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The need for sustainable and effective usage of limited resources like water and soil becomes more and more important due to increasing populations and their need for food. The research initiative BonaRes funded by the Federal Ministry of Education and Research, develops strategies to use soil as a sustainable resource for the bio-economy. One part of this initiative is the Intelligence for Soil (I4S) project. It deals with the development of an integrated system for the site-specific soil fertility management. The goal of the project is to establish a mobile sensor platform for soil mapping as well as to apply soil and crop models to deal with the high amount of produced data. These models are going to be used to formulate recommendations on the use of fertilizers and to gain an improvement on the soil fertility. Using this information, the environmental pollution with substances like nitrate contained in fertilizers can be decreased. Furthermore, the costs for farmers can be decreased if only the amounts of fertilizer needed are applied to the field.
The task for BAM is installation and optimization of a handheld XRF sensor for online measurement directly on the field. It is a non-destructive technique and quite suitable for an online approach due to a low maintenance in sample preparation and a fast and simultaneous multi element analysis. The elements of interest in this case are light elements like phosphorus, calcium, and potassium. One of the major tasks is the calibration of the sensor for different soils is finding suitable calibration models, which are evolved to deal with different types of soil. Due to the multi element analysis, micro and macro nutrients can be determined simultaneously. Those differ a lot in their contents, which makes it inevitable to optimize and adapt the analytical procedure. By analyzing soil it is always important to deal with matrix effects, that is why the influence of different disturbances like the moisturize content and the grain size needs to be investigated. The XRF is only one of many sensors that combined give customized fertilizing recommendations in the end.
This paper describes a wireless mobile prototype able to perform optical measurements by means of a miniaturized spectrometer for low light analysis, e.g. fluorescent sensors.
Evaluations, calculations, calibration management and result display are performed by a computer or a standard tablet. The device was designed primarily to detect traces of oil in drinking or ground water and for the analyses of crude oils. However, it can also address a wide range of fluorescent sensors. The fast and user-friendly inspection of water quality or oil properties, as well as the adaptability and mobility, make the device attractive for a variety of users. Further application areas could be easily implemented by adapting the optics and the software (database, data processing and calibration plots, etc.).
In addition to previously reported results on the simulated aging of polystyrene samples (PS) containing 1 wt. % hexabromocyclododecane (HBCD), we present the first results of our investigations of polypropylene (PP)-samples containing 0.1 wt. % BDE-209. All studied polymer samples were exposed to a defined weathering schedule in a climate chamber in accordance to regulation EN ISO 4892-3:2006.For the determination of BDE-209 in the collected rain water samples derived from the used climate chamber, the samples were prepared in accordance with a validated protocol. Before the analyses, each sample was spiked with 2 µL of isotopically labeled BDE-209 (13C10-BDE-209) to serve as internal standard (ISTD) in the performed stable isotope dilution analysis. Subsequently the samples were extracted with isooctane, the obtained aliquots of the extracts were concentrated to 200 µL and 2 µL of the resulting solution were injected to the GC/MS for quantification.
Additionally, the total bromine contents are monitored for the aged and untreated samples using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) as well as X-ray fluorescence analysis (XRF) as non-destructive and rapid method. Furthermore, results from surface analysis using environmental scanning electron microscopy (ESEM) for morphological characterization of the aged and untreated samples were presented and discussed. In general, the resulting data from the accelerated aging will be compared to those from the natural weathering experiments (“atmospheric exposure”, in soil).
The atmospheric exposure was performed by placing the samples on a weathering rack, which is aligned in SW direction (in a 45° angle to the horizon). The weathering data were regularly recorded by Deutscher Wetterdienst at this site. The surfaces of the test specimens (aged and stored references) were analyzed by ESEM as well as by LA-ICP-MS and by XRF. The surface of PS and PP specimens aged outdoors present the aging under real conditions and allow the comparison to the accelerated aged specimens by means of the weathering chamber. This way, we explore the efficiency of the accelerated aging procedure, which provides the advantage of well-defined and reproducible conditions compared to natural weathering, as a tool for testing different plastic materials.
Additionally “in soil” experiments were conducted in-door in a well characterized testing soil. The soil (boulder-clay, sand with 12 % loam, particle size in total 0.2-4 mm) is filled in a free-draining concrete basin inside of an air-conditioned room. In this manner, TOC, water capacity and humidity are recorded parameters. To assure a washing out process from the samples by the raining water, the target water content is calculated to 8%. The actual humidity is measured by a tensiometer, assuring the duration of the raining period. The water content is additionally monitored by weight of the basin, capturing water from raining periods. The correct humidity is a fundamental parameter for biological activity. Samples of PS resp. PP were of dimension 10x1cm and 5 specimens were placed up to the half in the soil per basin. Microbial activity of the soil, monitored by the reference polyurethane, sets HBCD resp. BDE-209 of the samples free and will be leached from the samples by raining water. Thereafter these will be captured by passive samplers placed in a distinct distance to the samples in the soil. The “in soil” experiments are complementary to the weathering experiments due to the biological activity in the soil. These experiments simulate the fate of the brominated flame retardants in the biosphere.
In addition to previously reported results on the accelerated weathering of polystyrene samples (PS) containing 1 wt.% hexabromocyclododecane (HBCD), we present the first results of our investigations of polypropylene samples (PP) containing 0.1 wt.% BDE-209. All studied polymer samples were exposed to a defined weathering schedule in a climate chamber in accordance to regulation EN ISO 4892-3:2006. For the determination of BDE-209 in the collected raining water the samples were prepared in accordance to a validated protocol. Before the analyses each sample was spiked with isotopically labeled BDE-209. Subsequently the samples were extracted with isooctane. The obtained extracts were concentrated, and the resulting solutions were analyzed by GC/MS. Additionally, the total bromine content was monitored for the weathered and untreated samples using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and X-ray fluorescence analysis (XRF) as a non-destructive and rapid method. In general, the resulting data from the accelerated weathering will be compared to those from the natural weathering experiments. Here, the surfaces of the test pieces were analyzed by LA-ICP-MS and XRF as well. Moreover, soil bed tests were conducted in a well characterized model soil. This soil (boulder-clay, sand with 12 % loam, particle size in total 0.2-4 mm) is filled in a free-draining basin inside of an air-conditioned cellar. In this manner, TOC, water capacity and humidity are recorded parameters. To induce a leaching process from the samples by the raining water, the target water content is calculated to 8%. The actual humidity is measured by a tensiometer, assuring the duration of the raining period. A defined humidity is a fundamental parameter for a biological activity in the soil. The test polymers were placed up to the half in the soil. Microbial activity of the soil is monitored by a reference polymer (polyurethane) and should induce the release of HBCD and BDE-209 out of the test materials. These released analytes will be captured by passive samplers (silicone tubes) placed in a distinct distance to the polymer samples in the soil. The soil bed experiments are complementary to the weathering experiments due to the biological activity in the soil.
Emission testing of volatile organic compounds (VOC) from materials and products is commonly based on emission test chamber measurements. To ensure the comparability of results from different testing laboratories their measurement performance must be verified. For this purpose, Bundesanstalt für Materialforschung und -prüfung (BAM) organizes an international proficiency test every two years using well-characterised test materials (one sealant, one furniture board and four times a lacquer) with defined VOC emissions. The materials fulfilled the requirements of homogeneity, reproducibility, and stability. Altogether, 41 VOCs were included of which 37 gave test chamber air concentrations between 10 and 98 µg/m³. This is the typical concentration range to be expected and to be quantified when performing chamber tests. Four compounds had higher concentrations between 250 and 1105 µg/m³. The relative standard deviations (RSD) of BAM proficiency tests since 2008 are compared and the improvement of the comparability of the emission chamber testing is shown by the decrease of the mean RSD down to 23% in 2021. In contrast, the first large European interlaboratory comparison in 1999 showed a mean RSD of 51%.
Tandem MS techniques are widely used for both, structure and sequence elucidation of biopolymers. Thereby, fragmentation activation is realized by various methods, for example with lasers or collisions with neutral gases. In this study, we present a new Tandem MS system using a commercially available vacuum ultraviolet lamp. On the one hand, this approach provides efficient fragmentation in both ionization modes, positive as well as negative. On the other hand, it enables an additional previously not achieved post ionization of the fragments. While the first results in atypical fragment patterns and, thus provides orthogonal information, the second is crucial especially to identify low abundant ions.
Tandem MS techniques are widely used for both, structure and sequence elucidation of biopolymers. Thereby, fragmentation activation is realized by various methods, for example with lasers or collisions with neutral gases. In this study, we present a new Tandem MS System using a commercially available vacuum ultraviolet lamp. On the one hand, this approach provides efficient fragmentation in both ionization modes, positive as well as negative. On the other hand, it enables an additional previously not achieved post ionization of the fragments. While the first results in atypical fragment patterns and, thus provides orthogonal information, the second is crucial especially to identify low abundant ions.
Gas Chromatography coupled with Electron Ionisation Mass Spectrometry (GC-EI-MS) is a well-established technique which, in combination with spectral libraries, has the potential to identify compounds in a sample. Nevertheless, most libraries are dominated by spectra with nominal mass resolution which does not allow to make full use of the data generated by modern high-resolution instruments. The production of high-resolution spectral library is time consuming and expensive, while in silico fragmentation tools that are capable of generating HR mass spectra are still too computationally intensive. We explored the alternative of using ML models to upscale existing spectral libraries. The models were trained with spectra from the RECETOX metabolome (DOI: 10.5281/zenodo.5483564), RECETOX Exposome (DOI: 10.5281/zenodo.4471216), and MassBank (10.5281/zenodo.7436394) HR-GC-MS libraries. The model was used to generate a synthetic library which was compared with a synthetic library simulated with CFM-ID (DOI: 10.1021/acs.analchem.6b01622).
Non-target (NT) mass spectrometry techniques play a crucial role in metabolomics applications, particularly in areas such as environmental safety. Soft ionization methods, such as electrospray ionization (ESI), are commonly employed due to their ability to generate spectra containing molecular ions, aiding in the identification of unknown peaks. However, ESI may fail to ionize certain compounds effectively, resulting in their absence in NT approaches. In contrast, hard ionization methods like electron impact (EI) can ionize a wide range of compounds but often lack information about the molecular ion. Although extensive databases of EI spectra exist, their nominal mass resolution (NR) limits their utility for modern high-resolution (HR) EI mass spectrometers. Here, the often-applied conversion of HR spectra to nominal mass leads to the loss of unique characteristics, i.e. by grouping distinct masses into more ambiguous nominal masses.
Our study aims to (i) quantify the negative impact of such a binning approach and (ii) develop a machine learning (ML) tool capable of enhancing existing nominal mass spectral libraries. In the initial phase, we employed the RECETOX Exposome HR-[EI+]-MS library to assess the influence of HR spectra on identification. We compared the dot product of each spectrum against all others, utilizing bin sizes of 0.001 and 1 Da. The difference in dot product between the second-best candidate and the query spectrum (the best candidate, with a score of 1) was calculated for both HR and nominal mass spectra. Subsequently, we explored the application of ML techniques to predict HR spectra from nominal mass spectra using the before mentioned dataset.
Preliminary findings demonstrate the potential of high-resolution spectral libraries. As anticipated, HR spectra consistently exhibited lower similarity scores for the second candidate. This observation likely stems from the high redundancy and resulting ambiguity associated with nominal masses. Even after eliminating spectra containing multiple HR masses mapped to the same nominal mass, the aforementioned trend persisted. Furthermore, initial investigations into ML have revealed its ability to predict up to 40% of HR masses within a 10 mDa precision window.