Analytische Chemie
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- 1 Analytische Chemie; Referenzmaterialien (38)
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- 1.1 Anorganische Spurenanalytik (6)
- 1.2 Biophotonik (6)
- 4 Material und Umwelt (6)
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- 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.