Analytische Chemie
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Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (38)
- 8 Zerstörungsfreie Prüfung (27)
- 6 Materialchemie (18)
- 1.8 Umweltanalytik (10)
- 8.5 Röntgenbildgebung (10)
- 6.1 Oberflächen- und Dünnschichtanalyse (9)
- 1.1 Anorganische Spurenanalytik (6)
- 1.2 Biophotonik (6)
- 4 Material und Umwelt (6)
- 6.3 Strukturanalytik (6)
- 1.4 Prozessanalytik (5)
- 1.9 Chemische und optische Sensorik (5)
- 8.0 Abteilungsleitung und andere (5)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (5)
- 8.2 Zerstörungsfreie Prüfmethoden für das Bauwesen (5)
- VP Vizepräsident (5)
- VP.1 eScience (5)
- 6.6 Physik und chemische Analytik der Polymere (4)
- 8.4 Akustische und elektromagnetische Verfahren (4)
- 1.6 Anorganische Referenzmaterialien (3)
- 1.7 Organische Spuren- und Lebensmittelanalytik (3)
- 4.2 Material-Mikrobiom Wechselwirkungen (3)
- 1.5 Proteinanalytik (2)
- 1.3 Instrumentelle Analytik (1)
- 3 Gefahrgutumschließungen; Energiespeicher (1)
- 3.5 Sicherheit von Gasspeichern (1)
- 4.1 Biologische Materialschädigung und Referenzorganismen (1)
- 4.3 Schadstofftransfer und Umwelttechnologien (1)
- 4.5 Kunst- und Kulturgutanalyse (1)
- 8.6 Faseroptische Sensorik (1)
We interpret solving the multi-vehicle routing problem as a team Markov game with partially observable costs. For a given set of customers to serve, the playing agents (vehicles) have the common goal to determine the team-optimal agent routes with minimal total cost. Each agent thereby observes only its own cost. Our multi-agent reinforcement learning approach, the so-called multi-agent Neural Rewriter, builds on the single-agent Neural Rewriter to solve the problem by iteratively rewriting solutions. Parallel agent action execution and partial observability require new rewriting rules for the game. We propose the introduction of a so-called pool in the system which serves as a collection point for unvisited nodes. It enables agents to act simultaneously and exchange nodes in a conflict-free manner. We realize limited disclosure of agent-specific costs by only sharing them during learning. During inference, each agents acts decentrally, solely based on its own cost. First empirical results on small problem sizes demonstrate that we reach a performance close to the employed OR-Tools benchmark which operates in the perfect cost information setting.
Hybrid optical measurement technique for detection of defects in epitaxially grown 4H-SiC layers
(2022)
Recent developments in power electronics require the use of new wide bandgap compound semiconductors. Silicon carbide (SiC) is one of the most promising materials for power electronics due to its outstanding properties and commercial availability. Some types of defects in the SiC substrates or homoepitaxial SiC layers can affect the performance of electronic devices in a serious manner or make its operation even impossible. Optical methods such as imaging ellipsometry (IE) and white light interference microscopy (WLIM) were applied for fast and non-contact investigation of defects in the epitaxially grown 12 µm 4H-SiC layers on 4H- SiC substrates.
Ellipsometry enables the investigation of material properties over a broad spectral range. As a fast and non-destructive method, it is widely used in industry for quality assurance. Despite the wide application of ellipsometry and its high industrial relevance there are some material-specific standards and there have been no generally accepted standards dealing with model validation and measurement uncertainties. The first German standard DIN50989-1: 2018 Ellipsometry – Part1: Principles (currently international standard ISO 23131: 2021) marks the beginning of a 6-part standard series for ellipsometry, which was developed under consideration of GUM.
Introduction:
With the introduction of accurate deep learning predictors, spectral matching applications might experience a renaissance in tandem mass spectrometry (MS/MS) driven proteomics. Deep learning models, e.g., Prosit, predict complete MS/MS spectra from peptide sequences and give the unprecedented ability to accurately predict mass spectra that may arise from any given proteome. However, the amount of spectral data is enormous when querying large search spaces, e.g., metaproteomes composed of many different species.
Current spectral library search software, such as SpectraST, is not equipped to meet run time and memory constraints imposed by such large MS/MS databases, covering several millions of peptide spectrum predictions.
Methods:
Inspired by the fragment index data structure that had been introduced with MSFragger, we implement an efficient peak matching algorithm for computing spectral similarity between query and library spectra. Mistle (Metaproteomic index and spectral library search engine) uses index partitioning and SIMD (Single instruction, multiple data) intrinsics, which greatly improves speed and memory efficiency for searching large spectral libraries. Mistle is written in C++20 and highly parallelized.
Results:
We demonstrate the efficiency of Mistle on two predicted spectral libraries for the lab-assembled microbial communities 9MM and SIHUMIx. Compared to the spectral library search engine SpectraST, Mistle shows a >10-fold runtime improvement and is also faster than msSLASH, which uses locality-sensitive hashing. Although Mistle is slower than MSFragger, Mistle‘s memory footprint is an order of magnitude smaller. Furthermore, we find evidence that the spectral matching approach to predicted libraries identifies peptides with higher precision. Mistle detects peptides not found by database search via MSFragger and in turn uncovers unnoticed false discoveries among their matches.
Conclusion:
In this study, we show that predicted spectral libraries can enhance peptide identification for metaproteomics. Mistle provides the means to efficiently search large-scale spectral libraries, highlighted for the microbiota 9MM and SIHUMIx.
In order to detect small and hidden material defects or micro-cracks, weak and localized magnetic stray fields need to be detected and characterized on the magnetic surface. Current flux leakage sensor elements are rigid and rely on air gaps to detect stray fields several hundred micrometers above the surface. Furthermore, the increasing complexity of critical components, enabled by novel fabrication technologies, primarily additive manufacturing, poses a significant challenge to the available flux leakage testing technologies.
The emergence of flexible magneto-electronics paves the way to a compliant form of magnetic sensors that, on one hand, are able to adapt to highly curved surfaces, allowing these measurements to be conducted on irregularly formed components, which are inaccessible for nowadays electromagnetic NDT equipment and, on the other hand, could enhance the detection limit for small magnetic stray fields, by allowing the magneto-sensitive elements to approximate the object’s surface until only a few µm, mediated by thin and flexible packaging.
Mycotoxins (toxic compounds formed by fungi) in food and feed have caused problems for mankind since the beginning of time. The group of ergot alkaloids plays a special role in human history. Several tens of thousands of deaths during the middle ages caused by to ergotism (the disease caused by continuous intake of ergot alkaloid contaminated food) underscore the importance of reliable analytical methods to ensure food safety.
More than 50 compounds belong to the group of ergot alkaloids. The 12 most found structures – the major ergot alkaloids – are typically measured, when it comes to ergot alkaloid quantification. High performance liquid chromatography (HPLC) with a fluorescence detector (FLD) is typically used to quantify the ergot alkaloid content. The main disadvantage of this method are the high costs for calibration standards (12 different calibration substances are required). But also, the time and effort required for the analysis of 12 peaks and overlapping signals that occur in complex food samples such as bread. As all ergot alkaloids share the ergoline structure and just differ in the substituents attached to this backbone, measurement of all ergot alkaloids in one sum parameter presents a time and cost saving alternative. The most important step for the development of such a sum parameter method is the reaction used to transfer all ergot alkaloids to one uniform structure. Two promising reactions, the acidic esterification to lysergic acid methyl ester and hydrazinolysis to lysergic acid hydrazide, were examined for possible use in a routine analysis method. In addition to yield and reaction rate, factors such as handling of the reaction and the possibility of parallel sample workup play a role.
A recent upgrade of key equipment of the BAMline widens its imaging capabilities: shorter scan acquisition times are now possible, in situ and operando studies can now be routinely performed, and different energy spectra can easily be set up. In fact, the upgraded double-multilayer monochromator brings full flexibility by yielding different energy spectra to optimize flux and energy resolution as desired.
Deciphering microbiological influenced corrosion processes on steel with single cell-ICP-ToF-MS
(2022)
Microbiologically influenced corrosion (MIC) is a highly unpredictable process dictated by the environment, microorganisms, and the respective electron source. Interaction pathways between cells and the metal surface remain unclear. The development of this novel single cell-inductively coupled plasma-time of flight-mass spectrometry analytical method and a MIC-specific staining procedure facilitate the investigation of steel-MIC interactions. With this it is possible to analyze the multi-elemental fingerprint of individual cells. The detection method revealed elemental selectivity for the corrosive methanogenic archaeal strain Methanobacterium-affiliated IM1. The interface between material and environmental analysis thus receives special attention, e.g., when considering MIC on solid steel. Hence, the possible uptake of individual elements from different steel samples is investigated. Results showed the cells responded at a single-cell level to the different types of supplemented elements and displayed the abilities to interact with chromium, vanadium, titanium, cobalt, and molybdenum from solid metal surfaces. 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.
References.
Direct detection of glyphosate in water with fluorescent molecularly imprinted polymer particles
(2022)
Analysis of environmental contaminants such as pesticides is increasing in importance due to frequent detection of residues in water reserves and food stuff, as well as lowering of maximum residue levels (MRLs). Molecularly imprinted polymers (MIPs) have been developed for preconcentration of these analytes prior to analysis by chromatographic techniques [1]. MIPs are prepared by polymerization of monomers in a matrix containing the analyte, followed by extraction of the analyte to obtain binding sites that are complementary to the analyte of interest. Recently, our group developed MIPs containing fluorescent reporter molecules that can be used for direct detection and quantification of 2,4-D in contaminated water. Core/shell MIP particles were employed, consisting of sub-micron silica nanoparticles coated with a MIP shell containing a fluorescent reporter whose signal was enhanced upon binding with 2,4-D in water. A limit of detection of 20 nM was attained [2]. We present here a comparable system, composed of fluorescent core-shell MIPs for the direct analysis of pesticides in environmental samples.
Perfluorocarboxylic acids (PFCAs) are a family of compounds that consist of a fully perfluorinated carbon backbone and a carboxylic acid moiety1. PFCAs have been classified as substances of very high concern by REACH regulations due to their persistence in the environment, non biodegradability and toxicological effects2. Thus, there is significant interest in detecting PFCAs in ground, waste, surface and drinking water. Fluorescence detection is a portable, easy-to-operate and cost-effective alternative, enabling the onsite detection of these analytes e.g., with miniaturized fluidic sensors.
Here, a guanidine benzoxadiazole (BD) dye covalently attached to a polymerizable methacrylate unit was developed for the integration of the dye into polymers and on surfaces. The response behavior of the dye toward PFCAs was assessed in monophasic (EtOAc) and biphasic (EtOAc-H2O) solvent systems, the biphasic system being advantageous for the extraction of the hydrophobic organic acids from the aqueous phase.
The BD dye was integrated into sensory silica core-polymer shell particles for the sensing of PFCAs directly in aqueous media. Submicron SiO2 particles were functionalized with 3 (trimethoxysilyl)propyl methacrylate followed by radical polymerization with the BD dye and ethylene glycol dimethacrylate. TEM images showed a homogeneous polymer shell with a thickness of 75±2 nm.
By incorporating the BD dye into core-shell particles, lower limits of detection (1.52 µM for perfluorooctanoic acid, PFOA) were achieved if compared to the use of the neat BD dye in a biphasic assay (17.3 µM for PFOA), and excellent discrimination against inorganic acids thanks to the hydrophobic polymer shell. The particle sensory platform has proven to be an alternative for the sensing of PFCAs directly in water.
Mechanochemistry offers a unique opportunity to modify or synthesize new crystal forms. Although the method is very promising, little is known about the mechanochemical means to control the synthesis of a solid form. Using an polymorphic organic cocrystal system, we show here that mechanochemistry can be used to obtain a polymorph transformation under the apparently conventional (thermal) transition point.
In many cases, science falls back on self-developed prototype systems, which are used and developed for the measurement and execution of the tasks. About 80 % of the development is based on the same hardware design, which is used in only one application scenario and then discarded. For the most part, there are also uncalibrated sensors, since it is costly to calibrate a complicated sensor measurement system or the entire measurement chain since access to the sensor systems is not always available. This paper describes a conceptual design to implement a versatile sensor system with the motivation to fuse the data recording and data reception, which can cover large areas with the help of LoRaWAN (Long Range Wide Area Network) technology [1, 2]. To overcome disadvantages of LoRaWAN, namely the slow data rates, the proposed sensor system can also cover smaller areas with the widespread WiFi technology. An enormous advantage over individual complete systems in the form of a prototype, is the rapid expansion, uncomplicated calibration of the individual sensors and the ecological relief.
A modular design is used, where individual stacks with sensors and peripherals can be added separately. The stacks are standalone low-power systems and can be calibrated, maintained, and replaced separately and do not require the entire measurement chain. The measured and sent values are stored locally on the main stack and sent to the data collector (gateway) and evaluated by means of the automated selection between WiFi and LoRaWAN.
New Reference Materials for Quantification and Standardization of Fluorescence-based Measurements
(2022)
Luminescence techniques are amongst the most commonly used analytical methods in the life and material sciences due to their high sensitivity and non-destructive and multiparametric character. Photoluminescence signals are, however, affected by wavelength-, polarization-, and time-dependent instrument specific effects and the compound-specific photoluminescence quantum yield. The former hamper the comparability of fluorescence measurements, while the relative determination of the latter requires suitable quantum yield standards with well-known photoluminescence quantum yields. For the simple correction of instrument specific effects in the wavelength region of 300 nm to 950 nm, the set of the five certified spectral fluorescence standards (CRM) BAM-F001 – BAM-F005, has been extended to the NIR range by including two new fluorescence standards currently under certification.
Als bildgebendes und zerstörungsfreies Verfahren eignet sich die Röntgen-Computertomographie (CT) insbesondere bei der Untersuchung von Kunst- und Kulturgütern. Die für Werkstoffprüfung und Materialanalyse konzipierten CT-Anlagen bieten dank hoher Röntgenleistung die Möglichkeit zusätzlich zu Holz, Keramiken und Kunststoffen auch stark schwächende Materialien, wie bspw. Metalle, zu durchdringen. Für eine hohe räumliche Auflösung im unteren Mikrometerbereich (2-200µm) sorgen entsprechend ausgelegte CT-Anlagen. In der Bundesanstalt für Materialforschung und -prüfung (BAM) stehen mehrere solcher CT-Anlagen für unterschiedliche Fragestellungen sowie Probengrößen und - materialien zur Verfügung. Einige Beispiele aus den vergangenen Arbeiten der BAM veranschaulichen das große Potential dieser Untersuchungsmethode.
Da bei einer CT-Messung in der Regel das gesamte Untersuchungsobjekt erfasst und in ein digitales Volumenmodell überführt wird, eröffnet sich für Archäologen und Restoratoren die Möglichkeit Untersuchungen hinsichtlich Materialzusammensetzung, Erhaltungszustand und Herstellungstechnik am virtuellen Objekt vorzunehmen, ohne die Originalsubstanz zu beeinträchtigen. Gegenüber der klassischen Radiografie, bei der nur eine zweidimensionale Abbildung erreicht wird, bietet die CT-Untersuchung die Möglichkeit innenliegende Strukturen dreidimensional zu erfassen. Die notwendige Bestimmung der Objektoberfläche erlaubt zudem die Erstellung eines Oberflächenmodells des untersuchten Gegenstandes. Damit lassen sich unter anderem mechanische Simulationen (Belastung, Durchbiegung, Durchströmung) durchführen. Der erzeugte Datensatz kann somit auch zur Herstellung eines Replikats im 3D-Druckverfahren genutzt werden. Anhand der Untersuchung der Mandoline von Smorsone wird gezeigt, wie eine CT-Messung durchgeführt wird und wie in dem anschließend rekonstruierten 3D-Datensatz mittels Koordinatenmesstechnik Maße (Abstände, Wandstärken, Winkel) exakt ermittelt werden können.
Im Rahmen von der BAM und anderen Partnern ins Leben gerufene Initiative „Digitale Qualitätsinfrastruktur“ ist der Fokus auf die Entwicklung von neuen Regelwerken und Zertifizierungsworkflows ausgerichtet. Dabei ist eine besondere Bedeutung dem Zusammenführen von Operational Technology (OT) und Informationstechnik (IT) beizumessen, wenn aktuelle Prozess- und Parameterdaten
zuverlässig zur Verfügung gestellt werden sollen. In dem Use Case Wasserstofftankstelle werden digitale Abbilder erprobt, die u.a. der Kalibrierung von Sensoren, dem Nachweis über die Wasserstoffreinheit und der vorausschauenden Wartung dienen sollen.
Großenteils der verfahrenstechnischen Bestandsanlagen, die sogenannten Brownfield-Anlagen, sind nach einem konservativen und hierarchischen Automatisierungskonzept ausgelegt. Hierbei können sämtliche Prozessdaten,
besonders aus der Feldebene, einer oberen informationstechnische Ebene
unzugänglich bleiben. Eine Brückentechnologie nach der NAMUR Open Architecture (NOA) soll möglichst viele Informationen und Daten aus der vorgegebenen Brownfield-Automatisierung sicher und rückwirkungsfrei zur
Verfügung stellen. Zusätzliche Sensorik soll ebenso zu der Datenerweiterung beitragen und letztendlich den digitalen Zwilling, bzw. das digitale Abbild des verfahrenstechnischen Prozesses, ergänzen.
Die Herausforderungen einer solchen Infrastruktur gelten vor allem einer universellen
Kommunikationsschnittstelle und der Sicherheit. Darüber hinaus werden vorgeschlagene Normen und Empfehlungen untersucht und erprobt.
Per- and polyfluorinated alkyl substances (PFASs) are a group of several thousand individual compounds. Many 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.
In the present work a HR-CS-GFMAS method for EOF analysis was utilized for suspended particulate matter (SPM) analysis in German rivers in time lines from 2005–2020. Therefore, time and spatial resolved trends were investigated. In addition, SPM samples were analyzed for the Σ41PFAS using target analysis based on UHPLC-HRMS. Overall, target analysis drastically underestimated the total PFAS burden in SPM of German rivers compared to the EOF HR-CS-GFMAS analysis. Using a fluorine mass balance approach, only 0.2% to 38.6% of the EOF was explainable using the Σ41PFAS determined with target analysis. Our study highlights the need to integrate PFAS sum parameters (e.g., EOF with HR-CS-GFMAS) in PFAS risk assessment strategies.
The isotopic analysis of lithium is also relevant to the study of geological phenomena.1 In this work we propose improvements to the method for the isotopic analysis of lithium using a high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) coupled to a double echelle modular spectrometer (DEMON). 2 This tool for 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←2 2S electronic transition around 670.788 nm. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm. For the training of the algorithm (XGBoost), a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol-1 was used. Subsequently, the procedure was validated of a set of stock chemicals (Li2CO3, LiNO3, LiCl and LiOH) and a BAM candidate reference material, the cathode material LiNi1/3Mn1/3Co1/3O2 (NMC111). Finally, the ML model was applied to the set of geological samples, previously digested, for the determination of their isotope ratio. The optical resolution was improved from 140,000 to 790,000 to better deconvolution the lithium isotopic components in the atomic spectrum. And the method was compared with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). The results are metrologically comparable.
Screening against ADAMTS4 reveals a specific peptide, which was turned into an MRI probe. The aneurysm in a mouse modal was visualized via MRI. A differentiation between stable and unstable aneurysm in an early state was performed. Using the probe as tool for an easy and non-invasive rupture assessment is possible.