Chemische Charakterisierung und Spurenanalytik
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Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (103)
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- 4 Material und Umwelt (16)
- 6.6 Physik und chemische Analytik der Polymere (16)
- 6.3 Strukturanalytik (12)
Eingeladener Vortrag
- nein (57)
A method, based on electrothermal vaporization (ETV) coupled to inductively coupled plasma optical emission spectrometry (ICP OES), has been optimized for direct solid sampling analysis of soda-lime glass - the most common type of industrially manufactured glass. This method allows fast and reliable quantification of the main elements - Al, Ca, K, Mg, Na, and Si - and trace elements - As, Ba, Cd, Ce, Co, Cr, Cu, Fe, Mn, Mo, Ni, (P), Pb, Sb, (Se), Sn, Sr, Ti, V, Zn, and Zr. In the presented ETV-ICP OES method, calibration is performed predominantly with matrix-free synthetic samples. This metrological advantage is normally not achieved with direct solid sampling methods and is one of the goals of the present study. In a certification interlaboratory comparison for the soda-lime glass CRM BAM-S005c, 2 out of 16 laboratories employed the ETV-ICP OES method. An improved analytical performance was obtained compared with the results of laboratories that used conventional liquid ICP OES. For both methods, the average relative deviations between the laboratory results and certified values as well as the average values of relative standard deviation were with a few exceptions <10%, in most cases even <5%, which indicated high trueness and precision.
Here, we describe a fast and simple extraction method for the determination of per- and polyfluorinated alkyl substances (PFASs) utilizing extractable organic fluorine (EOF) sum parameter analysis and high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) in soil samples. After extraction and separation of inorganic and organic fluorinated compounds, organically bound fluorinated compounds were indirectly determined via the molecular absorption of gallium mono-fluoride at 211.248 nm. The implementation of the decisions of the “Stockholm Convention on persistent organic pollutants” as well as the “Protocol on Persistent Organic Pollutants of the Convention on Long-Range Transboundary Air Pollution” of the UNECE include the reduction respectively the elimination of PFASs in the environment. Currently, regulations aim to target single compounds (mostly C8-PFAS). But the PFAS group includes over 4700 substances, which are potentially persistent and toxic, thus target analytical approaches are not suitable for a holistic approach investigating the PFAS pollutant situation. Furthermore, forbidden PFASs are substituted by short-chain PFASs, thus the number of unknow substances is steadily increasing. For this reason, sum parameter approaches are more suitable to investigate and assess the pollution situation as well as derive exposure limits. Our developed analytical method was successfully applied to determine PFASs in soil samples from a polluted site. In view of steadily increasing numbers of PFAS substances, our method will make an important contribution in assessing the pollution situation as well as support policy makers in deriving exposure limits for PFAS in the future.
Here, we describe a fast and simple extraction method for the determination of per- and polyfluorinated alkyl substances (PFASs) utilizing extractable organic fluorine (EOF) sum parameter analysis and high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) in soil samples. After extraction and separation of inorganic and organic fluorinated compounds, organically bound fluorinated compounds were indirectly determined via the molecular absorption of gallium mono-fluoride at 211.248 nm. The implementation of the decisions of the “Stockholm Convention on persistent organic pollutants” as well as the “Protocol on Persistent Organic Pollutants of the Convention on Long-Range Transboundary Air Pollution” of the UNECE include the reduction respectively the elimination of PFASs in the environment. Currently, regulations aim to target single compounds (mostly C8-PFAS). But the PFAS group includes over 4700 substances, which are potentially persistent and toxic, thus target analytical approaches are not suitable for a holistic approach investigating the PFAS pollutant situation. Furthermore, forbidden PFASs are substituted by short-chain PFASs, thus the number of unknow substances is steadily increasing. For this reason, sum parameter approaches are more suitable to investigate and assess the pollution situation as well as derive exposure limits. Our developed analytical method was successfully applied to determine PFASs in soil samples from a polluted site. In view of steadily increasing numbers of PFAS substances, our method will make an important contribution in assessing the pollution situation as well as support policy makers in deriving exposure limits for PFAS in the future.
A general method to carry out the fluorination of metal oxides with poly(tetrafluoroethylene) (PTFE, Teflon) waste by spark plasma sintering (SPS) on a minute scale with Teflon is reported. The potential of this new approach is highlighted by the following results. i) The tantalum oxyfluorides Ta3O7F and TaO2F are obtained from plastic scrap without using toxic or caustic chemicals for fluorination. ii) Short reaction times (minutes rather than days) reduce the process time the energy costs by almost three orders of magnitude. iii) The oxyfluorides Ta3O7F and TaO2F are produced in gram amounts of nanoparticles. Their synthesis can be upscaled to the kg range with industrial sintering equipment. iv) SPS processing changes the catalytic properties: while conventionally prepared Ta3O7F and TaO2F show little catalytic activity, SPS-prepared Ta3O7F and TaO2F exhibit high activity for photocatalytic oxygen evolution, reaching photoconversion efficiencies up to 24.7% and applied bias to photoconversion values of 0.86%. This study shows that the materials properties are dictated by the processing which poses new challenges to understand and predict the underlying factors.
Increasing contamination of environmental waters with pharmaceuticals represents an emerging threat for the drinking water quality and safety. In this regard, fast and reliable analytical methods are required to allow quick countermeasures in case of contamination. Here, we report the development of a magnetic bead-based immunoassay (MBBA) for the fast and cost-effective determination of the analgesic diclofenac (DCF) in water samples, based on diclofenac-coupled magnetic beads and a robust monoclonal anti-DCF antibody. A novel synthetic strategy for preparation of the beads resulted in an assay that enabled for the determination of diclofenac with a significantly lower limit of detection (400 ng/L) than the respective enzyme-linked immunosorbent assay (ELISA). With shorter incubation times and only one manual washing step required, the assay demands for remarkably shorter time to result (< 45 min) and less equipment than ELISA. Evaluation of assay precision and accuracy with a series of spiked water samples yielded results with low to moderate intra- and inter-assay variations and in good agreement with LC–MS/MS reference analysis. The assay principle can be transferred to other, e.g., microfluidic, formats, as well as applied to other analytes and may replace ELISA as the standard immunochemical method.
Lipid droplets, the dynamic organelles that store Triglycerides (TG) and cholesterol esters (CE), are highly accumulated in colon cancer cells. This work studies the TG and CE subspecies profile in colon carcinoma cell lines, SW480 derived from primary tumor, and SW620 derived from a metastasis of the same tumor. It was previously reported that the total TG and CE content is dramatically higher in SW620 cells; however, TG and CE subspecies profile has not been investigated in detail. The work presented here confirms that the total TG and CE Content is significantly higher in the SW620 cells. Moreover, the fatty acid (FA) composition of TG is significantly altered in the SW620 cells, with significant decrease in the abundance of saturated triglycerides. This resulted in a significantly decreased TG saturation index in the SW620 cells. The saturation index of CE was also significantly decreased in the SW620 cells.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions.