Analytische Chemie
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Aroma Sensing of Truffles
(2022)
The aim of this project is to develop a mobile technical device to search for truffles. This way, truffles can be harvested faster, cheaper and more efficiently compared to the current method using dogs.
For this purpose, suitable marker substances in the aroma of ripe truffles were identified using analytical-chemical methods. The collected data was used to create aroma profiles of different truffle species.
The specificity of possible marker substances was confirmed with a truffle dog study. The hypothesis “If trained truffle dogs recognize the substances as supposed truffles in the context of an experiment, they can be regarded as specific” was made. The results show that the truffle aroma is mainly characterized and perceived by dogs by dimethyl sulfide and dimethyl disulfide.
For the concentration measurement of these markers in the ambient air, we are currently building our own detector. The Challenge is to get a fast measurement with a very low limit of detection at the same time. The device will resemble a metal detector in terms of shape and handling and be particularly suitable for mobile use.
The R&D cooperation project between the Federal Institute for Materials Research and Testing (BAM) and sglux GmbH thus enables truffles to be harvested professionally and systematically. This brings the technical advances that have revolutionized agriculture over the last hundred years to truffle cultivation for the first time.
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.
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.
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.
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.
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.
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.
With the online coupling (or hyphenation) of chemically-resolved spectroscopy detection with classical size-exclusion chromatography (SEC) it is possible to correlate polymer molecular size with chemical structure in a single in-situ or on-flow measurement. Medium-resolution 1H-NMR (60 MHz) spectroscopy (i.e., “desktop NMR”) and Fouriertransform Infrared Spectroscopy (FTIR) have both been developed as coupled methods (SEC-MR-NMR, SEC-FTIR) for the detection of polymer analytes by monitoring e.g. alkene or carbonyl functionality.1,2 Here, we have investigated the potential for the detection of polymer end groups, using a slightly higher field-strength spectrometer (80 MHz 1H Larmor frequency) and taking advantage of a columnless injection method that provides bulk spectra for reference. End-functionalized polymers were synthesized by reaction of PEG with toluene isocyanate, yielding ,-functionalized polymers with exactly 2 IR- and NMR-detectable functional groups per chain, as proven by MALD-TOF mass spectrometry. We have investigated the sensitivity (limit of detection) and spectral resolution for these functional groups in chloroform, THF, and water. Results have demonstrated a good feasibility for the simultaneous online detection of PEG backbone (M~4000 g/mol) and these end groups at the level of ca. 2 mol%.
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.