierten Daten wird das Modell trainiert und die Architektur optimiert. Anschließend wird die Genauigkeit des erzeugten Modells mit realen Messdaten validiert. Es wird gezeigt, dass 2D-CNNs in der Lage sind, die isotropen elastischen Konstanten anhand multimodaler Merkmale aus Dispersionsbildern vorherzusagen, ohne dass eine anfängliche Schätzung der Parameter oder manuelle Merkmalsextraktion erforderlich ist.
This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Fungal pigments such as melanin and carotenoids are distinctive markers of animal and plant pathogenic fungi as well as their environmental relatives. These complex pigments play important roles in pathogenicity and stress tolerance while also being useful as biomarkers. Accordingly, it is important to be able to identify in situ the pigments in black fungi, a group of clinical and environmental importance. In this study, wild-type and genetically modified strains of Knufia petricola A95 and wild fungal cells attached to ancient rock were investigated for their spectroscopic and microscopic Raman features and morphological appearance. Knockout mutants of melanin synthesis genes pks1 (polyketide synthase), sdh1 (scytalone dehydratase), and both pks1 and the carotenoid synthesis gene phd1 (phytoene desaturase) were studied We applied two different Raman microscopes using two lasers, with 633 nm and 488 nm wavelengths. We analyzed and compared Raman spectra between the measured reference substances and the mutant and wild-type strains. In the wild strain WT:A95, the peaks close to melanin peals were found at 1353 cm−1 and 1611 cm−1. There are no characteristic melanin peaks at 1580–1600 cm−1 and around 1350 cm−1 at the spectrum of the Δpks1/Δphd1 mutant and the Δsdh1 mutant. The Δpks1 mutant spectrum has the peaks at the beta-carotene v2 C-C in-plane stretch at 1155 cm−1 and v3 C-CH3 deformation at 1005 cm−1. The peaks of carotenoids and melanin were found in all mutants and the wild strain, except the Δpks1/Δphd1 mutant. Raman spectra allow for discrimination between the various pigments. Hence, interactions between natural fungal melanin, as well as other protective pigments, and complex environmental matrices can be characterized on a range of spatial and temporal scales.
BAM (Federal Institute for Materials Research and Testing) is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the European Commission’s project of PREDIS, the supply of power to the battery-less sensors and the data acquired by such sensors are transmitted through the metallic waste drum by an innovative wireless technology developed by VTT (Technical Research Centre of Finland) in order to ensure long-term operation while keeping the integrity of the sealed container.
BAM is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the EU project PREDIS, the data acquired by such sensors are transmitted from inside to outside the metallic waste drum through wireless technology.
The sensing system is made of a chain of small sensing units, called SensorNodes. Each SensorNode includes two off-the-shelf sensors, one for relative humidity and temperature and one for pressure and temperature. A SensorNode is designed to have a unique identifier, in order to be connected to other units while being uniquely discoverable by a standard communication protocol. In this way, a distributed matrix of measurement points is created.
One of the most challenging tasks in designing a measurement system to run in a harsh environment (such as hardening concrete) is to let the sensors sense the external environment without damaging the sensor itself.
To keep the external environment away from the electronic board while still letting the sensors measure the concrete behavior, holes have been drilled through the lid and covered from the inside with a layer of a porous membrane. The membrane's pores allow water and gas particles to pass through and let the enclosed air equilibrate with the external environment.
With the help of the developed sensors, monitoring concrete in cemented waste drums will be possible. The derived data will also serve as the basis for ongoing modeling approaches for digital twins within the Predis project. Overall, the sensors provide a means of enabling safe nuclear waste management through advanced monitoring
Research on per- and polyfluoroalkyl substances (PFAS) frequently incorporates organofluorine measurements, particularly because they could support a class-based approach to regulation. However, standardized methods for organofluorine analysis in a broad suite of matrices are currently unavailable, including a method for extractable organofluorine (EOF) measured using combustion ion chromatography (CIC). Here, we report the results of an international interlaboratory comparison. Seven laboratories representing academia, government, and the private sector measured paired EOF and PFAS concentrations in groundwater and eel (Anguilla rostrata) from a site contaminated by aqueous film-forming foam. Among all laboratories, targeted PFAS could not explain all EOF in groundwater but accounted for most EOF in eel. EOF results from all laboratories for at least one replicate extract fell within one standard deviation of the interlaboratory mean for groundwater and five out of seven laboratories for eel. PFAS spike mixture recoveries for EOF measurements in groundwater and eel were close to the criterion (±30%) for standardized targeted PFAS methods. Instrumental operation of the CIC such as replicate sample injections was a major source of measurement uncertainty. Blank contamination and incomplete inorganic fluorine removal may introduce additional uncertainties. To elucidate the presence of unknown organofluorine using paired EOF and PFAS measurements, we recommend that analysts carefully consider confounding methodological uncertainties such as differences in precision between measurements, data processing steps such as blank subtraction and replicate analyses, and the relative recoveries of PFAS and other fluorine compounds.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of twodimensional ROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed
algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution
and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free twodimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. Our results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further. Furthermore, first data about the degradation of single-stranded DNA binding-proteins (G5P / GV5 and hmtSSB) under vacuum and NAP-XPS conditions are presented.
We give an overview about recent work concerning ionizing radiation damage to Oligonucleotides, plasmid DNA, DNA binding proteins (G5P), and DNA-protein complexes.
We focus on combining new experimental setups with Geant4/TOPAS particle scattering simulations to understand the effets of ionizing radiation.
Radiation biophysics
(2023)
A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
In the course of tomorrow's hydrogen-based energy transition, the construction of the corresponding infrastructure will play a central role. The majority of materials used to date are typically welded for component fabrication. In that context, steels are widely applied and can be prone to hydrogen embrittlement. This includes the classical delayed cold cracking during welding processing as well as embrittlement phenomena during operation. For the evaluation of any hydrogen effect on, for example, the mechanical properties of a welded metallic material, the hydrogen content must be precisely determined. In the case of welds, for example, according to ISO 3690, this is the isothermal carrier gas hot extraction (CGHE). CGHE is based on accelerated hydrogen degassing due to thermal activation of hydrogen at elevated temperatures. In addition to the pure quantification of hydrogen, thermal desorption analysis (TDA) with varied heating rates can be used to determine and evaluate the bonding state at microstructural defects in the material. For both techniques, experimental and measurement influences have to be considered, which have a great effect on the result. For CGHE, for example, ISO 3690 suggests different sample geometries as well as minimum extraction times. The present study summarizes results and experiences of numerous investigations with different sample temperatures and geometries (ISO 3690 type B and cylindrical TDA samples) regarding: the influence of the sample surface (polished/welded), measurement accuracies depending on the sample volume as well as the insufficient monitoring of the effect of the PI controller on the extraction temperature. In particular, a deviating extraction temperature to the set temperature, can significantly falsify the measurement results. Based on the results, methods are shown to quickly reach the desired extraction temperature without having to physically interfere with the measurement equipment. This serves to substantially improve the reliability of hydrogen measurement through increased signal stability and accelerated hydrogen desorption. In general, an independent temperature measurement with dummy samples for the selected heating procedure is advisable to exclude possible unwanted temperature influences already before the measurement. In addition (and way more important), the methods described can be transferred directly to industrial applications.
Multi-principal element alloys (MPEAs) are innovative materials that have attracted extensive research attention within the last decade. MPEAs are characterized by a solid solution of equiatomic metallic elements. Depending on the number of elements, they are also referred as high entropy alloys (HEAs with n ≥ 4 elements like CoCrFeMnNi) and medium-entropy alloys (MEA with n = 3 elements CoCrNi). Depending on the alloy concept, MPEAs show exceptional properties in terms of mechanical performance or corrosion resistance at extreme environments. In that connection, hydrogen and its challenges for the most metallic materials gets more and more important. MPEAs are candidate materials for the substitution of conventional materials like austenitic stainless steels e.g., at very high-pressure up to 1000 bar. Those pressures are typically reached in valves or compressors for refueling of tanks with operational pressure of 700 bar. So far, the susceptibility of HEA/MEAs to hydrogen assisted cracking (if any) and the especially the underlying hydrogen uptake and diffusion was not within the scientific scope and not investigated in detail yet. For that reason, we focused on the hydrogen absorption the characterization of the hydrogen diffusion and trapping at elevated temperatures in a CoCrFeMnNi-HEA (each element with 20 at.-%) and CoCrNi-MEA, each element with 33.3 at.-%). As reference grade, the commercially available austenitic stainless steel AISI 316L was investigated. High-pressure hydrogen charging was conducted at different pressures in autoclave environment with maximum value of 1,000 bar. Thermal desorption analysis (TDA) via carrier gas hot extraction with coupled mass spectrometry was used with a max. heating rate of 0.5 K/s up to 650 °C. The measured desorption spectra of the different samples were deconvoluted into a defined number of individual peaks. The individually calculated peak temperatures allowed the definition of activation energies for predominant trap sites in the respective materials as well as the percentage share of the totally absorbed hydrogen concentration. The results present for the first time the complex interaction of both MPEAs and high-pressure hydrogen charging. A deconvolution of four peaks was selected and a main desorption peak was identified the dominant hydrogen trap containing the biggest share of the absorbed hydrogen concentration. The chemical composition an austenitic phase of both MPEAs is responsible for delayed hydrogen diffusion and strong, but mostly reversible, trapping. The comparison with the 316L samples showed significantly higher activation energies in the MPEAs, whereas hydrogen was also trapped at very high extraction temperatures. The absorbed maximum hydrogen concentration at 1,000 bar was 130 ppm for the CoCrFeMnNi-HEA, 50 ppm for the CoCrNi-MEA and 80 ppm for the 316L. It is interesting that the CoCrFeMnNi-HEA has obviously a way higher trapping capability compared to the conventional austenitic 316L, which could be a major advantage in terms of resistance to hydrogen assisted cracking.
Covalent organic frameworks (COFs) are a prominent class of organic materials constructed from versatile building blocks via reversible reactions. The quality of imine-linked COFs can be improved by using amine monomers protected with benzophenone forming benzophenone imines. Here, we present a study on substituted benzophenones in COF synthesis via formal transimination. 12 para-substituted N-aryl benzophenone imines, with a range of electron-rich to electron-poor substituents, were prepared and their hydrolysis kinetics were studied spectroscopically. All substituted benzophenone imines can be employed in COF synthesis and lead to COFs with high crystallinity and high porosity. The substituents act innocent to COF formation as the substituted benzophenones are cleaved off. Imines can be tailored to their synthetic demands and utilized in COF formation. This concept can make access to previously unattainable, synthetically complex COF monomers feasible.
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology1 let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators over the last five years. Combined with universal, automat-ed data correction pipelines, as well as our analysis and simulation software, this led to more than 40 papers2 in the last 5 years with just over 2 full-time staff members.
While this approach greatly improved the consistency of the results, the consistency of the samples and sample series provided by the users was less reliable nor necessarily reproducible. To address this issue, we built an EPICS-controlled, modular synthesis platform to add to our laboratory. To date, this has prepared over 1200 additional (Metal-Organic Framework) samples for us to meas-ure, analyse and catalogue. By virtue of the automation, the synthesis of these samples is automat-ically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases alongside the morphological results obtained from the automated X-ray scat-tering analysis.
Having developed these proof-of-concepts, we find that the consistency of results are greatly im-proved by virtue of their reproducibility, hopefully adding to the reliability of the scientific findings as well. Additionally, the nature of the experiments has changed greatly, with much more emphasis on preparation and careful planning. This talk will discuss the advantages and disadvantages of this highly integrated approach and will touch upon upcoming developments.
Per- and polyfluoroalkyl substances (PFAS) are a large group of more than 10,000 anionic, cationic, zwitterionic or neutral organofluorine surfactants. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. While liquid chromatography tandem mass spectrometry (LC-MS/MS) is commonly used technique to characterize targeted PFAS in environmental samples, there are more than 10,000 different PFAS known, which have various headgroups and properties. Therefore, several analytical techniques are available to analyse various groups or pools of PFAS or “all” PFAS as a sum parameter. Current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Both approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Previously, mechanochemical treatment of polychlorinated organic compounds in soils showed an efficient dechlorination. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination with gas chromatography mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), respectively, as well es the fluoride mineralization by ion chromatography (IC) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
This contribution provides an overview of the BAMline synchrotron radiation beamline, which specializes in hard X-ray spectroscopy techniques for materials research. The BAMline offers X-ray absorption spectroscopy (XAS), x-ray fluorescence spectroscopy (XRF), and tomography to study materials' electronic structure, chemical composition, and structure. Key capabilities include standard and dispersive XAS for electronic structure, micro-XRF for elemental mapping, coded aperture imaging, and depth-resolved grazing exit XAS. The BAMline enables in situ characterization during materials synthesis and functions for energy, catalysis, corrosion, biology, and cultural heritage applications.
Ongoing developments like the implementation of machine learning techniques for experiment optimization and data analysis will be discussed. For instance, Bayesian optimization is being used to improve beamline alignment and scanning. An outlook to the future, where the BAMline will continue pioneering dynamic and multi-scale characterization, aided by advanced data science methods, to provide unique insights into materials research, will be given.
The structure and composition of ancient gold objects retain information about their long history of manufacture, from the exploitation of the ore to the finishing touches, as well as evidence of their use, deposition, and degradation. By developing an efficient analytical strategy, it is possible to retrieve that information. This chapter sets the necessary foundation 131to explore fully the analytical results presented in the following chapters of this volume. The techniques employed in the analyses of the Egyptian jewellery are described and the analytical parameters provided. For more established techniques, only brief introductions are presented, while more recent developments are presented in greater detail.
Enhancing efficiency at bamline: employing data science and machine learning for x-ray research
(2023)
This talk discusses how data science and machine learning techniques are being applied at the BAM Federal Institute for Materials Research and Testing to enhance efficiency and automation at the BAMLine synchrotron facility. The methods presented include Gaussian processes and Bayesian optimization for beamline adjustment and optimization of X-ray measurements. These statistical techniques allow automated alignment of beamline components and active learning scanning to reduce measurement time.
Additional machine learning methods covered are neural networks for quantification of X-ray fluorescence (XRF) data and decoding coded apertures.
Laser breakdown spectroscopy (LIBS) is a common tool for applications in various fields of science and technology. Originally an atomic analysis technique, LIBS was later extended to molecular analysis due to the transient nature of the laser-induced plasma, which develops from a hot dissociation stage on a nanosecond to several microsecond scale to a relatively cold recombination stage on a scale of 10 to 100 microseconds after breakdown. Molecules formed during the recombination stage or incompletely dissociated after ablation can be efficiently detected, allowing the analysis of "difficult" elements or even molecular isotopes. However, with a small amount of ablated material and a short lifetime of the luminous plasma, analytical signals, especially molecular ones, can be very weak.
Several methods have been proposed for reheating the plasma and increasing its lifetime, for example, a two-pulse LIBS or a LIBS combined with microwave radiation or with an electric spark discharge. Here we propose another one, LIBS combined with a capacitively coupled RF discharge at 13.6 MHz. The advantages of this combination are an increase in the lifetime of atomic and molecular emission and operation in a low-pressure atmosphere, which significantly reduces pressure line broadening and allows high-resolution spectroscopy. Another major advantage is operating in a chemically controlled atmosphere that can predictably drive desired chemical reactions. In this presentation, we will show the first results obtained with RF-LIBS combination. These will include separate and joint characterization of LIBS and RF plasmas and evaluation of its potential for elemental and molecular analysis and for plasma enhanced chemical vapor deposition.
Many applications of LIBS require the measurement of plasma temperature and electron density, which in turn requires knowledge of the integrated line intensity and the shape of the spectral lines. While the integral intensity is preserved as light passes through the spectrometer, the shape emitted by an individual atom or ion is greatly distorted. This is due, firstly, to the transfer of light through the plasma (self-absorption), secondly, to the influence of the instrumental function of the spectrometer, and, thirdly, to the aberrations of the optical system. In addition, processing of spectral information, such as background removal, noise reduction, deconvolution, and line fitting, introduces additional errors in the reconstructed linewidth and line integral, which leads to erroneous temperature and electron density values.
This communication will be devoted to the general shortcomings of spectral data processing and the resulting inaccuracies in determining the plasma parameters. The analysis is based on the use of synthetic spectra generated by plasma with known temperature and particle density. The estimation of errors caused by inadequate processing of the spectral data is made by comparing the initial and determined plasma parameters. As a result, an improved data processing method will be proposed that takes into account the spectrum distortion by the instrumental function and integration on the pixel detector. The former is accounted for by convolution (instead of deconvolution) of the estimated line profile using a predetermined slit function, and the latter is achieved by piecewise integration of the line profile by the pixel detector, taking into account the pixel size and uniform or non-uniform pixel separation. Recommendations will be made for which analytic function best approximates the observed spectral lines and examples will be given for the application of this routine to calibration-free LIBS using both synthetic and experimental data.
In the LIBS literature, almost every second article reports the determination of the plasma temperature using the Boltzmann plot method or the determination of the electron density using the Stark line broadening relation. The first requires the measurement of the integrated intensities of the spectral lines, and the second requires the measurement of the linewidth, under the same assumption of optical thinness. It is taken for granted that this can be easily done either by working with the raw spectra or by fitting an appropriate function to the observed spectral lines. As a rule, reported data are not verified either by an alternative method (e.g., Thomson scattering) or by computer simulations using synthetic spectra.
However, the question of how to extract the necessary information from the raw spectral data is not as simple as it might seem. The quality of such an extraction will depend critically on the type of spectral instrument used, its resolution, and the noise superimposed on the data. The problem is that we do not see the spectrum emitted by the plasma, but the spectrum distorted by the measurement; an exaggerated example of such a distortion is shown in Fig. 1. The elimination of this distortion belongs to the class of inverse problems, the so-called ill-posed problems, whose successful solution crucially depends on the quality of the information available. When it comes to spectroscopy, quality of information primarily means high spectral resolution and low noise. Not all spectrometers used in LIBS can provide the quality needed to solve the inverse problem; this casts doubt on many published plasma measurements.
The current presentation will be devoted to general shortcomings in the processing of spectral data and inaccuracies in the determination of plasma parameters resulting from these shortcomings. The analysis is based on the use of synthetic spectra produced by plasma with known characteristics, i.e., temperature, species densities, and electron density. The estimation of errors caused by inadequate processing of spectral data is made by comparing the initial and reconstructed plasma parameters. Recipes will be given for which the analytic function best approximates the observed spectral lines, and how data processing errors affect accuracy of calibration-free LIBS will be discussed. These issues were only partially covered in previously published works, for example [1, 2, 3].
The aim of the project is to develop an adequate model of laser induced plasma for conditions expected in space missions, i.e., vacuum, or low-pressure CO2 atmosphere. Numerical modeling will help to find optimal experimental parameters for the laser ablation under artificial lunar or Martian environments and obtain both qualitative, in terms of a composition, and quantitative, in terms of an elemental abundance, information about interrogated samples based on spectral data generated by the model. The best operational conditions will be found at a low cost without conducting tedious and time-consuming optimization experiments. The modeling approaches will be supported by machine learning to accelerate the optimization.
The application of multivariate data analysis is essential in extracting the full potential of laser-induced XUV spectroscopy (LIXS) for high-precision elemental mapping. LIXS offers significant advantages over traditional laser-induced breakdown spectroscopy in UV-vis (LIBS), including higher precision and a wider dynamic range,[1,2] while making it possible to determine light elements like lithium and fluorine. However, it is challenged by the presence of unresolved transition arrays (UTAs) for heavier elements. These UTAs add considerable complexity to the spectral data, often concealing crucial information. In this study, we employ well-established multivariate data analysis techniques and intensive data preprocessing to unravel this contained information.
The refined analysis reveals a high level of detail, enabling the precise identification of inhomogeneities within material samples. Our approach has particular relevance for studying aging processes in lithium-ion batteries (LIBs), specifically in relation to varying cathode materials and fluorine-containing polymer binder content. By combining elemental distribution with structural information, this improved method can offer a more comprehensive understanding of sample inhomogeneities and aging processes in LIBs, contributing to the development of more reliable and sustainable battery technologies.
Laser-induced XUV spectroscopy (LIXS) is an emerging technique for elemental mapping. In comparison to conventional laser-induced breakdown spectroscopy in UV-vis (LIBS), it has a higher precision and wider dynamic range, and it is well suited for the quantification light elements like lithium and fluorine. Further it can spot oxidation states. The XUV spectra are produced at a very early stage of the plasma formation. Therefore, effects from plasma evolution on the reproducibility can be neglected. It has been shown, that high-precision elemental quantification in precursor materials for lithium-ion batteries (LIBs) can be performed using LIXS. Based on these results, LIXS mapping was used to investigate aging processes in LIBs. Different cathode materials with varying compositions of fluorine containing polymer binders were compared at different stages of aging. Due to effects comparable to X-ray photoelectron spectroscopy but in reverse, monitoring of changes in the oxidation state is envisioned, which makes information about the chemical environment of the observed elements accessible. The combination of elemental distribution and structural information leads to a better understanding of aging processes in LIBs, and the development of more sustainable and safe batteries.
Improved Data Processing for Accurate Plasma Diagnostics with Implications for Calibration-Free LIBS
(2023)
Many LIBS papers report the determination of plasma temperature using the Boltzmann plot method or the determination of electron density using the Stark line broadening relation. This requires measuring the integrated intensities of the spectral lines and the linewidth under the assumption of optical thinness. It is taken for granted that this can be easily done either by working with the raw spectra or by fitting the appropriate function to the observed spectral lines. However, extracting the necessary information from raw spectral data is not as easy as it might seem. The quality of such extraction will depend to a decisive extent on the type of spectral instrument used. The spectrum emitted by the plasma is distorted by the device; an example is shown in Fig. 1. The elimination of this distortion belongs to the class of inverse problems, the successful solution of which fundamentally depends on the quality of the available information. When it comes to spectroscopy, the quality of information primarily means high spectral resolution and low noise. Not all spectrometers used in LIBS can provide the quality needed to solve the inverse problem; this casts doubt on many published plasma measurements. This communication will be devoted to the general shortcomings of spectral data processing and the inaccuracies in determining the plasma parameters resulting from these shortcomings. The analysis is based on the use of synthetic spectra generated by plasma with known temperature, particle density and electron density. The estimation of errors caused by inadequate processing of spectral data is made by comparing the initial and measured plasma parameters from the spectra. Recommendations will be made for which analytic function best approximates the observed spectral lines, and how data processing errors affect the accuracy of calibration-free LIBS will be discussed. These issues were only partially covered in previously published works, for example [1, 2].
Introduction
Lithium-ion batteries (LIBs) are one key technology to overcome the climate crisis and energy transition challenges. Demands of electric vehicles on higher capacity and power drives research on innovative cathode and anode materials. These high energy-density LIBs are operated at higher voltages, leading to increased electrolyte decay and the current collectors' degradation. Even though this fundamental corrosion process significantly affects battery performance, insufficient research is being done on the aluminum current collector. Fast and convenient analytical methods are needed for monitoring the aging processes in LIBs.
Methods
In this work glow-discharge optical emission spectrometry (GD-OES) was used for depth profile analysis of aged cathode material. The measurements were performed in pulsed radio frequency mode. Under soft and controlled plasma conditions, high-resolution local determination (in depth) of the elemental composition is possible. Scanning electron microscopy (SEM) combined with a focused ion beam (FIB) cutting and energy dispersive X-ray spectroscopy (EDX) was used to confirm GD-OES results and obtain additional information on elemental distribution.
Results
The aging of coin cells manufactured with different cathode materials (LCO, LMO, NMC111, NMC424, NMC532, NMC622, and NMC811) was studied. GD-OES depth profiling of new and aged cathode materials was performed. Quantitative analysis was possible through calibration with synthetic standards and correction by sputter rate. Different amounts of aluminum deposit on the cathode surface were found for different materials. The deposit has its origin in the corrosion of the aluminum current collector. The results are compatible with results from FIB-EDX. However, GD-OES is a faster and less laborious analytical method. Therefore, it will accelerate research on corrosion processes in high energy-density batteries.
Innovative aspects
- Quantitative depth profiling of cathode material
-Monitoring of corrosion processes in high energy-density lithium-ion batteries
- Systematic investigation of the influence of different cathode materials
Per- and polyfluoroalkyl substances (PFAS) are a large group of organofluorine surfactants used in the formulations of thousands of consumer goods. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system have been resulted in contaminated effluents and sewage sludge from wastewater treatment plants (WWTPs) which became an important pathway for PFAS into the environment. Because sewage sludge is often used as fertilizer its application on agricultural soils has been observed as significant input path for PFAS into our food chain. To produce high-quality phosphorus fertilizers for a circular economy from sewage sludge, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Normally, PFAS are analyzed using PFAS protocols typically with time-consuming extraction steps and LC-MS/MS target quantification. However, for screening of PFAS contaminations in wastewater-based fertilizers also the DGT technique can be used for the PFAS extraction. Afterwards, combustion ion chromatography (CIC) can be applied to analyze the “total” amount of PFAS on the DGT binding layer. The DGT method was less sensitive and only comparable to the extractable organic fluorine (EOF) method values of the fertilizers in samples with >150 µg/kg, because of different diffusion properties for various PFAS, but also kinetic exchange limitations. However, the DGT approach has the advantage that almost no sample preparation is necessary. Moreover, the PFAS adsorption on the DGT binding layer was investigated via surface sensitive spectroscopical methods, such as Fourier-transform infrared (FT-IR) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
DICONDE (Digital Imaging and Communication in Non-Destructive Testing) is an open international standard for storing and exchanging industrial test data and process-related information. The DICONDE standard defines both the semantics for structured storage of data and the network-based communication between two endpoints. This allows many test processes to be mapped digitally and securely, while at the same time meeting normative requirements such as traceability to the tester and test object and reproducibility of test results.
The amount of plant-available phosphorus (P) in soil strongly influences the yield of plants in agriculture. Therefore, various simple chemical extraction methods have been developed to estimate the plant-available P pools in soil. More recently, several experiments with the DGT technique have shown that it has a much better correlation to plant-available P in soils than standard chemical extraction methods (e.g. calcium-acetate-lactate (CAL), Colwell, Olsen, water) when soils with different characteristics are considered. However, the DGT technique cannot give information on the plant-available P species in the soil. Therefore, we combined DGT with solution 31P nuclear magnetic resonance (NMR) spectroscopy. This was achieved by using a modified DGT device in which the diffusive layer had a larger pore size, the binding layer incorporated an adsorption material with a higher capacity, and the device had a larger exposure area. The spectroscopic investigation was undertaken after elution of the deployed DGT binding layer in a NaOH solution. Adsorption tests using solutions of known organic P compounds showed that a sufficient amount of these compounds could be adsorbed on the binding layer in order for them to be analyzed by solution 31P NMR spectroscopy. Furthermore, various intermediates of the hydrolysis of trimetaphosphate in soil could be also analyzed over time.
O3BET Quality Protocols
(2023)
Presentation of the process-oriented approach for the development of the quality protocolls (standard operation procedures and work instructions) for the O3BETs. O3BETs are innovative testing facilities for building envelopes which are developed in the course of the Metabuilding Labs EU Horizon 2020 project.
X-ray refraction is analogous to visible light deflection by matter; it occurs at boundaries between different media. The main difference between visible light and X-rays is that in the latter case deflection angles are very small, from a few seconds to a few minutes of arc (i.e., the refraction index n is near to 1). Importantly, deflection of X-rays is also sensitive to the orientation of the object boundaries. These features make X-ray refraction techniques extremely suitable to a) detect defects such as pores and microcracks and quantify their densities in bulk (not too heavy) materials, and b) evaluate porosity and particle properties such as orientation, size, and spatial distribution (by mapping). While X-ray refraction techniques cannot in general image single defects, they can detect objects with size above a few wavelengths of the radiation.
Such techniques, especially at the Synchrotron BESSY II, Berlin, Germany, can be used in-situ, i.e. when the specimen is subjected to temperatures or external loads.
The use of X-ray refraction analysis yields quantitative information, which can be directly input in kinetics, mechanical and damage models.
We hereby show the application of non-destructive X-ray refraction radiography (SXRR, 2D mapping also called topography) to problems in additive manufacturing:
1) Porosity analysis in PBF-LM-Ti64. Through the use of SXRR, we could not only map the (very sparse) porosity distribution between the layers and quantify it, but also classify, and thereby separate, the filled porosity (unmolten powder) from the keyhole and gas pores (Figure 1).
2) In-situ heat treatment of laser powder bed fusion PBF-LM-AlSi10Mg to monitor microstructure and porosity evolution as a function of temperature (Figure 2). By means of SXRR we indirectly observed the initial eutectic Si network break down into larger particles as a function of increasing temperature. We also could detect the thermally induced porosity (TIP). Such changes in the Si-phase morphology upon heating is currently only possible using scanning electron microscopy, but with a much smaller field-of-view. SXRR also allows observing the growth of some individual pores, usually studied via X-ray computed tomography, but again on much smaller fields-of-view.
Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the defect distribution and the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Great complexity characterizes Additive Manufacturing (AM) of metallic components via laser powder bed fusion (PBF-LB/M). Due to this, defects in the printed components (like cracks and pores) are still common. Monitoring methods are commercially used, but the relationship between process data and defect formation is not well understood yet. Furthermore, defects and deformations might develop with a temporal delay to the laser energy input. The component’s actual quality is consequently only determinable after the finished process.
To overcome this drawback, thermographic in-situ testing is introduced. The defocused process laser is utilized for nondestructive testing performed layer by layer throughout the build process. The results of the defect detection via infrared cameras are shown for a research PBF-LB/M machine.
This creates the basis for a shift from in-situ monitoring towards in-situ testing during the AM process. Defects are detected immediately inside the process chamber, and the actual component quality is determined.
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.
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.
LIBS ConSort: Development of a sensor-based sorting method for constuction and demolition waste
(2023)
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. In construction and demolition waste (CDW) recycling, the preference to date has been to apply simple but proven techniques to process large quantities of construction rubble in a short time. This is in contrast to the increasingly complex composite materials and structures in the mineral building materials industry. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions. A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) with near-infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.) Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates. We present current advances and results about the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real-time classification of CDW on a conveyor belt.
Electromagnetic stirring is known to promote material flow, reduce porosity, uniform elements distribution, and refine grain in laser beam welding (LBW), which enhances the applicability of LBW in various industries. In this study, a phase-field model of dendrite growth in AA5754 Al alloy electromagnetic stirring laser beam welding was established. The model considered the thermal electromagnetic Lorentz force resulting from the interaction between the electric field generated by the Seebeck effect and the magnetic field, as well as the temperature gradient and solidification rate of the solidification interface obtained from the computational fluid dynamics electromagnetic stirring LBW model. The variation rules of dendrite growth with different magnetic parameters and effects are analyzed. Comprehensively, the magnetic field promotes the solidification rate, thus promoting interfacial instability and a large magnetic flux density leads to a faster interface instability. The solidification rate as well as the temperature gradient affect the growth rate, and the accelerated growth caused by the so lidification rate with a high frequency and a large magnetic flux density effectively inhibits the slow growth caused by the temperature gradient. The thermal electromagnetic Lorentz force is the main factor for the branch increment at low frequencies, while both thermal electromagnetic Lorentz force and temperature gradient in crease the number of branches at high frequencies. The calculated average branch numbers considering various factors in the stable stage under different magnetic parameters were consistent with the results of the scanning electron microscope tests.
Information about an existing structure can be collected at certain costs to evaluate the reliability and condition as realistically as necessary. This information can be relevant or irrelevant, true or biased, precise or imprecise. The incorporation of relevant and quality-assessed measured information into reliability reassessment offers the chance to extend remaining lifetimes and support decision making about optimal actions or maintenance strategies. This paper shows recent developments in a national research project that aims to produce a guideline on the NDT-based, structure-specific modification of partial safety factors. The general methodology, results from recalculations according to the Eurocodes and metrologically solvable testing tasks relevant in the recalculation of the concrete bridges are shown and compared with the non-destructive testing methods applicable to concrete bridges. A case study is used to demonstrate that as-built drawings, in this case of the positions of tendons and shear reinforcement, can be verified using the radar method.
High energy X-ray synchrotron diffraction is used to investigate the elastic anisotropy of the nickel-based superalloy IN718 produced by laser powder bed fusion (PBF-LB). This material is characterized by a columnar grain morphology with some crystallographic texture. The material is subjected to elastic loading to determine the diffraction elastic constants (DECs). Furthermore, the single-crystal elastic constants (SCEC) are refined from these experiments using different micromechanical models. The results show that each micromechanical model predicts a specific set of SCEC that well describes the elastic anisotropy of PBF-LB/IN718.
Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-A001 containing Polycyclic Aromatic Hydrocarbons (PAH) in olive oil. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto.
Hot Isostatic Pressing (HIP) is often introduced to tackle the porosity issue in additively manufactured (AM) materials. For instance, HIP post-processing is recommended to improve fatigue resistance of Laser powder bed fusion (PBF-LB) manufactured parts [1, 2]. Even though HIP cannot completely remove porosity, it significantly decreases the defect population and its average size below the critical threshold value leading to early crack initiation.
In the present study, in-situ investigation of HIP procedure of PBF-LB Ti-6Al-4V parts was carried out to gain further insights into the densification mechanism occurring during HIP. The in-situ observations at high pressure and high temperature are uniquely possible at the PSICHE beamline of the Soleil synchrotron (France), thanks to the Ultrafast Tomography on a Paris-Edinburgh Cell (UToPEC) and the combination of the fast phase-contrast tomography and energy-dispersive diffraction [3, 4]. A detailed methodology was developed to ensure that the correct pressure and temperature were maintained during the experiments.
The results allowed an estimation of the global dentification rate during HIP of PBF-LB Ti-Al-4V material, as well as a detailed quantitative characterization of the influence of pore size and shape on the densification process, thereby understanding the effectiveness of HIP process on different pore categories. After 20 mins, 75% of porosity can be considered as closed or has size below the resolution of the XCT reconstruction. We also observed that the smallest defects showed higher densification rate, while the defect shape did not have significant effect on such rate. The current development of in-situ HIP experiment allows experimental quantification and validation of the simulation work. Ultimately it paves the road to tailoring the HIP procedure for different materials depending on the porosity and microstructure.
The achievable spatial resolution of active thermographic testing is inherently limited by the diffusive nature of heat conduction in solids. This degradation of the achievable spatial resolution for a semi-infinite body acting on a defect signal can be approximated by spatial convolution with the Green’s function of the heat PDE. As the degradation in spatial resolution is dependent on the depth 𝐿, a common rule of thumb specifies that for proper detection, any defect should feature a spatial extension greater or equal to the depth it is located at. However, as the exact shape of a defect can have a large impact on its severity, at best a proper reconstruction of the defect shape should be performed, which therefore must also deal with the aforementioned adverse effects of heat conduction. One recent method to overcome the spatial resolution limit of thermographic testing is the photothermal super resolution reconstruction method. It is based on performing multiple active thermographic measurements on the same region of interest (ROI) with varying spatially structured heating and subsequent numerical reconstruction of the measured defect signals by solving a severely ill-posed inverse reconstruction problem relying on heavy regularization. By extending the experimental implementation of the method to make use of random-pixel patterns projected onto the ROI using a laser-coupled DLP-projector, defect reconstructions can now be performed within a reasonable time frame (~15 min per ROI) at high accuracy. Compared to conventional thermographic testing methods, the photothermal super resolution reconstruction stands out by resulting in a sparse representation of the defect structure of the ROI, making it especially well-suited to further automatic defect classification and quality assurance measures in an Industry 4.0 context.
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators. Combined with automated data correction pipelines, and our analysis and simulation software, this led to more than 40 papers in the last 5 years with just over 2 full-time staff members.
This year, our new, modular synthesis platform has made more than 1000 additional samples for us to analyse and catalogue. By virtue of the automation, the synthesis of these samples is automatically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases. Having developed these proof-of-concepts, we find that materials research itself is changed dramatically by automating dull tasks in a laboratory.
This talk is intended to spark ideas and collaborations by providing an overview of: 1) the current improvements in our scattering laboratory methodology, 2) introducing our open, modular robotic platform that is used for systematic sample preparation, and 3) demonstrating the data structure of the synthesis logs and measurements. Finally, the remaining bottlenecks and points of attention across all three are highlighted.
In this talk, the importance of metadata is underscored by real-world examples.
Metadata is essential to alleviating the reproducibility crises in science. This imples that a wide range of metadata must be collected, with a heavy emphasis on the automated collection of such metadata. This must subsequently be organized in an intelligible, archival structure, when possible with units and uncertainties.
Such metadata can aid in improving the usage efficiency of instrumentation, as is demonstrated on the MOUSE instrument. This metadata can now be used to connect the various aspects of the holistic experimental procedure to gain better insights on the materials structure.
A second example shows the extraction and organization of such metadata from an automated materials development platform, collected during the synthesis of 1200 samples. These metadata from the synthesis can then be linked to the results from the analysis of these samples, to find direct correlations between the synthesis parameters and the final structure of the materials.