Analytische Chemie
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Paper des Monats
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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.
Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and highthroughput mass quantification of microplastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermoanalytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg.
The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most
compact NIR spectrometers available.
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.
Till now application of printed magnetoelectronics is hindered by lack of large area exchange coupled metallic multilayers required to produce printable magneto-sensory inks. Large-scale roll-to-roll (R2R) fabrication process is an attractive approach owing to its capabilities for high volume, high throughput, and large area manufacturing. Precise and high performance R2R sputtering technology is developed to fabricate large area giant magnetoresistive (GMR) thin-films stacks that contain 30 metallic bilayers prepared by continuous R2R sputtering of Co and Cu sequential on a hundred meters long polyethylene terephthalate (PET) web. The R2R sputtered Co/Cu multilayer on a 0.2 × 100 m2 PET web exhibits a GMR ratio of ≈40% achieving the largest area exchange coupled room temperature magneto-sensitive system demonstrated to date. The prepared GMR thin-film is converted to magnetosensitive ink that enables printing of magnetic sensors with high performance in a cost-efficient way, which promotes integration with printed electronics. An average GMR ratio of ≈18% is obtained for 370 printed magnetic sensors. The realized precise R2R sputtering approach can also be extended to a wide range of hybrid thin-film material systems opening up a path for new functional inks applied with printing technologies.
Die passive Probenahme von VOC (Volatile Organic Compounds) mit Tenax® TA und Thermodesorption GC/MS Analytik ist eine einfache, kosteneffiziente und repräsentative Methode zur Bestimmung der VOC-Konzentrationen in der Innenraumluft. In der Theorie ist die Stoffaufnahme in den Passivsammler nur abhängig vom Diffusionskoeffizienten der Substanz in Luft und der Geometrie des Sammlers (ideale Adsorption). Um sie zu charakterisieren, wird die Aufnahmerate (UR), definiert als Quotient der Massenaufnahme und dem Produkt aus Konzentration und Expositionszeit, verwendet. Viele effektive Aufnahmeraten (UR,eff) unterscheiden sich beträchtlich von idealen (theoretischen) Werten (UR,id). Literaturwerte sind in nationalen und internationalen Normen lediglich für bestimmte Expositionszeiten vorgegeben, während detaillierte Informationen über den zugehörigen Konzentrationsbereich fehlen. Außerdem ist die Anzahl der insgesamt in der Literatur beschriebenen Substanzen begrenzt. Das Ziel der vorgestellten Studie ist es diesen Fundus an Aufnahmeraten zu begutachten und zu prüfen und ihn durch die Bestimmung eigener qualitätsgesicherter Laborwerte zu ergänzen. Die bestimmten Aufnahmeraten werden als akkurat bezüglich ihrer relativen Standardabweichung und Vergleichbarkeit zu Literaturwerten betrachtet und können für Expositionszeiten von 7 Tagen bei Konzentrationen von 50 100 µg/m³ (ca. 100 300 ppm min) empfohlen werden. Die Sieben Tage Aufnahmeraten aus ISO16017 2 und ASTM D6196 sind nicht generell für diesen Zweck geeignet, wie exemplarisch für Benzol gezeigt wurde.
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).
Molecularly imprinted polymers (MIPs) against sialic acid (SA) have been developed as a detection tool to target cancer cells. Before proceeding to in vivo studies, a better knowledge of the overall effects of MIPs on the innate immune system is needed. The aim of this study thus was to exemplarily assess whether SA-MIPs lead to inflammatory and/or cytotoxic responses when administered to phagocytosing cells in the innate immune system. The response of monocytic/macrophage cell lines to two different reference particles, Alhydrogel and PLGA, was compared to their response to SA-MIPs. In vitro culture showed a cellular association of SA-MIPs and Alhydrogel, as analyzed by flow cytometry. The reference particle Alhydrogel induced secretion of IL-1b from the monocytic cell line THP-1, whereas almost no secretion was provoked for SA-MIPs. A reduced number of both THP-1 and RAW 264.7 cells were observed after incubation with SA-MIPs and this was not caused by cytotoxicity. Digital holographic cytometry showed that SA-MIP treatment affected cell division, with
much fewer cells dividing. Thus, the reduced number of cells after SA-MIP treatment was not linked to SA-MIPs cytotoxicity. In conclusion, SA-MIPs have a low degree of inflammatory properties, are not cytotoxic, and can be applicable for future in vivo studies.
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.
Der Vortag berichtet über zwei Forschungsprojekte KALLUP (Vorrichtung zur Charakterisierung und Kalibrierung von luftgekoppelten Prüfköpfen) und PALUP (Phased-Array-Technik für Luftultraschall-Prüfungen). Projektpartner sind die BAM in Berlin und Hillger NDT. Die Phased-Array-Technik ermöglicht bekanntermaßen eine wesentlich flexiblere Anpassung der Ultraschallprüftechnik an unterschiedliche Prüfaufgaben als die klassische einkanalige Prüftechnik. Um diese Flexibilität auch bei berührungslosen Verfahren wie der Ankopplung über Luft zu erreichen, arbeiten die Partner BAM und Hillger NDT intensiv auf dem Gebiet. Entwickelt wurde ein achtkanaliger thermoakustischer Wandler, der als breitbandiger Phased-Array-Sender eingesetzt wird. Das Ziel im PALUP-Projekt ist die Entwicklung eines Phased-Array-Demonstrators mit Luftankopplung, wobei als Sender und Empfänger Sensoren aus zellulären Kunststoffmaterialien eingesetzt werden.
Die Arrays erlauben durch das Umschalten der Elemente ein elektronisches Scannen, elektronisches Schwenken des Einschallwinkels und elektronisches Fokussieren, was bisher nur mit der Phased-Array-Technik mit Koppelmitteln möglich ist. Die Teilziele der BAM sind: die Entwicklung des Layouts für Array-Sender und -Empfänger, Auswahl des zellulären Kunststoffs für den Wandlerbau, Konzept und Bau des Sende- und Empfangssensors sowie die Charakterisierung der Sensoren.
Die Teilziele von Hillger NDT sind: die Konzipierung der Prüfstrategie, Konzept und Bau der mehrkanaligen Sendetechnik, Konzept und Bau der mehrkanaligen Empfangstechnik, Entwicklung der Software für Datenerfassung.
Robotergeführte Ultraschallprüfung von Gasturbinenschaufeln mit adaptiver TFM im ZfP 4.0-Umfeld
(2022)
Leit- und Laufschaufeln stationärer Gasturbinen sind im Betrieb anspruchsvollen Bedingungen ausgesetzt. Die Prüfung, Wartung und Reparatur der hochbelasteten Teile sind notwendig, um Sicherheit und Effizienz über längere Zeiträume zu gewährleisten. Eine der in diesem Prozess angewandten Methoden ist die Ultraschallprüfung.
Im Zuge der fortschreitenden Digitalisierung ist es das Ziel des Projektes MRO 2.0, den Aufbereitungsvorgang um digitale Prozesse zu erweitern und somit zu modernisieren. Eine der Aufgaben ist es, dabei anstelle der konventionellen Ultraschallprüfung eine Array-Technik mit rekonstruierenden Verfahren einzusetzen und eine automatisierte, digital eingebundene Methode im Rahmen von ZfP 4.0 zu entwickeln.
Um die Ist-Geometrie der Oberfläche und die verbleibende Wanddicke flächendeckend an den Turbinenschaufeln zu bestimmen, wird ein adaptives TFM Verfahren (Total Focusing Method) in Tauchtechnik eingesetzt, welches die Brechung der Schallwellen an der Grenzfläche zum Prüfkörper in der Rekonstruktion berücksichtigt. In der hierfür entwickelten Prüfanlage führt ein Roboterarm einen Array-Prüfkopf und scannt das Bauteil normal zur inspizierten Oberfläche. Somit kann ein 3D-Modell des Ist Zustandes des zu prüfenden Bauteils erstellt werden.
Spezielle Herausforderungen an die Aufgabe stellen die komplexe Geometrie des Prüfobjektes sowie dessen geringe und ortsabhängige Wanddicke dar. Ein weiterer Fokus liegt auf der Optimierung der Prüfparameter, Verbesserung der Prüfgeschwindigkeit sowie der Zuverlässigkeit der Methode.
In diesem Beitrag werden die während des Projektes entwickelte Methode und die im zweiten Projektjahr erarbeiteten Ergebnisse vorgestellt, mit dem Schwerpunkt auf die entwickelten Rekonstruktionsalgorithmen und den Versuchsaufbau.
Brillouin Optical Frequency Domain Analysis (BOFDA) is a powerful and well-established method for static distributed sensing of temperature and strain. Recently, we demonstrated a BOFDA system based on convolutional neural network which shortens the measurement time considerably. In this paper, we apply leave-one-out cross validation to evaluate the generalization performance and provide an unbiased and reliable machine learning model for a time-efficient BOFDA system.
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
We present our achievements in the development of distributed fiber optic sensing systems based on Brillouin optical frequency-domain analysis for structural health monitoring. The focus of the applications is on the gapless monitoring of geotechnical structures, large area infrastructures and electrical grids. The work includes the latest use of machine learning algorithms to reduce measurement time by coexistent increasing the measurement accuracy.
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)
Silicon photonic micro-ring resonators (MRR) developed on the silicon-on-insulator (SOI) platform, owing to their high sensitivity and small footprint, show great potential for many chemical and biological sensing applications such as label-free detection in environmental monitoring, biomedical engineering, and food analysis. In this tutorial,we provide the theoretical background and give design guidelines for SOI-based MRR as well as examples of surface functionalization procedures for label-free detection of molecules. After introducing the advantages and perspectives of MRR, fundamentals of MRR are described in detail, followed by an introduction to the fabrication methods, which are based on a complementary metal-oxide semiconductor (CMOS) technology. Optimization of MRR for chemical and biological sensing is provided, with special emphasis on the optimization of waveguide geometry. At this point, the difference between chemical bulk sensing and label-free surface sensing is explained, and definitions like waveguide sensitivity, ring sensitivity, overall sensitivity as well as the limit of detection (LoD) of MRR are introduced. Further, we show and explain chemical bulk sensing of sodium chloride (NaCl) in water and provide a recipe for label-free surface sensing.
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.
Das Bauwesen erfordert sehr hohe Flächenleistungen, so dass der physische Kontakt zur Oberfläche möglichst vermieden werden sollte, um eine hohe Verfahrgeschwindigkeit der Sensoren zu gewährleisten. Andererseits weisen luftgekoppelte, membranbasierte Aktuatoren durch den Impedanzsprung sehr hohe Verluste auf. Daher stellt das schnelle berührungslose Ultraschallmessen immer noch eine ungelöste Herausforderung im Bauwesen dar.
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).
Die Thermo Extraktion Desorption Gas Chromatograpie Massen Spektrometrie (TED-GC/MS) ist ein schnelles thermoanalytisches Verfahren zur Bestimmung von Gehalten an Mikroplastik (MP). Die Kombination aus teils schwerflüchtigen Analyten und Kältebrücken führt zu Memory-Effekten, denen u.a. durch häufige Blindwertmessungen begegnet werden muss. Reduzierte Probedurchsätze sind die Folge. Um Messergebnisse abzusichern und den Gerätestatus bei gleichzeitig hoher Messleistung überwachen zu können, wurde die sequentielle Standardmethode überarbeitet.
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.
In this study, the concept of a Zero Mass Flow Liner is evaluated. The concept enables impedance control by the induction of periodic bias flow through the perforated facing sheet of the liner. The periodic bias flow is generated by a secondary high amplitude acoustic actuation. By means of the periodic bias flow, the liner can be tuned to different operating points in a given range of grazing flow velocities. The equivalent fluid impedance model for perforated plates is modified to account for the effects of periodic bias flow and grazing flow. An optimization routine, based on a genetic algorithm, is implemented. The method is applicable to any liner concept and uses the impedance of the lined surface as boundary condition in a numerical simulation. Thereby, a set of liner parameters is derived in order to obtain the desired damping characteristics. Based on the results of the optimization, a Zero Mass Flow Liner is manufactured and consequently evaluated experimentally. The damping characteristics are evaluated in form of the dissipated energy along the lined surface. Prediction and measurements show agreement. The Zero Mass
Flow Liner delivers broad band dissipation of high peak value over a range of grazing flow Mach numbers. Under grazing ow conditions, the effect of periodic bias flow is reduced. This poses high energy requirements in high Mach number flow regimes which might restrict the applicability of the Zero Mass Flow concept to grazing flows of low Mach numbers.
Die zerstörungsfreie Prüfung von metallischen Bauteilen hergestellt mit additiver Fertigung (Additive Manufacturing - AM) gewinnt zunehmend an industrieller Bedeutung. Grund dafür ist die Feststellung von Qualität, Reproduzierbarkeit und damit auch Sicherheit für Bauteile, die mittels AM gefertigt wurden. Jedoch wird noch immer ex-situ geprüft, wobei Defekte (z.B. Poren, Risse etc.) erst nach Prozessabschluss entdeckt werden. Übersteigen Anzahl und/oder Abmessung die vorgegebenen Grenzwerte für diese Defekte, so kommt es zu Ausschuss, was angesichts sehr langer Bauprozessdauern äußerst unrentabel ist. Eine Schwierigkeit ist dabei, dass manche Defekte sich erst zeitverzögert zum eigentlichen Materialauftrag bilden, z.B. durch thermische Spannungen oder Schmelzbadaktivitäten. Dementsprechend sind reine Monitoringansätze zur Detektion ggf. nicht ausreichend.
Daher wird in dieser Arbeit ein Verfahren zur aktiven Thermografie an dem AM-Prozess Laser Powder Bed Fusion (L-PBF) untersucht. Das Bauteil wird mit Hilfe des defokussierten Prozesslasers bei geringer Laserleistung zwischen den einzelnen gefertigten Lagen unabhängig vom eigentlichen Bauprozess erwärmt. Die entstehende Wärmesignatur wird ort- und zeitaufgelöst durch eine Infrarotkamera erfasst. Durch diese der Lagenfertigung nachgelagerte Prüfung werden auch zum Bauprozess zeitversetzte Defektbildungen nachweisbar.
In dieser Arbeit finden die Untersuchungen als Proof-of-Concept, losgelöst vom AM-Prozess, an einem typischen metallischen Testkörper statt. Dieser besitzt eine Nut als oberflächlichen Defekt. Die durchgeführten Messungen finden an einer eigens entwickelten L-PBF-Forschungsanlage innerhalb der Prozesskammer statt. Damit wird ein neuartiger Ansatz zur aktiven Thermografie für L-PBF erforscht, der eine größere Bandbreite an Defektarten auffindbar macht. Der Ansatz wird validiert und Genauigkeit sowie Auflösungsvermögen geprüft. Eine Anwendung am AM-Prozess wird damit direkt forciert und die dafür benötigten Zusammenhänge werden präsentiert.
Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous-Flow Production
(2022)
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.