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The metrological analysis uses an unbroken chain of comparative measurements to trace results back to the national or international standard. This enables comparable, absolute quantification between laboratories. In 2020/2021, a pilot study for the quantification of SARS-CoV-2 antibodies was initiated with the involvement of BAM. Despite the consistent use of ID-MS, a large discrepancy in the results of the participating laboratories was found. This was the motivation for a project to systematically investigate and optimize traceable methods of protein quantification using mass spectrometric nontarget analysis (NTA) and recombinant antibody panels.
Der Bunsen-Kirchhoff-Preis 2022 wurde am 23.06.2022 anlässlich der analytica conference in München an Dr. Carlos Abad verliehen - in Anerkennung seiner exzellenten Entwicklungen im Bereich der continuum source atomic absorption spectrometry (CS-AAS).
Dr. Carlos Abad ist ein herausragender Experte auf dem Gebiet der Atom- und molekularen Absorptionsspektrometrie. insbesondere trug er maßgeblich zur substanziellen Weiterentwicklung von Echelle-Spektrometern für die CS-AAS bei. So gelang es, einen quantitativen Zugang zu Elementen wie Bor, Chlor, Fluor und Schwefel, mittels AAS zu erreichen. Erstmals demonstriert Dr. Carlos Abad am Beispiel eines Zr-Modifier, dass durch die Zeitauflösung der eingesetzten Echelle-Systeme mechanistische Untersuchungen zur Wirkung des Modifiers im Graphitrohrofen möglich sind.
Besonders hervorzuheben sind seine Arbeiten zum Einsatz der CS-AAS für die Analyse von Isotopen, die eine Genauigkeit aufweist, welche an die der Multikollektor-induktiv gekoppelten Plasma-Massenspektrometrie (MC-ICP-MS) heranreicht. Damit ergeben sich völlig neue Einsatzmöglichkeiten für technologisch hochrelevante Applikationen, wie z.B. die Untersuchung der Alterung von Lithium-Batterien oder die Lithium-Analyse in Blutserum.
Calcium isotope analysis can be an important tool for paleoclimate studies of the carbon cycle, as well in carbon capture technology, but its utility is limited by challenges using conventional mass spectrometry. We propose a new fast, precise, and high-throughput technology based on multiple complementary high-resolution spectroscopies analyzed by machine-learning.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
Isotope analysis is a tool for material research. For example, it may provide information about the provenance of a sample or changes in dynamic systems. Here is presented optical spectroscopy as an analytical alternative to mass spectrometry for isotope quantification based on the isotopic shift of atoms and diatomic molecules.
XPS of GR2M
(2022)
High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries
(2022)
Lithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles.
Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li.
The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material, a cathode material (NMC111). Finally, the ML model was applied to determine the isotope ratio of geological samples, including anorthosite, granite, soil, rhyolite, nepheline syenite, and basalt and battery samples. These samples were measured as digested without any further purification step.
Improvements in the optical resolution resolve the lithium isotopic components of the atomic spectra. In the studied geological samples, were found δ7Li values between -0.5 and 4.5 ‰ with a precision range of 1 to 2 ‰. In addition, the proposed method was validated with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), and these results are comparable and compatible.
This presentation summarizes major findings from an international study in 16 countries and regions on digital transformation in conformity assessment bodies such as testing and calibration laboratories or certification and inspection bodies. It draws from survey data of 1.476 participants and specifically highlights findings on the digital maturity of the organizations, providing an international comparison.
The formation of irregularities such as keyhole porosity pose a major challenge to the manufacturing of metal parts by laser powder bed fusion (PBF-LB/M). In-situ thermography as a process monitoring technique shows promising potential in this manner since it is able to extract the thermal history of the part which is closely related to the formation of irregularities. In this study, we investigate the utilization of machine learning algorithms to detect keyhole porosity on the base of thermographic features. Here, as a referential technique, x-ray micro computed tomography is utilized to determine the part's porosity. An enhanced preprocessing workflow inspired by the physics of the keyhole irregularity formation is presented in combination with a customized model architecture. Furthermore, experiments were performed to clarify the role of important parameters of the preprocessing workflow for the task of defect detection . Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
Time is the most valuable parameter in synchrotron experiments. This is costly and some of the experiments suffer from low efficiency due to low counting statistics. With today's high processing power long experiments are run in a shorter time and increase efficiency. With optimization algorithms time in "counting-hungry" experiments reduced by factor of 10. Our project is to develop a new method to analyze the chemical properties of complex materials non-destructively and efficiently, such as high entropy materials subjected to corrosion processes. A better understanding of the corrosion process will help to develop corrosion-resistant materials and reduce the cost of corrosion damage, which averages around 2.5 trillion USD annually.
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
News from the BAMline
(2022)
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
In this paper, several examples in the areas of beamline alignment and measurement time optimization based on Bayesian optimization (BO) with Gaussian processes (GP) are presented. BO is a method for finding the global optimum of a function using a probabilistic model represented by a GP. The advantage of this method is that it can handle high-dimensional problems, does not depend on the initial estimate, and also provides uncertainty estimates.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM). To achieve optimal performance, up to three linear and two angular motor positions have to be optimized. To achieve this with a grid scan, at least 100^5 measurement points would be required. Assuming that all positions can be aligned independently, 100*5 points are still necessary. We show that with BO and GP less than 100 points are sufficient to achieve equal or better results.
The second example is the optimization of measurement time in XRF scanning. Here we will show the advantage of the BO GP approach over point-by-point scanning. As can be seen in Fig. 1, the number of points required and thus the measurement time can be reduced by a factor of 50, while the loss in image quality is acceptable. The advantages and limitations of this approach will be discussed.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
In this talk an overview about artificial intelligence/machine learning applications @BAMline is given. In the first part, the use of neural networks for the quantification of XRF measurements and the decoding of coded-aperture measurements are shown. Then it is shown how Gaussian processes and Bayesian statistics can be used to achieve an optimal alignment of the set-up and in general for optimization of measurements.
Gold is one of the seven metals already known in antiquity and was used from time immemorial as a medium of exchange and for the production of jewelry because of its luster and rarity. In addition, it is easy to work and largely resistant to chemical influences. Investigations of gold using synchrotron radiation excited X-ray fluorescence analysis are non-destructive and provide information about the chemical elements present in the sample under investigation. The investigations presented here at BAMline focus on questions such as the origin, manufacturing process, and association of gold findings. The different questions are explained by a number of examples ranging from the Viking treasure from Hiddensee to the Nebra Sky Disk and finds from Egypt. The find from Bernstorf is discussed in detail. A Bayesian treatment of the authenticity is shown.
Aging Mechanisms of Lithium Batteries: How can we make batteries more durable and more sustainable in the future?
Lithium batteries are particularly susceptible to ageing processes. During each charging and discharging process in an electric battery, lithium ions are deposited in the electrodes of the cell like in the pores of a sponge. Over time, however, fractures and cracks occur in the filigree structures. The result: more and more lithium ions no longer fit into the hollow spaces of the „sponge“, instead they accumulate in heaps around the electrodes and hinder the movement of other ions. The performance of the battery decreases.
We present our new project, in which we are developing a fast and cost-effective method with which companies that produce lithium batteries can already assess the ageing behaviour of their batteries in the laboratory.
Fluorescent semiconductor nanocrystals, also known as quantum dots (QDs), enabled many advancements in biotechnology, photovoltaics, photocatalysis, quantum computing and display devices. The high versatility of this nanomaterial is based on their unique size-tunable photoluminescence properties, which can be adjusted from the visible to the near-infrared range. In contrast to other nanomaterials, QDs made the transition from a laboratory curiosity to the utilization in commercial products, like the QLED television screen or in smartphone displays. The best investigated QDs are composed of heavy metals like cadmium or lead, which is not the best choice in terms of toxicity and environmental pollution. A more promising material is Indium Phosphide (InP), which is also currently used by Samsung, Sony and co. in the QLED displays.
In this contribution, I would like to give you a sneak peek behind the curtains of nanomaterial synthesis and show how this material is produced, how to stabilize their structural properties, and assess their toxicity in environmentally relevant conditions. Furthermore, I would like to present a synthesis method to accomplish the last open challenge in display technology of a blue luminescent LED based on QDs by introducing a new element to the InP QDs.
Per- and polyfluoroalkyl substances (PFAS) are a group of anionic, cationic and zwitterionic synthetic products, in which the hydrogen atoms on the carbon skeleton of at least one carbon atom have been completely replaced by fluorine atoms and which include more than 4730 compounds, depending on the definition. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. As a result of the perpetual use of PFAS containing products, effluents and sewage sludge from wastewater treatment plants (WWTPs) have been observed to be an important pathway for PFAS into the environment. In Germany, phosphorus and other nutrients from sewage sludge and wastewater should be recycled in WWTPs of cities with a large population. However, it is not clear if PFAS contamination from wastewater and sewage sludge end up in novel wastewater-based fertilizers. Normally, PFAS are analyzed using PFAS protocols typically with liquid chromatography tandem mass spectrometry (LC-MS/MS) quantification. To get a better overview of the amount of “total PFAS,” we applied sum parameter methods based on combustion ion chromatography (CIC) to screen the PFAS contaminations in various sewage sludge and wastewater-based fertilizers. Furthermore, current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Only a subsequent, high-energy consuming pyrolysis process guarantees the total destruction of all fluorinated organic contaminants. Both approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem.
In this work, synchrotron X-ray refraction radiography (SXRR) was combined with in-situ heat treatment to monitor microstructure and porosity evolution as a function of temperature. The investigated material was a laser powder bed fusion (LPBF) manufactured AlSi10Mg, where the initial eutectic Si network is known to break down into larger particles with increasing temperature. Such alloy is also prone to thermally induced porosity (TIP). We show that SXRR allows detecting the changes in the Si-phase morphology upon heating, while this is currently possible only using scanning electron microscopy. SXRR also allows observing the growth of pores, usually studied via X-ray computed tomography, but on much smaller fields-of-view. Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
X-ray refraction is an excellent tool for the characterization of the microstructure of materials. However, there are only a few (synchrotron) laboratories in the world that use this technique for material characterisation. Therefore, the seminar will first explain the basic principles of X-ray refraction and the measurement techniques installed at the hard X-ray beamline BAMline at BESSY II (Berlin, Germany). This is followed by examples of investigations on fibre-reinforced plastic composites (CFRP) as well as ceramic (Cordierite, ZrO2-SiO2) and metallic materials (Ti-6Al-4V, Inconel). Some of the investigations were carried out both ex-situ and in-situ under mechanical and thermal load. The results are correlated with the mechanical properties of the materials.
In the present talk the basics of the Raman spectroscopy and particularly of Raman microscopy are explained. Advantages and disadvantages of the method are highlighted through selected case studies. In the second part of the lecture examples of correlative imaging with electron, X-ray, ion and optical microscopies from micro- to the nanoscale are highlighted.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
At the end of the article, ideas for solutions are discussed in order to speed up the implementation of new special products from the point of view of process analytics and to network the existing process chains more closely.
The majority of ultrasonic devices used for non-
destructive testing in civil engineering require contact with the
surface of the concrete (specimen), which significantly increases
the time required for the measurement. This makes it impractical
for extensive investigation of large-scale structures such as bridge
decks, foundations, or tunnels.
In a pioneering approach, fluidic oscillators are used as contact
free ultrasonic sources to overcome the aforementioned limi-
tations. These robust and cost-effective actuators require only
pressurised air and are ideally suited for harsh environments. At
a constant supply pressure, they generate a continuous mono-
frequent actuation signal. Further, varying the supply pressure
via a fast pressure regulator was found to generate a frequency
modulated signal which enabled time-of-flight measurement with
an added advantage of increased signal to noise ratio. To
demonstrate the feasibility of this novel idea of non-contact
ultrasound, the results of the initial tests are presented.
One of the most common causes of damage is the ingress of harmful ions into the concrete, which can lead to deterioration processes and affect structural performance. Therefore, the increasingly aging infrastructure is regularly inspected to assess durability. Regular chemical analysis can be useful to determine the extent and evolution of ion ingress and to intervene in a timely manner. This could prove more economical than extensive repairs for major damage, particularly for critical infrastructure. In addition to already established elemental analysis techniques in civil engineering such as potentiometric titration or X-ray fluorescence analysis, laser-induced breakdown spectroscopy (LIBS) can provide further important complementary information and benefits. The possibilities of LIBS are demonstrated using the example of a drill core taken from a parking garage.
Whereas human factors (HF) in the non-destructive testing (NDT) of metallic components are a poorly investigated topic (in comparison to other industrial fields such as aviation), HF in the inspection of concrete components are even less known. Studies have shown that there is always some variability between individuals in their inspection results and that HF affect the reliability of NDT inspections. The aim of the ongoing WIPANO project is to draft a standard for a holistic reliability assessment, with concrete inspection as one case study. This includes also the HF. A human-oriented Failure Modes and Effects Analysis (FMEA) was carried out to do the following: a) identify possible human-related risks in tunnel inspection processes using a laser scan method (including data collection,evaluation, and assessment of tunnel damage) and b) evaluate these human-related risks as regards their possible causes, consequences and probability of occurrence – in addition with respect to existing and possible preventive measures. The results show that the causes for possible failures can lie within people, the physical environment, technology, organisation, and extra-organisational environment. Whereas current preventive measures rely mostly on the individual and quality management practices, there is potential for even larger improvement at the organisational and extra-organisational level. The FMEA results were also used to develop a quantification method to further understand the HF in tunnel inspection, which could possibly be included in the information into the overall reliability assessment. The usage of qualitative and quantitative data collected through the human-FMEA within the proposed quantification method shows promise that HF can be quantified and could offer broader understanding of HF influences on inspection in various industries.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
In addition to already established structural monitoring methods such as deformation, inclination or strain gauges or acoustic emission sensors, sonic or ultrasonic monitoring might provide valuable information about the condition or alteration of a structure. Sensors such as geophones, recording ambient noise in the sonic and subsonic frequency range can provide information beyond modal analysis by using interferometric methods. Wave velocities determined by this method are related to the elastic properties and stiffness of material and structure and can be converted into damage indicators. Embedded active ultrasonic transducer networks can provide more detailed insight about deterioration or damages again, using interferometric technologies. This approach is extremely sensible, detecting relative change in velocity on down to 10-5. These methods, including benefits and remaining challenges, are demonstrated using data from a test structure at BAM’s test site demonstrating the case of prestress loss, and data from an actual bridge still under traffic.
Existing concrete structures were usually designed for lifetimes of several decades. The current and urgently required efforts to increase sustainability and protect the environment will likely result in extended service lives up to 100 years. To achieve such objectives, it is required to assess structures over their entire lifecycles. Non-destructive testing (NDT) methods can reliably support the assessment of existing structures during the construction, operational, and decommissioning phases. One of the most important and safety-relevant components of a prestressed concrete structure are the tendons. NDT methods such as the ultrasonic echo method are suitable for both the detection and the localization of the tendons, i.e., the measurement of their geometrical position inside the component. The uniqueness of structures, concrete heterogeneity, and varying amounts of secondary components such as the reinforcement represent obstacles in the application of these methods in practice. The aim of this contribution is to demonstrate a practicable procedure, that can be used in the field to determine the parameters required for the measuring data analysis without extensive knowledge about the investigated components. For this purpose, a polyamide reference specimen is used to show which steps are required to obtain reliable imaging information on the position of tendons from the measurement data. The procedure is then demonstrated on a concrete test specimen that covers various relevant and practice-oriented test scenarios, such as varying tendon depths and component thicknesses.
Approaches to the development of a (GUM-) measurement model for the calculation of measurement uncertainties in the localization of tendons in concrete structures using the ultrasonic echo method including demonstration were presented.
Imaging of results in NDT-CE: Strength and limitations in the use of Radar vs. Ultrasonic Echo
(2022)
Presentation on behalf of the co-author specified in BAM-Publica.
Study on capabilities of volume methods (GPR, Ultrasonic Echo) regarding lateral and depth localisation of reinforcement and tendons in concrete components. Varied boundary conditions: spacing and diameter of both the near surface rebars of the mesh, and the reflectors of interest, as well as component thickness and concrete cover. Please find corresponding references on slide 2.
Modular production involving benchtop NMR Current Application Examples Driven by Digitalization
(2022)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
In this presentation, I will give a brief overview of my personal experience with laser induced plasma (LIP). I will start from my and colleagues’ early works, where we used LIP as an atomic reservoir for laser induced fluorescence (LIP). We applied LIP-LIF for a sensitive detection of trace elements in various materials and demonstrated that under certain conditions the technique can even be used for isotope analysis. Next, I will discuss the application of LIP spectroscopy, i.e., LIBS, to material identification that nowadays constitutes one of the best applications of this technique. In those early days, we used correlation analysis for spectra processing; it is now replaced by more powerful chemometric methods. Further, I will stop on our efforts in modeling LIP that we first intended for the improved quality of spectroscopic analysis and later extended to non-spectroscopic fields such as chemical vapor deposition and surface structuring. We developed a version of calibration-free LIBS, in which we iterated model-generated spectra until a close match was achieved between experimental and synthetic spectra to determine concentrations. Next, I will briefly overview our recent developments in plasma modeling that include plasma chemistry. This was important in view of widening application of LIBS as a molecular technique. I will also address several plasma diagnostics, e.g., Radon transform tomography that we developed to get more insight about LIP that was helpful for both analytic spectroscopy and modeling. Finally, I will mention several exotic applications of LIP such as LIP-based lasers and chemical reactors to illustrate a real multifaceted character of laser induced plasma and usefulness of its study for many science fields.
Back Deposition of Titanium Oxides under Laser Ablation of Titanium: Simulation and Experiment
(2022)
Titanium is widely used in medicine for implants and prostheses, thanks to its high biocompatibility, good mechanical properties, and high corrosion resistance. Pure titanium, however, has low wear resistance and may release metallic titanium into surrounding tissues. Structuring and coating its surface with oxide layers are necessary for high wear resistance and improved biocompatibility. In this work, a combination of theoretical and experimental methods was used to study processes responsible for deposition of titanium oxides during ablation of titanium in air.
The deposition process was modeled via the Navier-Stokes equations that accounted for the material removal and accumulation of the deposit on the ablation surface. The chemical part was based on the equilibrium model embedded into the hydrodynamic code. Simulations showed that the most active zone of production of condensed titanium oxides were at plasma periphery whereas a zone of strong condensation of titanium metal was above the molten pool.
In experiment, a pulsed Yb fiber laser was scanned across a titanium surface. The temperature and composition of the plasma were inferred from plasma emission spectra. The post-ablation surface was analyzed by SEM, TEM, STEM, AFM, and XRD.
The developed model well reproduced the main features of experimental data. It was concluded that the deposition of condensed metal oxides from the plasma is a principal mechanism of formation of nanoporous oxide layer on the metal surface. The method of surface structuring and modification by nanosecond laser ablation can be developed into a useful technology that may find applications in medicine, photonics, and other areas.
Inductively coupled plasma-time of flight-mass spectrometry (ICP-ToF-MS) enables the analysis of the multi-element fingerprint of individual cells due to a (quasi-)simultaneous detection of about 70 elements of the periodic table. The interface between material and environmental analysis thus receives special attention, e.g., when considering corrosion processes. Microbiologically influenced corrosion (MIC) is a highly unpredictable phenomenon due to the influence of the environment, microbial communities involved and the respective electron source. However, the interaction pathway between cells and the metal surface remains unclear. The development of the MIC-specific ICP-ToF-MS analytical method presented here, in combination with the investigation of steel-MIC interactions, contributes significantly to progress in instrumental MIC analysis and will enable clarification of the processes taking place. For this, a MIC-specific staining procedure was developed which ensures the analysis of intact cells. It allows the studies of archaea at a single cell level which is extremely scarce compared to other well characterized organisms. Additionally, the single cell ICP-ToF-MS is used for the analysis of archaea involved in MIC of steel. Hence, the possible uptake of individual elements from different steel samples is investigated - the information obtained will be used in the future to elucidate underlying mechanisms and develop possible material protection concepts, thus combining modern methods of analytical sciences with materials research.
Raman microspectroscopy enables imaging of the distributions of mineral phases as well as physical properties of materials, such as crystal orientations and crystallinities, with down to sub-micrometre resolution. In a combination with other spectroscopic and microscopic techniques, this approach was applied to the analysis and elucidation of ancient production technologies of stucco fragments made of high-fired gypsum mortar and Egyptian blue pigment discovered on a monochrome wall painting fragment originating from the Early Medieval (5th/6th century AD) construction phase of the church St. Peter above Gratsch in South Tyrol (Northern Italy).
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Nuclear magnetic resonance (NMR) with focus on 1H protons is increasingly applied for non-destructive testing applications. Besides mobile NMR, laboratory devices such as the NMR core-analyzing tomograph are used. As their magnetic field is more homogeneous, they enable measurements with higher signal-to-noise ratios (SNR), but with limited sample sizes. The tomograph presented here (8.9 MHz) was constructed for a maximum sample diameter of 70 mm and length of up to 1 m. The resolution, the echo time (min. 50 µs), the SNR and the measurement type can be adjusted by means of exchangable coils. The tomograph enables measurements along the complete sensitive length, slice-selective and even 2- or 3-dimensional measurements. A movable sample lifting system thereby allows a precise positioning of the sample.
Geophysical methods are able to contribute significantly to geotechnical site characterization. In-situ parameters are collected and gaps between boreholes or other direct tests are filled with information. However the limited resolution has to be considered and the indirect geophysical parameters have to be translated into something geotechnically useful. Moreover, the limitations have to be evaluated when including geophysical data into geostatistical models. If done properly, the use of geophysics will help in an efficient and effective site characterization. A comprehensive overview on existing geophysical (mostly seismic) methods is given as well as information on the calibration of geophysical against geotechnical parameters, pitfalls and limitations and some hints how to include these data into geostatistical/geotechnical models.
The climate and energy crisis are extreme challenges. One possible solution could be hydrogen technology. Safety is a big concern. Steel used for pipelines and storage is under permanent stress from low temperatures and high pressures. The content of different alloyed metals determines the performance of the steel. Nitrogen microwave inductively coupled atmosphere pressure plasma mass spectrometry (N2-MICAP-MS) is a promising method for trace metal analysis in steel. Nitrogen is cheap and can be generated on site. It has fewer interferences than argon. Additionally, MICAP-MS is very matrix tolerant, proving the matrix-matched calibration expendable. Safety in technology and chemistry is the mission of BAM. Providing reference methods and materials can create trust in future technologies like hydrogen.
Per- and polyfluorinated alkyl substances (PFASs) are a group of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their various chemical and physical properties as well as the high number of compounds. 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 realistic PFAS pollution levels.
PFAS sum parameters display 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 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 present an improved method for the determination of PFASs using HR-CS-GFMAS via GaF detection. The optimized method includes a Ga pretreatment as described by Gawor et al. resulting in overall lower detection limits. Furthermore, during optimization the influence of species-specific responses during HR-CS-GFMAS analysis was reduced resulting in a more accurate determination of PFAS sum parameters. To test the applicability of the improved method, we analyzed soil samples from a former fire-fighting training area combining the improved method for detection with our previously optimized extraction method for EOF determination in soils.
Per- and polyfluorinated alkyl substances (PFASs) are a group of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their various chemical and physical properties as well as the high number of compounds. 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 realistic PFAS pollution levels.
PFAS sum parameters display 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 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 present an improved method for the determination of PFASs using HR-CS-GFMAS via GaF detection. The optimized method includes a Ga pretreatment as described by Gawor et al. resulting in overall lower detection limits. Furthermore, during optimization the influence of species-specific responses during HR-CS-GFMAS analysis was reduced resulting in a more accurate determination of PFAS sum parameters. To test the applicability of the improved method, we analyzed soil samples from a former fire-fighting training area combining the improved method for detection with our previously optimized extraction method for EOF determination in soils.
How much do we, the small-angle scatterers, influence the results of an investigation? What uncertainty do we add by our human diversity in thoughts and approaches, and is this significant compared to the uncertainty from the instrumental measurement factors?
After our previous Round Robin on data collection, we know that many laboratories can collect reasonably consistent small-angle scattering data on easy samples1. To investigate the next, human component, we compiled four existing datasets from globular (roughly spherical) scatterers, each exhibiting a common complication, and asked the participants to apply their usual methods and toolset to the quantification of the results https://lookingatnothing.com/index.php/archives/3274).
Accompanying the datasets was a modicum of accompanying information to help with the interpretation of the data, similar to what we normally receive from our collaborators. More than 30 participants reported back with volume fractions, mean sizes and size distribution widths of the particle populations in the samples, as well as information on their self-assessed level of experience and years in the field.
While the Round Robin is still underway (until the 25th of April, 2022), the initial results already show significant spread in the results. Some of these are due to the variety in interpretation of the meaning of the requested parameters, as well as simple human errors, both of which are easy to correct for. Nevertheless, even after correcting for these differences in understanding, a significant spread remains. This highlights an urgent challenge to our community: how can we better help ourselves and our colleagues obtain more reliable results, how could we take the human factor out of the equation, so to speak?
In this talk, we will introduce the four datasets, their origins and challenges. Hot off the press, we will summarize the anonymized, quantified results of the Data Analysis Round Robin. (Incidentally, we will also see if a correlation exists between experience and proximity of the result to the median). Lastly, potential avenues for improving our field will be offered based on the findings, ranging from low-effort yet somehow controversial improvements, to high-effort foundational considerations.
Measuring an X-ray scattering pattern is relatively easy, but measuring a steady stream of high-quality, useful patterns requires significant effort and good laboratory organization.
Such laboratory organization can help address the reproducibility crisis in science, and easily multiply the scientific output of a laboratory, while greatly elevating the quality of the measurements. We have demonstrated this for small- and wide-angle X-ray scattering in the MOUSE project (Methodology Optimization for Ultrafine Structure Exploration).
With the MOUSE, we have combined a comprehensive and highly automated laboratory workflow with a heavily modified X-ray scattering instrument. This combination allows us to collect fully traceable scattering data, within a well-documented, FAIR-compliant data flow (akin to what is found at the more automated synchrotron beamlines). With two full-time researchers, our lab collects and interprets thousands of datasets, on hundreds of samples, for dozens of projects per year, supporting many users along the entire process from sample selection and preparation, to the analysis of the resulting data.
This talk will briefly introduce the foundations of X-ray scattering, present the MOUSE project, and will highlight the proven utility of the methodology for materials science. Upgrades to the methodology will also be discussed, as well as possible avenues for transferring this holistic methodology to other instruments
Per- and polyfluoroalkyl substances (PFAS) are anionic, cationic and zwitterionic synthetic products, in which the hydrogen atoms on the carbon skeleton of at least one carbon atom have been completely replaced by fluorine atoms (see Figure 1) and which include more than 4730 compounds, depending on the definition. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. Furthermore, because of the continuous contamination through PFAS containing commercial products, effluents and sewage sludge from WWTPs have been shown to be an important source of PFAS discharge into the aquatic environment. In the last few years, legacy PFAS (≥C4) have been found in various environments, including soil, water and wastewater, and their environmental pathways have been partly described. To get a better
overview of the amount of “total PFAS,” sum parameter methods like total oxidizable precursor (TOP) assay and methods based on combustion ion chromatography (CIC) are in development. CIC results in data regarding the sum of absorbable organic fluorine (AOF) or extractable
organic fluorine (EOF), which can also quantify other organically bound fluorine compounds such as fluorinated pesticides and pharmaceutical. Additionally, for research purpose several spectroscopical methods like X-ray photoelectron spectroscopy (XPS), fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy, particular induced gamma-ray emission (PIGE) spectroscopy and 19F nuclear magnetic resonance (NMR) spectroscopy are available. Therefore, an overview is given on various analytical techniques for PFAS in environmental samples and their application possibilities discussed for different kind of PFAS compounds
Per- and polyfluoroalkyl substances (PFAS) are a large group of anionic, cationic, or zwitterionic organofluorine surfactants used in the formulations of thousands of products and consumer goods, including aqueous film-forming foams (AFFF) used to suppress aviation fires in training scenarios, non-stick cookware, fast-food wrappers, water-repellent fabrics, medical equipment. Because PFAS have been extensively used in a variety of AFFF products they can be found in soils from industrial and military installations. Current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Only a subsequent, high-energy consuming pyrolysis process guarantees the total destruction of all fluorinated organic contaminants. Both approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Previously, mechanochemical treatment of polychlorinated organic compounds in soils showed an efficient dechlorination. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination with gas chromatography mass spectrometry (GCMS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), respectively, as well es the fluoride mineralization by ion chromatography (IC) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
Analytical Challenges for PFAS in Environmental Samples - Methods, Approaches and Applicability
(2022)
Per- and polyfluoroalkyl substances (PFAS) are anionic, cationic and zwitterionic synthetic products, in which the hydrogen atoms on the carbon skeleton of at least one carbon atom have been completely replaced by fluorine atoms and which include up to 1.7 M compounds, depending on the definition. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. Furthermore, because of the continuous contamination through PFAS containing commercial products, effluents and sewage sludge from WWTPs have been shown to be an important source of PFAS discharge into the aquatic environment. In the last few years, legacy PFAS (≥C4) have been found in various environments, including soil, water and wastewater, and their environmental pathways have been partly described.
Several long-chain PFAS species, and their respective salts are considered as persistent organic pollutants by the United Nations Stockholm Convention. These pollutants have been linked to altered immune and thyroid function, liver disease, lipid and insulin dysregulation, kidney disease, adverse reproductive and developmental outcomes, and cancer. A significant shift in the chemical industry towards production of short (C4-C7) and ultrashort (C1-C3) alternatives was observed in response to recently intensified regulations and restrictions on the use of long-chain (≥C8) PFAS. PFAS analysis in environmental samples is currently mainly done by liquid chromatography tandem mass spectrometry (LC-MS/MS). This efficient method is conducted in a targeted fashion analyzing a small subset of PFAS. The US EPA method for analysis of PFAS using LC-MS/MS for example currently lists 40 PFAS (≥C4). However, to get a better overview of the amount of “total PFAS,” sum parameter methods like total oxidizable precursor (TOP) assay and methods based on combustion ion chromatography (CIC) are in development. CIC results in data regarding the sum of absorbable organic fluorine (AOF) or extractable organic fluorine (EOF), which can also quantify other organically bound fluorine compounds such as fluorinated pesticides and pharmaceutical. Moreover, non-target and suspect screening mass spectrometry can be used to identify novel emerging PFAS and partly unknown fluorinated compounds in environmental samples. Furthermore, to analyze ultrashort PFAS (C1-C3), supercritical fluid chromatography (SFC), hydrophilic interaction chromatography (HILIC) and gas chromatography-mass spectrometry (GC-MS) are available, but further research is needed to develop reliable and accurate methods to quantify several ultrashort PFAS in environmental samples.
Additionally, for research purpose several spectroscopical methods like X-ray photoelectron spectroscopy (XPS), fluorine K-edge X-ray absorption near-edge structure (XANES)spectroscopy, particular induced gamma-ray emission (PIGE) spectroscopy and 19F nuclear magnetic resonance (NMR) spectroscopy are available.
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Since 1997, the Committee for Health-related Evaluation of Building Products (AgBB) has been developing the basis for building regulations for protection against indoor health risks that may arise when building products are used. In 2009, the AgBB decided to include relevant VVOCs in the assessment procedure. The ISO 16000-6 (2021) states that the use of the thermal desorption gas chromatography technique is appropriate for VVOCs, if adaptations are considered. However, a suitable method for the trustworthy quantification of VVOC emissions from building products and in the indoor air is still missing.
This webinar will present the results of a research project on the development of a procedure for VVOC analysis:
• identification of the gaps towards standardization
• investigations on gas standards and the suitability of chromatography columns
• investigations on sorbent combinations and water management
• validation of the method and screening of VVOC emissions from building products.
Isotope reference materials
(2022)
The variation of isotope ratios is increasingly used to unravel natural and technical questions. In the past, the investigation and interpretation of such variations was the field of a limited number of experts. With new upcoming techniques and research topics in the last decades, such as provenance or food authenticity studies, the number of published isotope data strongly increased. Instrumental developments such as the enhancement of inductively coupled plasma mass spectrometers (ICP-MS) from an instrument for simple quantitative analysis to highly sophisticated isotope ratio machines influenced this process significantly. While in former times only experts in mass spectrometry were able to produce reliable isotope data, nowadays many laboratories, never been in touch with mass spectrometry before, produce isotope data with an ICP-MS. Isotope reference materials (iCRM) are indispensable to enable a reliable method validation or in rare cases even SI-traceability. The fast development and the broad availability of ICP-MS also lead to an expansion of the classical research areas and new elements are under investigation. Irrespective of the investigated element or the knowledge of the user all isotope ratio applications require reference materials either for correction of instrumental isotope fractionation, for method validation or to provide a common accepted basis as needed for delta measurements. This presentation will outline the basic principles and illustrate the urgent need for new iCRMs. Consequently, the production and certification of iCRMs will be discussed and illustrated by examples of already completed certification projects. Finally, plans for future iCRMs to be produced at BAM will be presented.
Concrete structures often show severe damage during their lifetime. One such damage is pitting corrosion of the steel reinforcement caused by chloride ingress into the porous concrete structure. Laser-induced breakdown spectroscopy (LIBS) is a promising method in civil engineering, which is used for detection of chlorine in concrete structures in addition to conventional methods of wet chemistry. To assess LIBS as a trustful analytical technique, its accuracy and robustness is carefully tested. The presentation will outline the results of the interlaboratory comparison of chlorine quantification in cement paste samples, which was carried out by 12 laboratories in 10 countries. Two sets of samples with chloride content ranging from 0.06-1.95 wt.% in the training set and 0.23-1.51 wt.% in the test sample set (“unknowns”), with additional variations in the type of cement and chlorine source (salt type) were sent to the laboratories. The overall result demonstrates that LIBS is suitable for the quantification of the investigated sample compositions: average relative bias was mostly below 15 %. Considering that the laboratories did not receive instructions on how to perform the analysis or how to process the data, the results can be evaluated as a true status quo of the LIBS technique for this type of analysis.
Modeling is an important tool for understanding a physical phenomenon. It helps to interpret results of experiments and optimize experimental parameters for obtaining a desirable result. Modeling laser induced plasma is beneficial for many scientific and industrial fields, e.g., analytical chemistry, pulsed laser deposition, plasma enhanced chemical vapor deposition, laser welding, additive manufacturing etc. In this presentation, a personal experience in development of a physical model of laser induced plasma will be given in a chronological sequence starting from early 2000th and until now.
Over the time, the model evolved from its simple analytical form that described plasma emission spectra to its current numerical form that describes plasma dynamics, chemistry, and interaction with a substrate surface. Several examples will be given for the application of the model to practical problems such as spectroscopic chemical analysis, plasma enhanced chemical vapor deposition, and surface modification by laser ablation.
The composition of thin films of polymer blends in vertical direction is still under discussion. For explaining the thickness dependence of some properties like the thermal glass transition temperature, a three-layer model has been introduced consisting of an adsorbed layer with a reduced segmental mobility at the substrate, a bulk-like layer in the middle of the film and an outermost surface layer with a higher molecular mobility. X-ray photoelectron spectroscopy (ER-XPS) measurements with a varying excitation energy from 400 eV to 1486.6 eV and, herewith, an information depth from 1.5 nm to 10 nm were performed at PVME/PS films with compositions of 25/75 wt% and 50/50 wt% and thicknesses between 15 nm and 190 nm. As expected, it was found that the PVME concentration decreases with increasing information depth. Secondly, a complex correlation between the PVME concentration at the surface and the film thickness was found. The PVME concentration increases with decreasing film thickness until a maximum at 30 nm. For thinner films, the PVME concentration decreases. These data agree with previous investigations obtained with specific heat spectroscopy.
We thank BESSY II (HZB) for the allocation of beamtime at the HE-SGM beamline and for technical support. DFG (Project number 124846229) is acknowledged for financial support.
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.
Engineered nanomaterials (NM) with their unique size-dependent properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing and electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties. Especially, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups and ligands, is an important key driver for the performance, stability, and processibility of NM, as well as their interaction with the environment. Thus, methods for functional group quantification can foster the sustainable development of functional and safe(r) NM.
Aiming at the development of simple, versatile and multimodal tools for the quantification of common bioanalytically relevant functional groups, we designed a catch-and-release assay based on cleavable probes that enable the quantification of the cleaved-off reporters in the supernatant after particle separation. Thus, the approach circumvents interferences resulting from particle light scattering and sample-inherent absorption or emission. To study the potential of the assay, commercially available and in-house synthesized aminated and carboxylated polymer and silica nanoparticles of different functional group densities were tested.
Our cleavable probe strategy can be easily adapted to other analytical techniques requiring different reporters, or to different types of linkers that can be cleaved thermally, photochemically, or by variation of pH, utilizing well-established chemistry. In addition, it can contribute to the development of multi-method characterization strategies to provide a more detailed picture of the intrinsic physicochemical property - performance/safety relationships and thus can support the design of tailored nanomaterials with better controlled properties.
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.
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.
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.
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.
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.
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 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).
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.
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.
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.
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.
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.
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.
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 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.
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.