Chemie und Prozesstechnik
Filtern
Erscheinungsjahr
- 2022 (456) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (163)
- Vortrag (149)
- Posterpräsentation (67)
- Beitrag zu einem Tagungsband (36)
- Forschungsbericht (15)
- Forschungsdatensatz (10)
- Sonstiges (5)
- Buchkapitel (3)
- Dissertation (2)
- Video (2)
- Zeitschriftenheft (Herausgeberschaft für das komplette Heft) (2)
- Preprint (2)
Sprache
- Englisch (456) (entfernen)
Schlagworte
- Digitalization (21)
- Certification (19)
- Conformity assessment (19)
- Fluorescence (19)
- Digital transformation (18)
- COVID-19 (17)
- Calibration (17)
- Conformity assessment body (17)
- Non-destructive testing (17)
- Quality infrastructure (17)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (165)
- 8 Zerstörungsfreie Prüfung (150)
- 6 Materialchemie (106)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (49)
- 1.1 Anorganische Spurenanalytik (44)
- 6.1 Oberflächen- und Dünnschichtanalyse (42)
- 8.5 Röntgenbildgebung (41)
- 6.3 Strukturanalytik (40)
- 1.2 Biophotonik (35)
- 8.4 Akustische und elektromagnetische Verfahren (32)
Paper des Monats
- ja (2)
The COVID-19 pandemic posed new and manifold challenges to organizations and their operations worldwide. Conformity assessment bodies (CABs), such as testing or medical laboratories, certification, and inspection bodies, were also affected by the associated disruptions. Their role in this crisis is highly relevant, as CABs are essential pillars of the quality infrastructure: their activities ensure that products and services meet requirements as defined in standards and regulations, thereby contributing to their safety and reliability. The question arises of how CABs and their operations were affected by the pandemic and how they responded. To this end, we present the results of an international survey of 986 CABs of all types in Germany, the UK, Italy, and New Zealand. Overall, CABs reported, on average, a reduction in demand for their services during the pandemic, facing restrictions in all countries. In addition, the pandemic had an overall negative impact on the CABs’ investment and innovation activities. However, investments in digital infrastructure were increased as a countermeasure, with CABs reporting a higher need for digitalization. The paper highlights and discusses results from in-depth analyses relevant to policymakers and industry alike.
Introduction of a monitoring system for Bingham fluids in additive manufacturing with concrete
(2022)
Freeform additive manufacturing of concrete structures is a rising technology in civil engineering with several fascinating advantages. Nonetheless, to ensure reliability and structural integrity, standards and quality control are required in the future to bring this technology into the market. As the concrete is manufactured continuously, continuous quality control of the printing process is also required, i.e. comprehensive process monitoring. At BAM, a test rig will be installed, enabling the printing of concrete structures with a maximum size of 2 m x 1 m x 1 m (l x w x h). Here, process monitoring is the focus of the test rig. In this study, we show the results of the first pump tests, including the measurement of several parameters such as temperature and pressure along the supply system, i.e. from the concrete pump to the printer head.
Introduction of a monitoring system for Bingham fluids in additive manufacturing with concrete
(2022)
Freeform additive manufacturing of concrete structures is a rising technology in civil engineering with several fascinating advantages. Nonetheless, to ensure reliability and structural integrity, standards and quality control are required in the future to bring this technology into the market. As the concrete is manufactured continuously, continuous quality control of the printing process is also required, i.e. comprehensive process monitoring. At BAM, a test rig will be installed, enabling the printing of concrete structures with a maximum size of 2 m x 1 m x 1 m (l x w x h). Here, process monitoring is the focus of the test rig. In this study, we show the results of the first pump tests, including the measurement of several parameters such as temperature and pressure along the supply system, i.e. from the concrete pump to the printer head.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in the Netherlands. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on Dutch CABs is part of a global project that covers various other countries (see www.qi-fokus.de).
The aim of this study was to identify specific truffle marker substances within the truffle aroma. The aroma profile of different truffle species was analyzed using static headspace sampling with gas chromatography mass spectrometry analysis (SHS/GC-MS). Possible marker substances were identified, taking the additional literature into account. The selected marker substances were tested in an experiment with 19 truffle dogs. The hypothesis “If trained truffle dogs recognize the substances as supposed truffles in the context of an experiment, they can be regarded as specific” was made. As it would be nearly impossible to investigate every other possible emitter of the same compounds to determine their specificity, this hypothesis was a reasonable approximation. We were interested in the question of what it is the dogs actually search for on a chemical level and whether we can link their ability to find truffles to one or more specific marker substances. The results of the dog experiment are not as unambiguous as could have been expected based on the SHS/GC-MS measurements. Presumably, the truffle aroma is mainly characterized and perceived by dogs by dimethyl sulfide and dimethyl disulfide. However, as dogs are living beings and not analytical instruments, it seems unavoidable that one must live with some degree of uncertainty regarding these results.
pH presents one of the most important analytes in the life and material sciences, indicating, e.g., diseases and corrosion processes. This includes the optical monitoring of pH in living cells for studying cellular internalization pathways, such as phagocytosis, endocytosis, and receptor mediated internalization with the aid of molecular and nanoscale fluorescent sensors. Nanoparticle (NP)-based sensors, that are labelled or stained with a multitude of sensor dyes, have several advantages as compared to conventional molecular probes like enhanced brightness, i.e., amplified signals, ease of designing ratiometric systems by combining analyte-sensitive and inert reference dyes, and increased photostability. Moreover, this can enable the use of hydrophobic dyes in aqueous environments. Versatile templates and carriers for the fabrication of nanosensors by staining and/or labelling with different fluorophores and sensor molecules are surface-functionalized particles like silica (SiO2) and polystyrene (PS) particles. Here we present a platform of blue-red-green fluorescent pH nanosensors for the measurement of acidic, neutral, and basic pH utilizing both types of matrices and two spectrally distinguishable sensor dyes with an integrated reference dye and demonstrate its applicability for cellular studies.
Mechanically stable structures with interconnected hierarchical porosity combine the benefits of both small
and large pores, such as high surface area, pore volume, and good mass transport capabilities. Hence, lightweight micro-/meso-/macroporous monoliths are prepared from ordered mesoporous silica COK-12 by means of spark plasma sintering (SPS, S-sintering) and compared to conventionally (C-) sintered monoliths. A multi-scale model is developed to fit the small angle X-ray scattering data and obtain information on the hexagonal lattice parameters, pore sizes from the macro to the micro range, as well as the dimensions of the silica population. For both sintering techniques, the overall mesoporosity, hexagonal pore ordering, and amorphous character are preserved. The monoliths' porosity (77–49%), mesopore size (6.2–5.2 nm), pore volume (0.50–0.22 g cm-3
), and specific surface area (451–180 m2 g-1) decrease with increasing processing temperature and pressure. While the difference in porosity is enhanced, the
structural parameters between the C-and S-sintered monoliths are largely converging at 900 C, except for the mesopore size and lattice parameter, whose dimensions are more extensively preserved in the
S-sintered monoliths, however, coming along with larger deviations from the theoretical lattice. Their higher mechanical properties (biaxial strength up to 49 MPa, 724 MPa HV 9.807 N) at comparable porosities and ability to withstand ultrasonic treatment and dead-end filtration up to 7 bar allow S-sintered monoliths to reach a high permeance (2634 L m-2 h-1 bar-1), permeability (1.25 x 10^-14 m2), and ability to reduce the chemical oxygen demand by 90% during filtration of a surfactant-stabilized oil in water emulsion, while indicating reasonable resistance towards fouling.
Avoiding the formation of defects such as keyhole pores is a major challenge for the production of metal parts by Laser Powder Bed Fusion (LPBF). The use of in-situ monitoring by thermographic cameras is a promising approach to detect defects, however the data is hard to analyze by conventional algorithms. Therefore, we investigate the use of Machine Learning (ML) in this study, as it is a suitable tool to model complex processes with many influencing factors. A ML model for defect prediction is created based on features extracted from process thermograms. The porosity information calculated from an x-ray Micro Computed Tomography (µCT) scan is used as reference. Physical characteristics of the keyhole pore formation are incorporated into the model to increase the prediction accuracy. Based on the prediction result, the quality of the input data is inferred and future demands on in-situ monitoring of LPBF processes are derived.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. 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) and visual (VIS)/ near-infrared (NIR) spectroscopy. 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-containing 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.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
In a joint project of partners from industry and research, the automated recycling of construction and demolition waste (CDW) is investigated and tested by combing laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy. 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.). The project focuses primarily on the Berlin site to analyze the entire value chain, minimize economic/technological barriers and obstacles at the cluster level, and sustainably increase recovery and recycling rates. First measurements with LIBS and NIR spectroscopy show promising results in distinguishing various material types and indicate the potential for a successful combination. In addition, X-ray fluorescence (XRF) spectroscopy is being performed to obtain more information about the quantitative elemental composition of the different building materials. Future work will apply the developed sorting methodology in a fully automated measurement setup with CDW on a conveyor belt.
This sequence of X-Ray images shows how one of the most common Italian moka pots actually work! The sequence starts with a completely prepared moka pot (water in the bottom part, coffee in the middle and hot plate on). During the process the water starts to boil and the steam pressure pushes the hot water through the coffee into the bassin at the top of the pot.
This video sequence and additional explanations can also be found on Wikipedia.
X-Ray computed tomography (XCT) scan of 11 individual metallic powder particles, made of (Mn,Fe)2(P,Si) alloy. The data set consists of 4 single XCT scans which have been stitched together [3] after reconstruction. The powder material is an (Mn,Fe)2(P,Si) alloy with an average density of 6.4 g/cm³. The particle size range is about 100 - 150 µm with equivalent pore diameters up to 75 µm. The powder and the metallic alloy are described in detail in [1, 2].
By means of laser thermography, surface defects, in particular surface breaking cracks, can be detected with high sensitivity. Basically, this requires a focused heat source (high-power laser), a thermographic camera and a relative movement between laser and test object, as well as a suitable evaluation algorithm to distinguish between surface defects and defect-free areas. In this paper we report on a method in which the relative motion is realised by a robot to fully inspect large and non-planar test objects such as rail sections, turbine blades, gears, etc. We show the influence of the excitation laser, which can be varied in terms of spot geometry, wavelength, and scan scheme, and we demonstrate our evaluation algorithms with the aim of automatically detecting surface defects.
In a joint project of partners from industry and research, the automated recycling of construction and demolition waste (CDW) is investigated and tested by combing laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy. 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.). The project focuses primarily on the Berlin site to analyze the entire value chain, minimize economic/technological barriers and obstacles at the cluster level, and sustainably increase recovery and recycling rates. First measurements with LIBS and NIR spectroscopy show promising results in distinguishing various material types and indicate the potential for a successful combination. In addition, X-ray fluorescence (XRF) spectroscopy is being performed to obtain more information about the quantitative elemental composition of the different building materials. Future work will apply the developed sorting methodology in a fully automated measurement setup with CDW on a conveyor belt.
Nebivolol (NEB), a β-blocker frequently used to treat cardiovascular diseases, has been widely detected in aquatic environments, and can be degraded under exposure to UV radiation, leading to the formation of certain transformation products (UV-TPs). Thus, the toxic effects of NEB and its UV-TPs on aquatic organisms are of great importance for aquatic ecosystems. In the present study, the degradation pathway of NEB under UV radiation was investigated. Subsequently, zebrafish embryos/larvae were used to assess the median lethal concentration (LC50) of NEB, and to clarify the sub-lethal effects of NEB and its UV-TPs for the first time. It was found that UV radiation could reduce the toxic effects of NEB on the early development of zebrafish. Transcriptomic analysis identified the top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in zebrafish larvae exposed to NEB, most of which were associated with the antioxidant, nervous, and immune systems. The number of differentially expressed genes (DEGs) in the pathways were reduced after UV radiation. Furthermore, the analysis of protein biomarkers, including CAT and GST (antioxidant response), AChE and ACh (neurotoxicity), CRP and LYS (immune response), revealed that NEB exposure reduced the activity of these biomarkers, whereas UV radiation could alleviate the effects. The present study provides initial insights into the mechanisms underlying toxic effects of NEB and the detoxification effects of UV radiation on the early development of zebrafish. It highlights the necessity of considering the toxicity of UV-TPs when evaluating the toxicity of emerging pollutants in aquatic systems.
Inflammatory bowel diseases (IBD) comprise mainly ulcerative colitis (UC) and Crohn´s disease (CD). Both forms present with a chronic inflammation of the (gastro) intestinal tract, which induces excessive changes in the composition of the associated extracellular matrix (ECM). In UC, the inflammation is limited to the colon, whereas it can occur throughout the entire gastrointestinal tract in CD. Tools for early diagnosis of IBD are still very limited and highly invasive and measures for standardized evaluation of structural changes are scarce. To investigate an efficient non-invasive way of diagnosing intestinal inflammation and early changes of the ECM, very small superparamagnetic iron oxide nanoparticles (VSOPs) in magnetic resonance imaging (MRI) were applied in two mouse models of experimental colitis: the dextran sulfate sodium (DSS)-induced colitis and the transfer model of colitis. For further validation of ECM changes and inflammation, tissue sections were analyzed by immunohistochemistry. For in depth ex-vivo investigation of VSOPs localization within the tissue, Europium-doped VSOPs served to visualize the contrast agent by imaging mass cytometry (IMC). VSOPs accumulation in the inflamed colon wall of DSS-induced colitis mice was visualized in T2* weighted MRI scans. Components of the ECM, especially the hyaluronic acid content, were found to influence VSOPs binding. Using IMC, colocalization of VSOPs with macrophages and endothelial cells in colon tissue was shown. In contrast to the DSS model, colonic inflammation could not be visualized with VSOP-enhanced MRI in transfer colitis. VSOPs present a potential contrast agent for contrast-enhanced MRI to detect intestinal inflammation in mice at an early stage and in a less invasive manner depending on hyaluronic acid content.
Ultrasonic measurement technology has become indispensable in NDT-CE. Air-coupled ultrasonic (ACU) measurement techniques promise to reduce measurement time. However, the signal quality suffers from large specific impedance mismatch at the transducer-air and air-specimen interface. Additionally, large pressure amplitudes are necessary for the penetration depth required in NDT-CE applications. To address the specific requirements of ultrasonic testing in NDT-CE, a robust ACU transducer was developed, that generates ultrasound by quickly switching a pressurized air flow. The simple design of the fluidic transducer makes the device maintenance free and resilient against harsh environmental conditions. Since the signal is generated by aeroacoustics, there is no specific impedance mismatch between the transducer and the surrounding air. The ultrasonic signal exhibits frequencies in the 30-60 kHz range and is therefore well suited to penetrate heterogenous materials such as concrete. This contribution gives an introduction in the working principle and signal characteristics of the fluidic transducer. Its applicability to measurements in concrete is verified. A detailed outlook is given to discuss the future potential of fluidic ultrasonic actuators.
Materials are key for our modern communities; current life seems nearly impossible without concrete, plastic and metal. In particular metals play important roles in all areas of our daily life - from building materials to high tech products.
However, due to the increasing consumption of metals and corresponding waste production, an elevated release of metals from buildings and consumer goods into the environment takes place. Furthermore, metals in direct contact with the environment undergo corrosion processes which leads also to a release of metals into the (aquatic) environment. Besides this immediate metal release, the lifespan of products/buildings are substantially reduced – hence unnecessary economic costs arise. Thus, research in this regard is needed within the force field of metal/material environment.
However, to evaluate the environmental impact of materials as well as developing “safe” materials, new analytical methods are highly needed. One promising powerful tool in this regard is single cell-ICP-ToF-MS for multi-elemental analysis on a single cell/organism level.
Within this presentation the concept, strength as well as challenge of single cell-ICP-MS are briefly introduced. Afterwards, two application examples are presented: (i) assessing the environmental impact of metals and (ii) the impact of the environment on metal-based materials and the derivation of potential environmental-friendly material protection strategies. These applications highlight the strength of new analytical approaches to explore the durability and safety of newly developed materials. Thus, analytical chemistry is one corner stone to transformation of modern society into circular economy (CEco).
(i) Diatoms are located at the bottom of the food chain. Thus, toxicological relevant metals taken up by diatoms can possibly accumulate within the food web and cause harmful effects. Diatoms are a common test system in ecotoxicology. To investigate potential metal uptake and harmful effects on a single cell level, we developed an on-line single cell-ICP-ToF-MS approach for multi-elemental diatom analysis. Our approach is a new potential tool in ecotoxicological testing for metal-based materials.
(ii) Next to classical corrosion processes, microorganisms are responsible for so called microbially influenced corrosion (MIC). MIC is a highly unpredictable process relying on the interaction pathways between cells and the metal surface. To shed light on MIC processes and derivate potential metal protection strategies, we applied single cell-ICP-ToF-MS for MIC research on a single bacteria/archaea level. It turned out that microorganism are taking up particular metals from alloys - thus, single bacteria-ICP-ToF-MS will enable the development of environmental friendly corrosion protection strategies.
Several countries, which use or used nuclear power, started to destruct nuclear power plants. Thus, large amounts of radioactive waste have to be stored safely during the next decades. Large underground caverns will
be used a nuclear waste disposal. Once the cavern is full, a sealing construction is required. The sealing should avoid the contact to any fluids or substances of the storage barrels and reduce hazardous radiation.
Ultrasonic measurement technology has become indispensable in NDT-CE. Air-coupled ultrasonic (ACU) measurement techniques promise to reduce measurement time. However, the signal quality suffers from large specific impedance mismatch at the transducer-air and air-specimen interface. Additionally, large pressure amplitudes are necessary for the penetration depth required in NDT-CE applications.
To address the specific requirements of ultrasonic testing in NDT-CE, a robust ACU transducer was developed, that generates ultrasound by quickly switching a pressurized air flow. The simple design of the fluidic transducer makes the device maintenance free and resilient against harsh environmental conditions. Since the signal is generated by aeroacoustics, there is no specific impedance mismatch between the transducer and the surrounding air. The ultrasonic signal exhibits frequencies in the 30-60 kHz range and is therefore well suited to penetrate heterogenous materials such as concrete. This contribution gives an introduction in the working principle and signal characteristics of the fluidic transducer. A detailed outlook is given to discuss the future potential of fluidic ultrasonic actuators.
In non-destructive testing and structural health monitoring, ultrasonic guided waves (UGWs) are of great interest for finding and characterizing structural flaws. The interaction of the waves with the flaws can often not be described analytically due to waves’ complexity. This makes numerical simulations and experiments indispensable. However, mentioned field of research is still relatively young and most of the methods focus on flaw localization, using time of flight of the reflected signal. This leaves many possibilities for further research, especially when it comes to separate analysis of different propagating modes.
It is well-known that ultrasonic wave modes convert when interacting with flaws. When a fundamental mode (A0 or S0) encounters a notch, it interacts and converts to another fundamental mode. In this contribution, this effect is used to analyze the depth of a notch. Firstly, numerical simulations are presented, which show notch depth proportionality to amplitude ratio of fundamental modes. To validate these results, experiments were carried out on a metal plate with a shallow notch which was gradually deepened. UGWs were excited using a polymer-based interdigital transducer (IDT) and detected with a 3D laser Doppler vibrometer. The IDT is employed to ensure excitation of a single mode and thus to reduce the complexity of the analysis. Good agreement between numerical and experimental results has been found. The results show the potential of UGWs not only for defect reconstruction and localization, but also its precise sizing.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Latvia. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on Latvian CABs is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Ireland. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on Irish CABs is part of a global project that covers various other countries (see www.qi-fokus.de).
Rapid, cost-efficient, and eco-friendly methods are desired today for routine analysis of the Fusarium mycotoxin zearalenone (ZEN) in edible vegetable oils. Liquid chromatography with fluorescence detection (HPLC-FLD) is commonly used to reliably control the specified ZEN maximum levels, which requires efficient sample clean-up to avoid matrix interferences. Therefore, a highly selective extraction and clean-up method based on reversible covalent hydrazine chemistry (RCHC) using hydrazine-functionalized silica was developed. This efficient solid-phase extraction (SPE) involves reversible hydrazone formation of ZEN with the hydrazine moiety covalently bound to a solid phase. Optimal conditions were achieved with 1 mL SPE cartridges filled with 400 mg of hydrazine-functionalized silica. The developed RCHC-SPE method was validated in an interlaboratory comparison study (ILC) with twelve participants analyzing six edible vegetable oils with a focus on maize oils. The derived method parameters (ZEN recovery 83%, repeatability 7.0%, and reproducibility 18%) meet the performance criteria of Commission Regulation (EC) No 401/2006. The developed RCHC-SPE-based HPLC-FLD method allows the reliable quantification of ZEN in the range of 47–494 μg/kg for different types of edible vegetable oils, also for matrix-reach native oils. Due to the high efficiency, the significantly reduced matrix load helps to extend the lifetime of analytical equipment. Furthermore, the re-useability of the RCHC-SPE cartridges contributes to an eco-friendly approach and reduced analysis costs. To our knowledge, this is the first report on ZEN quantification in edible vegetable oils based on manual RCHC-SPE cartridges. Due to its high performance, the developed RCHC-SPE method is a promising alternative to the current European standard method EN 16924:2017 (HPLC-FLD part).
NaYF4:Yb3+/Tm3+@NaGdF4:Nd3+/Yb3+ upconversion nanoparticles (UCNPs) were prepared using a solvothermal method, and the effects of key factors such as the content of sensitiser Nd 3+ and Yb3+ on their luminescence properties were investigated. The nanoparticles are homogeneous in size and well dispersed. Under 808 nm excitation, it can produce strong upconversion fluorescence. At the same time, the nanoparticles have good temperature-sensing properties at the thermally coupled energy levels of 700 nm and 646 nm for Tm3+. Using its fluorescence intensity ratio (FIR), accurate temperature measurements can be performed, and it has been found that it exhibits different temperature sensing properties in low and high-temperature regions. The maximum relative sensitivity was found to be 0.88% K-1 and 1.89% K-1 for the lowtemperature region of 285 K-345 K and the high-temperature region of 345 K-495 K. The nanoparticles were applied to the internal temperature measurement of lithium batteries and the actual high-temperature environment, respectively, and were found to have good temperature measurementt performance.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2022)
Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging.
A new “green” and mild synthesis of highly stable microcrystalline Cs2AgxNa1-xBiyIn1-yCl6 (CANBIC) perovskites under ambient conditions was developed that is scalable to the multi-gram production. Under UV illumination, the CANBIC perovskites emit intense broadband photoluminescence (PL) with a quantum yield (QY) of 92% observed for x = 0.35 and y = 0.01-0.02. The combination of strong UV absorbance and broadband visible emission, high PL QY, and long PL lifetimes of up to 1.4 μs, along with an outstanding stability makes these CANBICs a promising material class for many optical applications.
For test laboratories operating under accreditation schemes like ISO/IEC 17025 (ISO/IEC 17025), as the international reference for testing and calibration laboratories wanting to demonstrate their capacity to deliver reliable results, a periodical control of the critical instrumental parameters of an Energy-Dispersive X-ray Spectrometer (EDS) is required.
This periodical check of an EDS is specified with exact procedures and materials in the ISO 15632:2021 ”Microbeam Analysis – Selected instrumental performance parameters for the specification and checking of energy-dispersive X-ray spectrometers for use in electron probe microanalysis” (ISO 15632). The EDS check can be simplified to the acquisition of only one 10 kV spectrum from a dedicated test material, EDS-TM002, which is made available by BAM since 2009 (https://webshop.bam.de/webshop_en/). The optional BAM software “EDX spectrometer check” is destined to automatically evaluate this spectrum and determine the performance of the EDS in terms of energy resolution and calibration, as well as possible alteration of low-energy efficiency due to detector contamination. Nearly 200 laboratories have the EDS-TM and associated software package in use.
Practical examples based on various types of artifacts occurred in the EDS spectra and a long-term (>10 years) meticulous observation of the own spectrometers will be discussed. Different types of EDS spectrometers are considered, e.g. Si(Li) and SDD, of various window types (AP, the recent one Si3N4 or even windowless), and with different front contact layers (Au and Ni) (Hodoroaba and Procop, 2014). Evaluation of other parameters or effects such as the deadtime at different count rates or pileup effects is also explained with examples.
This study presents a practical procedure to give access to more information by tilting the sample holder and hence allowing images of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, extended information on surface roughness of the particle can be extracted. Thus, instead of obtaining 2D information from a single SEM image, three-dimensional (3D) information is obtained from 2D projections recorded at different particle orientations.
Lithium and boron are trace components of magmas, released during exsolution of a gas phase during volcanic activity. In this study, we determine the difusivity and isotopic fractionation of Li and B in hydrous silicate melts. Two glasses were synthesized with the same rhyolitic composition (4.2 wt% water), having diferent Li and B contents; these were studied in difusion-couple experiments that were performed using an internally heated pressure vessel, operated at 300 MPa in the temperature range 700–1250 °C for durations from 0 s to 24 h. From this we determined activation energies for Li and B difusion of 57±4 kJ/mol and 152±15 kJ/mol with pre-exponential factors of 1.53 × 10–7 m2/s and 3.80× 10–8 m2 /s, respectively. Lithium isotopic fractionation during difusion gave β values between 0.15 and 0.20, whereas B showed no clear isotopic fractionation. Our Li difusivities and isotopic fractionation results difer somewhat from earlier published values, but overall confrm that Li difusivity increases with water content. Our results on B difusion show that similarly to Li, B mobility increases in the presence of water. By applying the Eyring relation, we confrm that B difusivity is limited by viscous fow in silicate melts. Our results on Li and B difusion present a new tool for understanding degassing-related processes, ofering a potential geospeedometer to measure volcanic ascent rates.
Heterogeneous Oxysulfide@Fluoride Core/ Shell Nanocrystals for Upconversion-Based Nanothermometry
(2022)
Lanthanide (Ln3+)-doped upconversion nanoparticles (UCNPs) often suffer from weak luminescence, especially when their sizes are ultrasmall (less than 10 nm). Enhancing the upconversion luminescence (UCL) efficiency of ultrasmall UCNPs has remained a challenge that must be undertaken if any practical applications are to be envisaged. Herein, we present a Ln3+-doped oxysulfide@fluoride core/shell heterostructure which shows efficient UCL properties under 980nm excitation and good stability in solution. Through epitaxial heterogeneous growth, a ∼4 nm optically inert β-NaYF4 shell was coated onto ∼5 nm ultrasmall Gd2O2S:20%Yb,1%Tm. These Gd2O2S:20%Yb,1%Tm@NaYF4 core/shell UCNPs exhibit a more than 800-fold increase in UCL intensity compared to the unprotected core, a 180-fold increase in luminescence decay time of the 3H4 → 3H6 Tm3+ transition from 5 to 900 μs, and an upconversion quantum yield (UCQY) of 0.76% at an excitation power density of 155 W/cm2. Likewise, Gd2O2S:20%Yb,2%Er@NaYF4 core/shell UCNPs show a nearly 5000-fold
increase of their UCL intensity compared to the Gd2O2S:20%Yb,2%Er core and a maximum UCQY of 0.61%. In the Yb/Er core−shell UCNP system, the observed variation of luminescence intensity ratio seems to originate from a change in lattice strain as the temperature is elevated. For nanothermometry applications, the thermal sensitivities based on thermally coupled levels are estimated for both Yb/Tm and Yb/Er doped Gd2O2S@NaYF4 core/shell UCNPs.
The ability of industrial X-ray computed tomography (CT) to scan an object with several internal and external features at once causes increasing adoption in dimensional metrology. In order to evaluate the quality of a measurement value, the task-specific measurement uncertainty has to be determined. Currently, VDI/VDE 2630 part 2.1 gives a guideline to determine the uncertainty of CT measurements experimentally by conducting repeated measurements. This is costly and time-consuming. Thus, the aim is to determine the task-specific measurement uncertainty numerically by simulations (e. g. according to the guide to expression of uncertainty in measurement (GUM) Supplement 1). To achieve that, a digital twin is necessary. This contribution presents a simple first approach how a digital twin can be built. In order to evaluate this approach, a study comparing measurements and simulations of different real CT systems was carried out by determining the differences between the measurement results of the digital twin and of the measurement results of the real-world CT systems. The results have shown a moderate agreement between real and simulated data. To improve on this aspect, a standardized method to characterize CT systems and methods to implement CT parameters into the simulation with sufficient accuracy will be developed.
The residual stresses and load transfer in multiphase metal alloys and their composites (with both random planar-oriented short fibers and particles) will be shown, as studied by neutron diffraction, by X-ray computed tomography, and by a model based on the reformulation of classic Maxwell’s homogenization method.
Contrary to common understanding and state-of-the-art models, we experimentally observe that randomly oriented phases possess non-hydrostatic residual stress. Moreover, we disclose that the unreinforced matrix alloy stays under hydrostatic compression even under external uniaxial compression.
The recently developed modeling approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses accounting for the interaction of random oriented phases with fibers having preferential orientation. It also allows the explanation of the unconventional in-situ behavior of the unreinforced alloy and the prediction of the micromechanical behavior of other similar alloys.
The availability of non-destructive methods is particularly important for composites, e.g., carbon or glass fiber-reinforced polymers because their properties strongly depend on the manufacturing process and in-service conditions. Composites are mostly used in thin-walled components which are perfectly suited for the characterisation with ultrasonic guided waves (UGWs).
In this contribution, we demonstrate sensitivities of UGW to different elastic constants of a composite material. Then we present a characterisation procedure which can be used to in-fer elastic properties. Our approach is based on an inverse procedure in which the numeri-cally calculated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite various UGW modes and a 3D laser Doppler vibrometer (3D LDV) to record them. Compared to the approaches based on laser excitation, the PZT provides a better signal-to-noise ratio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows cap-turing in-plane and out-of-plane components giving more dispersion information for a better characterisation. Since the inverse procedure requires many iterations before elastic prop-erties are retrieved, an efficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement be-tween theoretical and experimental curves is demonstrated.
The residual stresses and load transfer in multiphase metal alloys and their composites (with both random planar-oriented short fibers and particles) will be shown, as studied by neutron diffraction, by X-ray computed tomography, and by a model based on the reformulation of classic Maxwell’s homogenization method.
Contrary to common understanding and state-of-the-art models, we experimentally observe that randomly oriented phases possess non-hydrostatic residual stress. Moreover, we disclose that the unreinforced matrix alloy stays under hydrostatic compression even under external uniaxial compression.
The recently developed modeling approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses accounting for the interaction of random oriented phases with fibers having preferential orientation. It also allows the explanation of the unconventional in-situ behavior of the unreinforced alloy and the prediction of the micromechanical behavior of other similar alloys.
The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability and impact on probability of detection (POD).
This paper quantitatively describes two different methods to compensate the temperature effect, namely the optimal baseline selection (OBS) and the baseline signal stretch (BSS) extending their application to the case of a distributed sensor networks (DSN). This latter introduces a number of possible data to explore compensation strategies which do not necessarily returns univocal results. Hence, a decision framework is needed, which takes into consideration multiple ultrasonic time traces with different arrival times and amplitude. In detail, the effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and a frequent value warning is introduced to find the more probable temperature with increasing reliability of the assessment. The same procedure is applied using the BSS algorithm. Finally, the use of both approaches is introduced, comparing the capability of the mixed algorithm to correctly sort temperature information from OBS and then apply the BSS combining the frequent value warning to have a unique correction all over the DSN.
Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combinations of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS and BSS approaches making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions. In addition, the possibility to combine BSS approached also demonstrates that the use of compensation strategies improves detectability and localization of damage even in a DSN. This result can be used to improve the SHM system reliability, with promising perspectives in increasing POD.
While there is a extensive literature on the micro-mechanical behavior of metal matrix composites (MMCs) under uniaxial applied stress, very little is available on multi-phase MMCs. In order to cast light on the reinforcement and damage processes in such multi-phase composites, an Al alloy with one and two ceramic reinforcements (planar-random oriented alumina fibers and SiC particles) were studied. In-situ compression tests during neutron diffraction experiments were used to track the load transfer among phases, while X-ray computed tomography was used to investigate pre-strained samples, in order to monitor and quantify damage. We found that damage progresses differently in composites with different orientations of the fiber mat. Because of the presence of the intermetallic network, it was observed that the second ceramic reinforcement changes the load transfer scenario only at very high applied load, when also intermetallic particles break. We rationalized the experimental results by means of a micromechanical model based on Maxwell’s homogenization scheme, and we could explain why no damage is observed in the ductile matrix under compression: the matrix finds itself in hydrostatic compression, and the Poisson’s tensile strain is totally carried by the reinforcement phases
Global Status and Trends in Digital Transformation and Conformity Assessment – The Case of Germany
(2022)
This presentation summarizes findings from the first comprehensive study on digitalization in conformity assessment worldwide. The reults are based on data from a survey among conformity assessment bodies (CABs) in Germany conducted in 2022, as well as some first insights from Latin American countries. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on CABs is part of a global project that covers various countries (see www.qi-fokus.de).
Ultrasonic probes for high-temperature applications are provided with metallic wedges, which can withstand the contact with the high temperature of the inspected structure. The ultrasonic signal travels within the wedge and gets reflected from its boundaries, causing interference signals called “ghost echoes”. The current work presents an investigation of the additional damping effect provided by porous sintered metal plates applied onto the surface of the wedge. In particular, the study evaluates the effect of damping plate thickness on the interference signal level at different transmission frequencies. Damping plates made of sintered metal SIKA-R 15 AX were attached to a wedge prototype made of steel 1.4301. The study revealed, that the most effective thickness of damping plates in the selected frequency interval of 1 to 4 MHz is equal to 4 mm. The evaluation of the interference signal has shown that the application of such damping plates to the wedge surface contributes to an additional attenuation of an interference signal of 10 to 30 dB after 500 μs of signal propagation.
In this work, we report on a method for automatic inspection of components using laser scanning thermography, in which the relative motion is performed by a robot to fully inspect complex test objects such as turbine blades. We demonstrate our evaluation algorithms with the aim of automatically detecting surface defects on calibrated specimens. We show the influence of the excitation laser, which can be varied in terms of spot geometry, wavelength, and scan scheme. Additionally, we show some advantages, versatility, and current challenges of using a programmed robot for non-destructive evaluation in thermography.
Analysis of electrochemical and liver microsomal transformation products of lasalocid by LC/HRMS
(2022)
Rationale: Lasalocid (LAS), an ionophore, is used in cattle and poultry farming as feed additive for its antibiotic and growth-promoting properties. Literature on transformation products (TP) resulting from LAS degradation is limited. So far, only hydroxylation is found to occur as the metabolic reaction during the LAS degradation. To investigate potential TPs of LAS, we used electrochemistry (EC) and liver microsome (LM) assays to synthesize TPs, which were identified using liquid chromatography high-resolution mass spectrometry (LC/HRMS).
Methods: Electrochemically produced TPs were analyzed online by direct coupling of the electrochemical cell to the electrospray ionization (ESI) source of a Sciex Triple-TOF high resolution mass spectrometer. Then, EC-treated LAS solution was collected and analyzed offline using LC/HRMS to confirm stable TPs and improve their annotation with a chemical structure due to informative MS/MS spectra. In a complementary approach, TPs formed by rat and human microsomal incubation were investigated using LC/HRMS. The resulting data were used to investigate LAS modification reactions and elucidate the chemical structure of obtained TPs.
Results: The online measurements identified a broad variety of TPs, resulting from modification reactions like (de-)hydrogenation, hydration, methylation, oxidation as well as adduct formation with methanol. We consistently observed different ion complexations of LAS and LAS-TPs (Na+; 2Na+ K+; NaNH4 +; KNH4 +). Two stable methylated EC-TPs were found, structurally annotated, and assigned to a likely modification reaction. Using LM incubation, seven TPs were formed, mostly by oxidation/hydroxylation. After the identification of LM-TPs as Na+-complexes, we identified LM-TPs as K+-complexes.
Conclusion: We identified and characterized TPs of LAS using EC- and LM-based methods. Moreover, we found different ion complexes of LAS-based TPs. This knowledge, especially the different ion complexes, may help elucidate the metabolic and environmental degradation pathways of LAS.
Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims at qualitatively and quantitatively evaluating images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.
CS particles show unique properties by merging individual characteristics of the core and the shell materials. An alteration particularly in their surface roughness affects the final performance of the particles in the targeted application. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task employing microscopic techniques being scarce and showing large differences in terms of methodology and results.
In our previous work, we have reported a systematic study with a reliable analysis tool, which evaluates profile roughness quantitatively, for individual core-shell microparticles using electron microscopy (EM) images of both types, Scanning Electron Microscopy (SEM) and transmission mode SEM (or TSEM). The SEM images contain two-dimensional (2D) information, therefore, provide profile roughness data only from the projection in the horizontal plane (in other words, from the “belly”) of a spherical particle. The present study offers a practical procedure to give access to more information by tilting the sample holder and hence allowing images of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, extended information on surface roughness of the particle can be extracted. Thus, instead of obtaining 2D information from a single SEM image, three-dimensional (3D) information is obtained from 2D projections recorded at different particle orientations.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Italy. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
The study on Italian CABs is part of a global project that covers various other countries (see www.qi-fokus.de).
Photothermal characterization of polyester composites loaded with parallelly arranged graphite rods
(2022)
One of the biggest challenges in the measurement of thermal properties is to measure inhomogeneous materials This work focuses on measuring the thermal properties of cylindrical polyester resin composite materials loaded with graphite rods oriented in the direction of the resin thickness, varying the graphite concentrations starting from zero to 8 75 of volumetric fraction and changing the distribution of graphite rods inside the polyester matrix.
A first tricolor fluorescent pH nanosensor is presented, which was rationally designed from biocompatible carboxylated polystyrene nanoparticles and two analyte-responsive molecular fluorophores. Its fabrication involved particle staining with a blue-red-emissive dyad, consisting of a rhodamine moiety responsive to acidic pH values and a pH-inert quinoline fluorophore, followed by the covalent attachment of a fluorescein dye to the particle surface that signals neutral and basic pH values with a green fluorescence. These sensor particles change their fluorescence from blue to red and green, depending on the pH and excitation wavelength, and enable ratiometric pH measurements in the pH range of 3.0−9.0. The localization of the different sensor dyes in the particle core and at the particle surface was confirmed with fluorescence microscopy utilizing analogously prepared polystyrene microparticles. To show the application potential of these polystyrene-based multicolor sensor particles, fluorescence microscopy studies with a human A549 cell line were performed, which revealed the cellular uptake of the pH nanosensor and the differently colored emissions in different cell organelles, that is, compartments of the endosomal-lysosomal pathway. Our results demonstrate the underexplored potential of biocompatible polystyrene particles for multicolor and multianalyte sensing and bioimaging utilizing hydrophobic and/or hydrophilic stimuli-responsive luminophores.
A fluorolytic sol–gel method was used for the fast and simple synthesis of small cubic-phase SrF2:Yb3+, Er3+ upconversion (UC) nanocrystals (UCNC) of different composition at room temperature. Systematic studies of the crystal phase and particle size of this Yb3+,Er3+-concentration series as well as excitation power density (P)-dependent UC luminescence (UCL) spectra, UCL quantum yields (ΦUCL), and UCL decay kinetics yielded maximum UCL performance for doping amounts of Yb3+ of 13.5% and Er3+ of 1.3% in the studied doping and P-range (30–400 W cm−2). Furthermore, ΦUCL were determined to be similar to popular β-NaYF4:Yb3+,Er3+. The relative spectral UCL distributions revealed that all UCNC show a strong red emission in the studied doping and P-range (30–400 W cm−2) and suggest that the UCL quenching pathway for unshelled cubic-phase SrF2:Yb3+,Er3+ UCNC differs from the commonly accepted population and depopulation pathways of β-NaYF4:Yb3+,Er3+ UCNC. In SrF2:Yb3+,Er3+ UCNC the 4S3/2 →
4I13/2 transition exhibits a notably stronger sensitivity towards P and reveals increasing values for decreasing Yb3+–Yb3+ distances while the 4I9/2 → 4I15/2 transition is significantly less affected by P and energy migration facilitated UCL quenching. These results emphasize the complexity of the UC processes and the decisive role of the crystal phase and symmetry of the host lattice on the operative UCL quenching mechanism in addition to surface effects. Moreover, the room temperature UCNC synthesis enabled a systematic investigation of the influence of the calcination temperature on the crystal phase of powder-UCNC and the associated UCL properties. Calcination studies of solid UCNC of optimized doping concentration in the temperature range of 175 °C and 800 °C showed the beneficial influence of temperature-
induced healing of crystal defects on UCL and the onset of a phase separation connected with the oxygenation of the lanthanide ions at elevated temperature. This further emphasizes the sensitivity of the UC process to the crystal phase and quality of the host matrix.
Li-rich nanoparticles of Li1+xMn2–xO4 doped with Al, Co, or Ni are successfully synthesized using a facile, fast, and efficient microwave-assisted hydrothermal route. Synchrotron X-ray diffraction confirms the formation of the crystalline cubic spinel phase type. X-ray absorption spectroscopy analysis at the Co and Ni K- and L-edges verifies that the dopants are within the Li1+xMn2–xO4 spinel structure and are inactive during cycling in the bulk and at the surface. Moreover, we demonstrate that nanocrystallinity and cationic doping play an important role in improving the electrochemical performance with respect to LiMn2O4 microparticles. They significantly reduce the charge-transfer resistance, lower the first cycle irreversible capacity loss to 6%, and achieve a capacity retention between 85 and 90% after 380 cycles, with excellent Coulombic efficiency close to 99% without compromising the specific charge at a 5C cycling rate. Furthermore, the Mn K- and L-edges attest that after long cycling, the Mn oxidation state in the bulk differs from that at the surface caused by the Mn disproportion reaction; however, the cationic doping helps mitigate the Mn dissolution with respect to the undoped Li1+xMn2–xO4 nanoparticles, as indicated by inductively coupled plasma atomic emission spectrometry.
Fluid inclusion microthermometry is one of the analytical approaches that has been proposed for speleothem-based temperature reconstructions. The proxy of this paleothermometer is the density of drip water relicts that have been enclosed in microscopic fluid inclusions during speleothem growth. Prior to microthermometric analyses, the monophase liquid inclusions need to be transferred from a metastable liquid into a stable liquid-vapour two-phase state by stimulating vapour bubble nucleation by means of single ultra-short laser pulses. Subsequent microthermometric analyses determine the temperature at which the vapour bubble disappears again, the so-called liquid-vapour homogenisation temperature (Th(obs) ). The observed homogenisation temperature depends not only on the water density but also on the inclusion volume. In order to determine the water density, a thermodynamic model is used that takes account of the effect of surface tension on Th(obs) to calculate Th∞. This is the corresponding homogenisation temperature at saturation pressure that determines the water density and defines the formation temperature of the fluid inclusion. The analytical precision of the method ranges between 0.1 and 0.3 °C depending on the size of the inclusions.
Validation of a fast and traceable radiographic scale calibration of dimensional computed tomography
(2022)
A fast and highly precise method of determining the geometrical scale factor of computed tomography (CT) measurements has been validated successfully by Bundesanstalt für Materialforschung und -prüfung (BAM), the Federal Institute of Metrology (METAS) and Physikalisch-Technische Bundesanstalt (PTB) within the scope of AdvanCT (Advanced Computed Tomography for dimensional and surface measurements in industry), a project funded in the European Metrology Programme for Innovation and Research (EMPIR). The method has been developed by PTB and requires only two radiographic images of a calibrated thin 2D standard (hole grid standard) from two opposite directions. The mean grid distance is determined from both radiographs. From this and with the help of the calibration result, the radiographic scale and therefore the voxel size is determined. The procedure takes only a few minutes and avoids a time-consuming CT scan. To validate the method, the voxel sizes determined via this method were compared with voxel sizes determined from CT scans of calibrated objects. Relative deviations between the voxel sizes in the range of 10−5 were
achieved with minimal effort using cone-beam CT systems at moderate magnifications.
Methodologies for model parameterization of virtual CTs for measurement uncertainty estimation
(2022)
X-ray computed tomography (XCT) is a fast-growing technology for dimensional measurements in industrial applications. However, traceable and efficient methods to determine measurement uncertainties are not available. Guidelines like the VDI/VDE 2630 Part 2.1 suggest at least 20 repetitions of a specific measurement task, which is not feasible for industrial standards. Simulation-based approaches to determine task specific measurement uncertainties are promising, but require closely adjusted model parameters and an integration of error sources like geometrical deviations during a measurement. Unfortunately, the development of an automated process to parameterize and integrate geometrical deviations into XCT models is still an open issue. In this work, the whole processing chain of dimensional XCT measurements is taken into account with focus on the issues and requirements to determine suitable parameters of geometrical deviations. Starting off with baseline simulations of different XCT systems, two approaches are investigated to determine and integrate geometrical deviations of reference measurements. The first approach tries to iteratively estimate geometric deviation parameter values to match the characteristics of the missing error sources. The second approach estimates those values based on radiographs of a known calibrated reference object. In contrast to prior work both approaches only use a condensed set of parameters to map geometric deviations. In case of the iterative approach, some major issues regarding unhandled directional dependencies have been identified and discussed. Whereas the radiographic method resulted in task specific expanded measurements uncertainties below one micrometre even for bi-directional features, which is a step closer towards a true digital twin for uncertainty estimations in dimensional XCT.
i-TRIBOMAT will provide the world's first Open Innovation Test Bed dedicated to analysing and simulating materials in tribological systems. In order to make necessary results of tribological tests comparable, harmonised ways to produce data are mandatory. Many sources influence the outcome of a Tribological test. Different approaches of institutes were evaluated in best practices via quality management tools minimising the impact on results.
Probe diagnostics is used to determine the electron temperature and electron number density in a low pressure inductively coupled plasma (ICP) ignited in the mixture of SiF4, Ar and H2. Emission spectra of mixtures with different stoichiometry of components are investigated and the electron density distribution function (EDDF) is estimated. The optimal conditions for high conversion of SiF4 into Si are found by studying the dependence of the yield of silicon upon the ratio of reagents. The maximum achieved yield of silicon is 85% under the optimal conditions. Based on the analysis of IR and MS spectra of exhaust gases, 5% of initial SiF4 converts into volatile fluorosilanes. A rate of production of Si is 0.9 g/h at the energy consumption 0.56 kWh /g.
Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is increasingly used to study the distribution of metal-containing drugs, imaging probes and nanomaterials in connection with disease related changes and therapy progress. Additionally, biomolecules can be detected indirectly by using metal-tagged antibodies.
The extracellular matrix (ECM) is, besides the cells, an important component of all body tissues. The macromolecular network of the ECM consists of structural proteins (e.g., collagen, elastin) and proteoglycans composed of highly negatively charged carbohydrates, the glycosaminoglycans (GAGs), which are covalently linked to a protein core. Many diseases, including inflammatory processes and tumors, are associated with characteristic ECM changes at an early stage. Recent studies have shown that contrast agents for magnetic resonance imaging (MRI), which are based on gadolinium containing chelate complexes or iron oxide nanoparticles, can bind themselves to ECM components.
To elucidate the role of GAGs like keratan sulfate (KS) and its modification state in disease, highly specific tools are necessary. As a complement to conventional immunohistochemistry LA-ICP-MS was applied to investigate the distribution of KS in tissue thin sections using a well characterized anti-KS antibody labelled with metal ions. Furthermore, LA-ICP-MS was used for the detection of MRI contrast agents and the identification of their target cells and molecules in tissue samples from animal models, e.g. for cardiovascular diseases. The results show the possibilities of LA-ICP-MS for the elucidation of pathological tissue changes.
Mechanochemistry has become a sustainable and attractive cost-effective synthetic technique, largely used within the frame of crystal engineering. Cocrystals, namely, crystalline compounds made of different chemical entities within the same crystal structure, are typically synthesized in bulk via mechanochemistry; however, whereas the macroscopic aspects of grinding are becoming clear, the fundamental principles that underlie mechanochemical cocrystallization at the microscopic level remain poorly understood. Time-resolved in situ (TRIS) monitoring approaches have opened the door to exceptional detail regarding mechanochemical reactions. We here report a clear example of cocrystallization between two solid coformers that proceeds through the formation of a metastable low melting binary eutectic phase. The overall cocrystallization process has been monitored by time-resolved in situ (TRIS) synchrotron X-ray powder diffraction with a customized ball milling setup, currently available at μ Spot beamline at BESSY-II, Helmholtz-Zentrum Berlin. The binary system and the low melting eutectic phase were further characterized via DSC, HSM, and VT-XRPD.
Fire-gilding is a historic technique for the application of golden layers on a number of different base materials utilizing a gold amalgam. This technique leaves a significant amount of Hg in the golden layer, giving archeometrists a reliable indicator to identify firegildings.
Recent findings on presumably fire-gilded objects have shown in several cases significantly lower Hg content than previously studied objects. This prompted a synchrotron-based X-ray fluorescence investigation into the Hg distribution along the material–gilding interface, as well as a series of measurements regarding the Hg content development in fire-gilded samples during artificial aging. This work presents findings on laboratory-prepared fire-gildings, indicating an Hg enrichment at the interface of firegilded silver samples. Notably, such an enrichment is missing in fire-gilded copper samples. Further, it is confirmed that fire-gilded layers typically do not undercut an Hg bulk content of 5%. In this light, it seems improbable that ancient samples that contain <5% Hg are fire-gilded. The results presented in this study might lead to a non-destructive method to identify the Hg enrichment at the interface. This might be obtained by a combination of different non-destructive measurements and might also work unambiguously in samples in which the gold top layer is altered.
EXAFS analysis of pure elements, binary and ternary equiatomic refractory alloys within the Nb-Zr-Ti-Hf- Ta system is performed at the Nb and Zr K-edges to analyze the evolution of the chemical local environ- ment and the lattice distortion. A good mixing of the elements is found at the atomic scale. For some compounds, a distribution of distances between the central atom and its neighbors suggests a distortion of the structure. Finally, analysis of the Debye-Waller parameters shows some correlation with the lat- tice distortion parameter δ², and allows to quantify experimentally the static disorder in medium entropy alloys.
This dataset contains raw data resulting from Impact-Echo measurements at the reference concrete block "IE Platte", located at BAM (German Federal Institute for Materials Research and Testing).
The specimen contains three polystyrene slabs and one polyethylene foil to act as reflectors. The specimen was produced in a three-step process. First, the base plate was cast. Second, the reflectors were taped to the base plate. Finally, the upper layer was cast on top of base plate and reflectors. A drawing is contained in the dataset.
The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publications elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010).
The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition.
Measurements were conducted using a grid of 29x29 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s.
The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points.
The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools.
Several aspects were explored towards the standardization of a suitable procedure. The use of gaseous standards is necessary and a standard gas mixture containing 60 substances was successfully generated and employed for further investigations. The suitability of different chromatography columns was addressed: The use of PLOT (Porous Layer Open Tubular) columns is well suitable for VVOC analysis. The recoveries of the 60 analytes on several adsorbents and their combinations were determined: A combination of a graphitized carbon black and a carbon molecular sieve showed great results for all analytes. Carbon molecular sieves adsorb water which can impair the analysis. Different options such as purging, the use of a drying system or splitting were investigated for water removal. This contribution will present experimental results supporting the standardization of a method for VVOC analysis.
Within this work, the combination of a microdroplet generator and an ICP-ToF-MS for nanoparticle analysis is presented. For the size determination of platinum nanoparticles an on-line isotope dilution analysis approach was developed. The 194Pt/195Pt isotopic ratio was used for the characterization of the particles, while the 182W/183W isotopic ratio was monitored simultaneously for mass bias correction. The on-line ID-MDG-sp-ICP-ToF-MS approach was deployed for the size determination of three platinum nanoparticle samples (50 nm, 63 nm, 70 nm); for validation, complementary size characterization techniques (sp-ICP-ToF-MS and TEM) were used. The robustness of this technique was evidenced, by using sodium chloride concentrations up to 100 mg L−1 as a matrix component. Our new on-line ID MDG-sp-ICP-ToF-MS approach is a promising tool for the fast and reliable determination of nanoparticles' size in severe matrix concentrations, e.g., environmental samples.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment.
With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case.
Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs.
Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks
(2022)
The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage.
In this work, we report on our progress for investigating a new experimental approach for thermographic detection of internal defects by performing 2D photothermal super resolution reconstruction. We use modern high-power laser projector technology to repeatedly excite the sample surface photothermally with varying spatially structured 2D pixel patterns. In the subsequent (blind) numerical reconstruction, multiple measurements are combined by exploiting the joint-sparse nature of the defects within the specimen using nonlinear convex optimization methods. As a result, a 2D-sparse defect/inhomogeneity map can be obtained. Using such spatially structured heating combined with compressed sensing and computational imaging methods allows to significantly reduce the experimental complexity and to study larger test surfaces as compared to the one-dimensional approach reported earlier.
Acoustic methods are ideally suited for determining the mechanical properties of different materials non-destructively. The availability of such methods is particularly important for fiber-reinforced polymers (FRPs) because their properties strongly depend on the manufacturing process and in-service conditions. Since FRPs are mostly used in thin-walled components, properties can be derived from the dispersion curves of ultrasonic guided waves (UGWs).
Our approach is based on an inverse procedure in which the numerically calcu-lated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite and a 3D laser Doppler vibrometer (3D LDV) to record the waves. Compared to the ap-proaches based on laser excitation, the PZT provides a better signal-to-noise ra-tio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows capturing in-plane and out-of-plane components and thus providing more dispersion information. Since the inverse procedure requires many iterations before elastic properties are retrieved, an ef-ficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement between theoretical and experimental curves is demonstrated.
The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The challenges in the residual stress analysis of AM components are discussed on the basis on the show studies performed in BAM. Also, the synchrotron X-ray refraction technique, available in BAM, is presented, showing example of in-situ heating test of Al10SiMg AM material.
Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control. In fact, the optimization of both the AM process and the properties of TPMSS is impossible without considering structural characteristics as manufacturing accuracy, internal defects, and as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of laboratory X-ray computed tomography (XCT).
Quantification of the Total and Accessible Number of Functional Groups and Ligands on Nanomaterials
(2022)
Surface-functionalized organic and inorganic nanoparticles (NP) are of great interest in the life and material sciences, as they can be used e.g. as drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. NP performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG) and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Methods for FG quantification should be simple, robust, reliable, fast, and inexpensive, and allow for the characteriza-tion of a broad variety of nanomaterials differing in size, chemical composition, and optical properties.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG such as amine, carboxy, thiol and aldehyde functionalities, we investigated and compared various analytical methods commonly used for functional group quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance, mass spectrometry, and thermal analysis methods.
The spatial distribution and concentration of lanthanide activator and sensitizer dopant ions are of key importance for the luminescence color and efficiency of upconverting nanoparticles (UCNPs). Quantifying dopant ion distributions and intermixing, and correlating them with synthesis methods require suitable analytical techniques. Here, X-ray photoelectron spectroscopy depth-profiling with tender X-rays (2000–6000 eV), providing probe depths ideally matched to UCNP sizes, is used to measure the depth-dependent concentration ratios of Er3+ to Yb3+, [Er3+]/[Yb3+], in three types of UCNPs prepared using different reagents and synthesis methods. This is combined with data simulations and inductively coupled plasma-optical emission spectroscopy (ICP-OES) measurements of the lanthanide ion concentrations to construct models of the UCNPs’ dopant ion distributions. The UCNP sizes and architectures are chosen to demonstrate the potential of this approach. Core-only UCNPs synthesized with XCl3·6H2O precursors (β-phase) exhibit a homogeneous distribution of lanthanide ions, but a slightly surface-enhanced [Er3+]/[Yb3+] is observed for UCNPs prepared with trifluroacetate precursors (α-phase). Examination of Yb-core@Er-shell UCNPs reveals a co-doped, intermixed region between the single-doped core and shell. The impact of these different dopant ion distributions on the UCNP's optical properties is discussed to highlight their importance for UCNP functionality and the design of efficient UCNPs.
Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT. The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
Electron microscopy (EM) is the gold standard for the characterisation of the morphology (size and shape) of nanoparticles. Visual observation of objects under examination is always a necessary first step in the characterisation process. Several questions arise when undertaking to identify and count particles to measure their size and shape distribution. In addition to challenges with the dispersion and identification of the particles, more than one protocol for counting particles is in use. This paper focuses on precise rules for the counting of particles in EM micrographs, as this influences the measurement accuracy of the number of particles, thus implicitly affecting the size values of the counted particles. We review and compare four different, commonly used methods for counting, which we then apply in case studies. The impact of the selected counting rule on the obtained final particle size distribution is highlighted. One main aim of this analysis is to support the application of a specific, well-defined counting approach in accordance with regulatory
requirements to contribute to achieving more reliable and reproducible results. It is also useful for the new harmonised measurement procedures for determining the particle size and particle size distribution of nanomaterials.
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared.
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared
Laser-induced plasmas are widely used in many areas of science and technology; examples include spectrochemical analysis, thin film deposition, and material processing. Several topics will be addressed. First, general phenomenology of laser-induced plasmas will be discussed. Then, a chemical model will be presented based on a coupled solution of Navier-Stokes, state, radiative transfer, material transport, and chemical equations. Results of computer simulations for several chemical systems will be shown and compared to experimental observations obtained by optical imaging, spectroscopy, and tomography. The latter diagnostic tools will also be briefly discussed. Finally, a prospective application of laser-induced plasma and plasma modeling will be illustrated on the example of chemical vapor deposition of molybdenum borides and micro processing and coating of titanium dental implants.
IRWG strategy update
(2022)
In this study, carried out within the Joint Danube Survey 4, a comprehensive microplastic screening in the water column within a large European river basin from its source to estuary, including major tributaries, was realized. The objective was to develop principles of a systematic and practicable microplastic monitoring strategy using sedimentation boxes for collection of suspended particulate matter followed by its subsequent analysis using thermal extraction desorption-gas chromatography/mass spectrometry. In total, 18 sampling sites in the Danube River Basin were investigated. The obtained suspended particulate matter samples were subdivided into the fractions of >100 μm and <100 μm and subsequently analyzed for microplastic mass contents. The results showed that microplastics were detected in all samples, with polyethylene being the predominant polymer with maximum contents of 22.24 μg/mg, 3.23 μg/mg for polystyrene, 1.03 μg/mg for styrene-butadiene-rubber, and 0.45 μg/mg for polypropylene. Further, polymers such as different sorts of polyester, polyacrylates, polylactide, and natural rubber were not detected or below the detection limit. Additional investigations on possible interference of polyethylene signals by algae-derived fatty acids were assessed. In the context of targeted monitoring, repeated measurements provide more certainty in the interpretation of the results for the individual sites. Nevertheless, it can be stated that the chosen approach using an integrative sampling and determination of total plastic content proved to be successful.
In view of the increasing digitization of research and the use of data-intensive measurement and analysis methods, research institutions and their staff are faced with the challenge of documenting a constantly growing volume of data in a comprehensible manner, archiving them for the long term, and making them available for discovery and re-use by others in accordance with the FAIR principles. At BAM, we aim to facilitate the integration of research data management (RDM) strategies during the whole research cycle from the creation and standardized description of materials datasets to their publication in open repositories. To this end, we present the BAM Data Store, a central system for internal RDM that fulfills the heterogenous demands of materials science and engineering labs. The BAM Data Store is based on openBIS, an open-source software developed by the ETH Zurich that has originally been created for life science laboratories but that has since been deployed in a variety of research domains. The software offers a browser-based user interface for the digital representation of lab inventory entities (e.g., samples, chemicals, instruments, and protocols) and an electronic lab notebook for the standardized documentation of experiments and analyses.
To investigate whether openBIS is a suitable framework for the BAM Data Store, we carried out a pilot phase during which five research groups with employees from 16 different BAM divisions were introduced to the software. The pilot groups were chosen to represent a diverse array of domain use cases and RDM requirements (e.g., small vs big data volume, heterogenous vs structured data types) as well as varying levels of prior IT knowledge on the users’ side.
Overall, the results of the pilot phase are promising: While the creation of custom data structures and metadata schemas can be time-intensive and requires the involvement of domain experts, the system offers specific benefits in the form of a simplified documentation and automation of research processes, as well as constituting a basis for data-driven analysis. In this way, heterogeneous research workflows in various materials science research domains could be implemented, from the synthesis and characterization of nanomaterials to the monitoring of engineering structures. In addition to the technical deployment and the development of domain-specific metadata standards, the pilot phase also highlighted the need for suitable institutional infrastructures, processes, and role models. An institute-wide rollout of the BAM Data Store is currently being planned.
The present Table of Standard Atomic Weights (TSAW) of the elements is perhaps one of the most familiar data sets in science. Unlike most parameters in physical science whose values and uncertainties are evaluated using the “Guide to the Expression of Uncertainty in Measurement” (GUM), the majority of standard atomic weight values and their uncertainties are consensus values, not GUM-evaluated values. The Commission on Isotopic Abundances and Atomic Weights of the International Union of Pure and Applied Chemistry (IUPAC) regularly evaluates the literature for new isotopic-abundance measurements that can lead to revised standard atomic-weight values, Ar(E) for element E.
The Commission strives to provide utmost clarity in products it disseminates, namely the TSAW and the Table of Isotopic Compositions of the Elements (TICE). In 2016, the Commission recognized that a guideline recommending the expression of uncertainty listed in parentheses following the standard atomic-weight value, for example, Ar(Se) = 78.971(8), did not agree with the GUM, which suggests that this parenthetic notation be reserved to express standard uncertainty, not the expanded uncertainty used in the TSAW and TICE. In 2017, to eliminate this noncompliance with the GUM, a new format was adopted in which the uncertainty value is specified by the “±” symbol, for example, Ar(Se) = 78.971 ± 0.008. To clarify the definition of uncertainty, a new footnote has been added to the TSAW. This footnote emphasizes that an atomic-weight uncertainty is a consensus (decisional) uncertainty. Not only has the Commission shielded users of the TSAW and TICE from unreliable measurements that appear in the literature as a result of unduly small uncertainties, but the aim of IUPAC has been fulfilled by which any scientist, taking any natural sample from commerce or research, can expect the sample atomic weight to lie within Ar(E) ± its uncertainty almost all of the time.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.
Inductively coupled plasma-mass spectrometry (ICP-MS) is a well-established analytical method offering high sensitivity and multi-element analysis. ICP-MS has found acceptance in various application areas ranging from material analysis to applications in the life sciences. Within the last 15 years new strategies for the sensitive detection and accurate quantification of biomolecules in complex biomedical samples have been developed. Recent instrumental improvements have contributed to this progress.
As most of the biomolecules do not contain endogenous metals etectable with ICP-MS, bioconjugation with artificial metal-containing tags based on metal-loaded chelate complexes or nanoparticles is increasingly applied to determine biomolecules indirectly. Especially, the combination of immunohistochemical workflows using lanthanoid-tagged antibodies and ICP-MS detection provides new insights in the complexity and interdependency of cellular processes. Single-cell ICP-MS, also termed as mass cytometry, allows high-dimensional analysis of biomarkers in cell populations at single-cell resolution. For that purpose, lanthanoid isotope labelled antibodies are used to detect their corresponding target molecules. The visualisation of the elemental distribution is possible with laser ablation ICP-MS (LA-ICPMS) at high spatial resolution. Especially, the combination of LA with ICP time-of-flight mass spectrometry, also referred to as imaging mass cytometry (IMC), opens new possibilities for multiparametric tissue imaging at the single-cell level and even below. The lanthanoid localisation and concentration can be linked to their conjugated antibody target providing valuable information about surface markers, intracellular signalling molecules to measure biological function, and the network state of an individual cell in a tissue.
This book chapter focuses on new applications, where the multi-element capabilities of ICP-MS are used for the detection of lanthanoids applied as artificial elemental stains or tags for biomolecules and in particular antibodies.
Per- and polyfluorinated alkyl substances (PFASs) are a substance class of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their different chemical and physical properties as well as the high number of target substances. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate a realistic PFAS pollution level.
PFAS sum parameters compromise the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for indirect fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
Here, we describe a fast and simple extraction method for the determination of the EOF using HR-CS-GFMAS in soil samples. Common approaches for the EOF determination use solid phase extraction (SPE). To omit the bias of this time consuming and expensive step we optimized a fast and simple SPE-free extraction method. The developed extraction method consists of a liquid-solid extraction using acidified methanol. Comparison of the method with and without an SPE clean-up step revealed a drastic underestimation of EOF concentrations using SPE. In the next step, the applicability of our method was tested for other solid matrices. In view of steadily increasing numbers of PFASs, our method will make an important contribution in assessing the pollution situation as well as support policy makers in deriving exposure limits for PFASs in the future.
Thermographic non-destructive testing is based on the interaction of thermal waves with inhomogeneities. The propagation of thermal waves from the heat source to the inhomogeneity and to the detection surface according to the thermal diffusion equation leads to the fact that two closely spaced defects can be incorrectly detected as one defect in the measured thermogram. In order to break this spatial resolution limit (super resolution), the combination of spatially structured heating and numerical methods of compressed sensing can be used. The improvement of the spatial resolution for defect detection then depends in the classical sense directly on the number of measurements. Current practical implementations of this super resolution detection still suffer from long measurement times, since not only the achievable resolution depends on performing multiple measurements, but due to the use of single spot laser sources or laser arrays with low pixel count, also the scanning process itself is quite slow. With the application of most recent high-power digital micromirror device (DMD) based laser projector technology this issue can now be overcome.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. 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) and visual (VIS)/ near-infrared (NIR) spectroscopy. 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-containing 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.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.
Catalysts are important components in chemical processes because they lower the activation energy and thus determine the rate, efficiency and selectivity of a chemical reaction. This property plays an important role in many of today’s processes, including the electrochemical splitting of water. Due to the continuous development of catalyst materials, they are becoming more complex, which makes a reliable evaluation of physicochemical properties challenging even for modern analytical measurement techniques and industrial manufacturing.
We present a fast, vacuum-free and non-destructive analytical approach using multi-sample spectroscopic ellipsometry to determine relevant material parameters such as film thickness, porosity and composition of mesoporous IrOx–TiOy films. Mesoporous IrOx–TiOy films were deposited on Si wafers by sol–gel synthesis, varying the composition of the mixed oxide films between 0 and 100 wt%Ir. The ellipsometric modeling is based on an anisotropic Bruggeman effective medium approximation (a-BEMA) to determine the film thickness and volume fraction of the material and pores. The volume fraction of the material was again modeled using a Bruggeman EMA to determine the chemical composition of the materials. The ellipsometric fitting results were compared with complementary methods, such as scanning electron microscopy (SEM), electron probe microanalysis (EPMA) as well as environmental ellipsometric porosimetry (EEP).
Atomically precise gold nanoclusters are a fascinating class of nanomaterials that exhibit molecule-like properties and have outstanding photoluminescence (PL). Their ultrasmall size, molecular chemistry, and biocompatibility make them extremely appealing for selective biomolecule labeling in investigations of biological mechanisms at the cellular and anatomical levels. In this work, we report a simple route to incorporate a preformed Au25 nanocluster into a model bovine serum albumin (BSA) protein. A new approach combining small-angle X-ray scattering and molecular modeling provides a clear localization of a single Au25 within the protein to a cysteine residue on the gold nanocluster surface.
Attaching Au25 to BSA strikingly modifies the PL properties with enhancement and a redshift in the second near-infrared (NIR-II) window. This study paves the way to conrol the design of selective sensitive probes in biomolecules through a ligand-based strategy to enable the optical detection of biomolecules in a cellular environment by live imaging.
Biofilms are ubiquitous in nature and in the man-made environment. Given their harmful effects on human health, an in-depth understanding of biofilms and the monitoring of their formation and growth are important. Particularly relevant for many metabolic processes and survival strategies of biofilms is their extracellular pH. However, most conventional techniques are not suited for minimally invasive pH measurements of living biofilms. Here, a fluorescent nanosensor is presented for ratiometric measurements of pH in biofilms in the range of pH 4.5–9.5 using confocal laser scanning microscopy. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with pH-inert dye Nile Red and is surface functionalized with a pH-responsive fluorescein dye. Its performance was validated by fluorometrically monitoring the time-dependent changes in pH in E. coli biofilms after glucose inoculation at 37 °C and 4 °C. This revealed a temperature-dependent decrease in pH over a 4-h period caused by the acidifying glucose metabolism of E. coli. These studies demonstrate the applicability of this nanosensor to characterize the chemical microenvironment in biofilms with fluorescence methods.
Asymmetrically bridged aroyl-S,N-ketene acetals and aroyl-S,N-ketene acetal multichromophores can be readily synthesized in consecutive three-, four-, or five-component syntheses in good to excellent yields by several successive Suzuki-couplings of aroyl-S,N-ketene acetals and bis(boronic)acid esters. Different aroyl-S,N-ketene acetals as well as linker molecules yield a library of 23 multichromophores with substitution and linker pattern-tunable emission properties. This allows control of different communication pathways between the chromophores and of aggregation-induced emission (AIE) and energy transfer (ET) properties, providing elaborate aggregation-based fluorescence switches.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on an instrumental design and operational parameters, which require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In the presence of surface defects, the temperature field is distorted in a specific manner that depends on shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for monitoring the process: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows for a cautious inference that optical spectroscopy can detect surface defects and, possibly, predict their characters, e.g., inner or protruding.
Global supply chains rely on the compliance and safety of their products, processes, and facilities. These vital services (often referred to as ‘quality assurance’ or ‘conformity assessment’ services) are provided by Conformity Assessment Bodies (CABs). This empirical study explores the impact of the COVID-19 pandemic on CABs as well as their response to the resulting challenges. Data was gathered through an online survey among all accredited CABs in Germany, which resulted in 555 valid responses. Taking a resilience perspective, we reveal that CABs were hit hard by the disruptions caused by the pandemic, albeit to different degrees, in part due to their type of services, size, and sectors served. Furthermore, we find that contingency plans do not directly cushion order declines (as the main indicator of the economic impact of the pandemic) but rather indirectly through helping CABs respond more quickly, which in turn mitigates their order declines. However, our results show that contingency plans can also have adverse effects if they hinder flexible reaction to the crisis. The findings of our study help managers and policymakers learn from the COVID-19 pandemic and improve the resilience of the conformity assessment sector and quality assurance in the event of future crises.
The services of Conformity Assessment Bodies (CABs) are essential to provide for trust in and safety of digital products and services by demonstrating that requirements from standards are met. Thus, it is vital that CABs are ready to fulfil their tasks also in the digital transformation, having the necessary capabilities and resources. Our study is the first to comprehensively assess the digital maturity in the CA industry and to provide some insights into the readiness of the industry to support and at the same time benefit from the digital age. To this end, we developed and implemented a digital maturity model tailored to the CA industry. In this paper, we present first results from our survey among 354 accredited CABs in Germany. With our research we contribute to better understand the digital transformation and maturation of CABs along distinctive stages. The findings suggest that the transformation process in the CA industry is just at the beginning, with the majority of CABs still in early stages of digital maturity. Also, only a few of them already exploit the latest digital technologies and applications like artificial intelligence, blockchain or big data analytics. Nevertheless, CABs regard digitalization as a big
opportunity – for themselves and their industry.
The finite volume method (FVM), like the finite element method (FEM), is a numerical method for determining an approximate solution for partial differential equations. The derivation of the two methods is based on very different considerations, as they have historically evolved from two distinct engineering disciplines, namely solid mechanics and fluid mechanics. This makes FVM difficult to learn for someone familiar with FEM. In this paper we want to show that a slight modification of the FEM procedure leads to an alternative derivation of the FVM. Both numerical methods are starting from the same strong formulation of the problem represented by differential equations, which are only satisfied by their exact solution. For an approximation of the exact solution, the strong formulation must be converted to a so-called weak form. From here on, the two numerical methods differ. By appropriate choice of the trial function and the test function, we can obtain different numerical methods for solving the weak formulation of the problem. While typically in FEM the basis functions of the trial function and test function are identical, in FVM they are chosen differently. In this paper, we show which trial and test function must be chosen to derive the FVM alternatively: The trial function of the FVM is a “shifted” trial function of the FEM, where the nodal points are now located in the middle of an integration interval rather than at the ends. Moreover, the basis functions of the test function are no longer the same as those of the trial function as in the FEM, but are shown to be a constant equal to 1. This is demonstrated by the example of a 1D Poisson equation.
Sound production due to main-flow oriented vorticity-nozzle interaction in absence of a net swirl
(2022)
The downstream acoustic response due to the interaction of main-flow oriented vorticity with a choked nozzle in a swirl-free flow was experimentally demonstrated. The response was obtained by means of impulsive radial air injection in the pipe upstream from the nozzle. The resulting downstream acoustic data are shown to obey a scaling rule that differs, from the one for swirl-nozzle interaction, which according to the literature is proportional to the square of the swirl number. In contrast, here evidence is presented that points to the scaling of main-flow oriented vorticity noise with the cross-sectional average of the square of the transversal velocity at the throat divided by the square of the critical sound speed.