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In the interest of exploring their potential in the field of single particle analysis, a Microdroplet Generator (MDG) was coupled to an ICP-ToF-MS.
Isotopic Dilution Analysis was also incorporated for the size determination of three different Platinum Nanoparticles samples (50, 63 and 70 nm). The performance of the technique was validated by comparison to traditional size characterization techniques (sp-ICP-ToF-MS, TEM), while the robustness of the technique was proven by incorporating NaCl in the samples’ matrix, up to 100 mg/L.
LIBS is a complementary method to XRF and can detect all elements without the need for vacuum conditions. Automated systems are already commercially available capable of scanning surfaces with a resolution of up to 0.1 mm within a few minutes. In addition to possible applications in R&D, LIBS is also used for practical applications in building materials laboratories and even on-site.
In view of ageing infrastructure facilities, a reliable assessment of the condition of concrete structures is of increasing interest. For concrete structures, the ingress of potential harmful ions is affecting the serviceability and eventually structural performance. Pitting corrosion induced by penetrating chlorides is the dominant deterioration mechanism. Condition assessment based on frequently performed chloride profiling can be useful to identify the extent and evolution of chloride ingress. This could prove to be more economical than extensive repairs, especially for important infrastructure facilities.
Currently the most common procedure for determining the chloride content is wet chemical analysis with standard resolution of 10 mm. The heterogeneity is not considered. LIBS is an economical alternative for determining the chloride content at depth intervals of 1 mm or less. It provides 2D distributions of multiple elements and can locate spots with higher concentrations. The results are directly correlated to the mass of binder and can also be performed on-site with a mobile LIBS-System.
The application of a LIBS-system is presented. Calibration is required for quantitative analysis. Concrete cores were drilled, sliced and analyzed to determine the 2D-distribution of harmful elements. By comparing the chloride ingress and the carbonation, the interaction of both processes can be visualized in a measurement that takes less than 10 minutes for a 50 mm x 100 mm drill core.
A leaflet on the use of LIBS for the chloride ingress assessment has been completed.
In many scientific fields, isotopic analysis can offer valuable information, e.g., for tracing the origin of food products, environmental contaminants, forensic and archaeological samples (provenance determination), for age determination of minerals (geochronological dating) or for elucidating chemical processes. Up to date, typically bulk analysis is aimed at measuring the isotopic composition of the entire elemental content of the sample. However, the analyte element is usually present under the form of different elemental species. Thus, separating species of interest from one another and from matrix components prior to isotope ratio measurements can provide species-specific isotopic information, which could be used for tracing the origin of environmental pollutants and elucidation of (environmental) speciation. Using on-line hyphenations of separation techniques with multicollector-ICP-MS (MC-ICP-MS) can save time and effort and enables the analysis of different species during a single measurement.
In this work, we developed an on-line hyphenation of CE with multicollector-ICP-MS (CE/MC-ICP-MS) for isotopic analysis of sulfur species. With this method, the isotopic composition of sulfur in sulfate originating from river water could be analyzed without sample preparation. The results were compared with data from off-line analysis of the same samples to ensure accuracy. The precision of the results of the on-line measurements was high enough to distinguish the rivers from one another by the isotopic signature of the river water sulfate. Next to environmental applications, a current field is species-specific isotopic analysis of biomolecules, as sulfur is the only covalently bound constituent of proteins which can be analyzed by MC-ICP-MS. Data analysis of transient signals in terms of isotope ratio determination is further issue - we developed a small free accessible App allowing for fast data analysis taking relevant aspects (e.g., mass bias correction, peak picking, …) into account.
Due to the ageing of the infrastructure facilities, a reliable assessment of the condition of concrete structures is of great interest to plan timely and appropriate measures. In concrete structures, pittingcorrosion of the reinforcement is the predominant deterioration mechanism affecting serviceability and eventually structural performance. Determination of quantitative chloride ingress is not only necessary to obtain valuable information on the current condition of a structure, but the data obtained can also be used to predict future developments and the associated risks. An overview of the progress and the possibilities of the application of laser-induced breakdown spectroscopy for concrete analysis in daily civil engineering practice is given. High-resolution 2D measurements of drill cores to determine the penetration of harmful species into concrete is presented. Furthermore, the application of a mobile LIBS system in a parking garage is shown. The system consists of a diode-pumped low-energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A scanner allows two-dimensional element mapping. Progress towards the establishment of LIBS in a leaflet for the analysis of chlorine ingress into concrete in civil engineering is presented.
The main application of LIBS in civil engineering is the detection of harmful ions in concrete, which can penetrate the component through the porous concrete structure. The advantages of LIBS over standard methods are the possibility of multi-element analysis, measurement speed, spatially resolved measurements, and minimal sample preparation. The spatially resolved measurements of LIBS allow the assessment of the heterogeneity of the concrete by measuring separately the chemical composition of the aggregates and the binder matrix. The latter is particularly relevant because the determined elemental distribution can be directly related to the binder matrix. This is not possible with standard methods, since the material is homogenized to powder during sample preparation stage and the determined concentration is thus related to the total mass. In addition to the use of LIBS for the specific analysis of individual harmful ions, LIBS can also be used to estimate the concrete composition and thus determine, for example, the type of cement used. Corresponding information are relevant for the estimation of the remaining service life and for the preparation of a maintenance concept. In recent years, LIBS has been increasingly used in civil engineering. Currently, however, it is primarily used in research institutions and only occasionally in building materials laboratories. Special commercial devices have also been developed, which greatly simplify the application due to the high degree of automation. Mobile LIBS systems allow on-site application. A central point, which limits the use of LIBS in the commercial sector, is the lack of norms and standards. Therefore, within the framework of a project funded by the German government, work has been carried out on the preparation of a leaflet on quantitative chlorine determination in concrete, which will be published this year. In interlaboratory comparisons the robustness and accuracy for the practical application was demonstrated. LIBS also has great potential in the recycling of construction waste in conjunction with hyperspectral sensors. This issue is currently being addressed in a national project. During the presentation, the state of the art of LIBS in civil engineering will be presented, next steps will be discussed, and future challenges will be outlined.
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).