Chemische Charakterisierung und Spurenanalytik
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A set of strained aromatic macrocycles based on [n]cyclo2,7-(4,5,9,10-tetrahydro)pyrenylenes is presented with size dependent photophysical properties. The K-region of pyrene was functionalized with ethylene glycol groups to decorate the outer rim and thereby confine the space inside the macrocycle. This confined space is especially pronounced for n = 5, which leads to an internal binding of up to 8.0×104 M–1 between the ether-decorated [5]cyclo-2,7-pyrenylene and shape complementary crown ether–cation complexes.
Both, the ether-decorated [n]cyclo-pyrenylenes as well as one of their host–guest complexes have been structurally characterized by single crystal X-ray analysis. In combination with computational methods the structural and thermodynamic reasons for the exceptionally strong binding have been elucidated. The presented rim confinement strategy makes cycloparaphenylenes an attractive supramolecular host family with a favorable, size-independent read-out signature and binding capabilities extending beyond fullerene guests.
The occurrence of microplastic (MP) in food products, such as beverages in plastic bottles, is of high public concern. Existing analytical methods focus on the determination of particle numbers, requiring elaborate sampling tools, laboratory infrastructure and generally time-consuming imaging detection methods. A comprehensive routine analysis of MP in food products is still not possible. In the present work, we present the development of a smart filter crucible as sampling and detection tool. After filtration and drying of the filtered-off solids, a direct determination of the MP mass content from the crucible sample can be done by thermal extraction desorption gas chromatography mass spectroscopy (TED-GC/MS). The new filter crucible allows a filtration of MP down to particle sizes of 5 µm. We determined MP contents below 0.01 µg/L up to 2 µg/L, depending on beverages bottle type. This may be directly related to the bottle type, especially the quality of the plastic material of the screw cap. Dependent on the plastic material, particle formation increases due to opening and closing operations during the use phase. However, we have also found that some individual determinations of samples were subjected to high errors due to random events. A conclusive quantitative evaluation of the products is therefore not possible at present.
In this work, we describe the use of artificial neural networks for the quantification of X-ray fluorescence measurements. The training data were generated using Monte Carlo simulation, which avoided the use of adapted reference materials. The extension of the available data set by means of an ANN to generate additional data was demonstrated. Particular emphasis was put on the comparability of simulated and experimental data and how the influence of deviations can be reduced. The search for the optimal hyperparameter, manual and automatic, is also described. For the presented case, we were able to train a network with a mean absolute error of 0.1 weight percent for the synthetic data and 0.7 weight percent for a set of experimental data obtained with certified reference materials.
Microplastic particles are currently detected in almost all environmental compartments. The results of detection vary widely, as a multitude of very different methods are used with very different requirements for analytical validity.
In this work four thermoanalytical methods are compared and their advantages and limitations are discussed. One of them is thermal extraction-desorption gas chromatography mass spectrometry (TED-GC/MS), an analysis method for microplastic detection that has become established in recent years. In addition, thermogravimetric analysis coupled with Fourier-transform infrared spectroscopy (TGA-FTIR) and mass spectrometry (TGA-MS) were applied, two methods that are less common in this field but are still used in other research areas. Finally, microscale combustion calorimeter (MCC) was applied, a method not yet used for microplastic detection.
The presented results are taken from a recently published interlaboratory comparison test by Becker et al. (2020). Here a reference material consisting of suspended matter and specified added polymer masses was examined, and only the results of the recoveries were presented. In the present paper, however, the results for the individual polymers are discussed in detail and individual perspectives for all instruments are shown.
It was found that TED-GC/MS is the most suitable method for samples with unknown matrix and unknown, variable kinds and contents of microplastic. TGA-FTIR is a robust method for samples with known matrix and with defined kinds of microplastic. TGA-MS may offer a solution for the detection of PVC particles in the future. MCC can be used as a very fast and simple screening method for the identification of a potential microplastic load of standard polymers in unknown samples.
Tire and road wear particles (TRWPs) are heteroagglomerates of tire rubber and other particles deposited on the road surface and one of the main contributors to non-exhaust emissions of automobile traffic. In this study, samples from road environments were analyzed for their TRWP contents and concentra- tions of eight organic tire constituents. TRWP concentrations were determined by quantifying Zn in the density fraction < 1.9 g/cm ³and by thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC/MS) and the concentrations ranged from 3.7 to 480 mg TRWP/g. Strong and statistically signif- icant correlations with TRWPs were found for 2-hydroxybenzothiazole and 2-aminobenzothiazole, indi- cating that these substances may be suitable markers of TRWPs. The mass distribution of TRWPs in road dust suggests that the main mass fraction formed on roads consists of coarse particles ( > 100 μm). Data for a sedimentation basin indicate that the fine fraction ( < 50 μm) is preferentially transported by road runoffinto receiving waters. The size distribution and density data of TRWP gathered by three different quantitation approaches also suggest that aging of TRWPs leads to changes in their particle density. An improved understanding of the dynamics of TRWP properties is essential to assess the distribution and dissipation of this contaminant of emerging concern in the environment.
Two sets of polystyrene nanoparticles (PSNPs) with comparable core sizes but different carboxyl group densities were made and separated using asymmetric flow field flow fractionation (AF4), capillary electrophoresis (CE), and the off-line hyphenation of both methods. Our results revealed the significant potential of two-dimensional off-line AF4-CE hyphenation to improve the separation and demonstrated for the first time, the applicability of CE to determine the functional group density of nanoparticles (NPs). Compared to the result acquired with conductometric titration, the result obtained with synthesized 100 nm sized PSNPs revealed only a slight deviation of 1.7%. Commercial 100 nm sized PSNPs yielded a deviation of 4.6 %. For 60 nm sized PSNPs, a larger deviation of 10.6 % between both methods was observed, which is attributed to the lower separation resolution.
To better study the impact of nanoparticles on both in vitro and in vivo models, tissue distribution and cellular doses need to be described more closely. Here silver nanoparticles were visualized in alveolar macrophages by means of synchrotron radiation micro X-ray fluorescence spectroscopy (SR-μXRF) with high spatial resolution of 3 × 3 μm2. For the spatial allocation of silver signals to cells and tissue structures, additional elemental labeling was carried out by staining with eosin, which binds to protein and can be detected as bromine signal with SR-μXRF. The method was compatible with immunostaining of macrophage antigens. We found that the silver distribution obtained with SR-μXRF was largely congruent with distribution maps from a subsequent laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) of the same tissue sites. The study shows a predominant, though not exclusive uptake of silver into alveolar macrophages in the rat lung, which can be modeled by a similar uptake in cultured alveolar macrophages. Advantages and limitations of the different strategies for measuring nanoparticle uptake at the single cell level are discussed.
Cyclic poly(L-lactide)s were prepared by ring-opening polymerization combined with simultaneous polycondensation (ROPPOC) in bulk at 160 ° with dibutyltin bis(4-cyanophenoxide) as catalyst. It is demonstrated by MALDI TOF mass spectrometry and 1H NMR end group analyses that cycles are formed by endto-end cyclization in addition to “back-biting” transesterification. Formation of high molar mass cyclic poly L-lactide)s by means of several more reactive ROPPOC catalysts presented previously and in new experiments is discussed. These experimental results, together with theoretical arguments, prove that part of the Jacobson–Stockmayer theory is wrong. The critical monomer concentration, above which end-toend cyclization is seemingly impossible, does not exist and reversible like irreversible polycondensations can theoretically proceed up to 100% conversion, so that finally all reaction products will necessarily adopt a cyclic architecture.
The analysis of pollen chemical composition is important to many fields, including agriculture, plant physiology, ecology, allergology, and climate studies. Here, the potential of a combination of different spectroscopic and spectrometric methods regarding the characterization of small biochemical differences between pollen samples was evaluated using multivariate statistical approaches. Pollen samples, collected from three populations of the grass Poa alpina, were analyzed using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface enhanced Raman scattering (SERS), and matrix assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). The variation in the sample set can be described in a hierarchical framework comprising three populations of the same grass species and four different growth conditions of the parent plants for each of the populations. Therefore, the data set can work here as a model system to evaluate the classification and characterization ability of the different spectroscopic and spectrometric methods. ANOVA Simultaneous Component Analysis (ASCA) was applied to achieve a separation of different sources of variance in the complex sample set. Since the chosen methods and sample preparations probe different parts and/or molecular constituents of the pollen grains, complementary information about the chemical composition of the pollen can be obtained. By using consensus principal component analysis (CPCA), data from the different methods are linked together. This enables an investigation of the underlying global information, since complementary chemical data are combined. The molecular information from four spectroscopies was combined with phenotypical information gathered from the parent plants, thereby helping to potentially link pollen chemistry to other biotic and abiotic parameters.