Filtern
Erscheinungsjahr
Dokumenttyp
- Zeitschriftenartikel (31)
- Vortrag (24)
- Beitrag zu einem Tagungsband (18)
- Posterpräsentation (13)
- Forschungsdatensatz (1)
Schlagworte
- Chemometrics (11)
- NIR (9)
- Microplastics (8)
- Raman (7)
- Process analytical technology (6)
- Prozessanalytik (6)
- Hydroformylation (5)
- Raman spectroscopy (5)
- Reaction monitoring (5)
- Chemometrie (4)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (26)
- 1.4 Prozessanalytik (25)
- 6 Materialchemie (4)
- 6.6 Physik und chemische Analytik der Polymere (3)
- 1.7 Organische Spuren- und Lebensmittelanalytik (1)
- 1.9 Chemische und optische Sensorik (1)
- 4 Material und Umwelt (1)
- 4.4 Thermochemische Reststoffbehandlung und Wertstoffrückgewinnung (1)
- 5 Werkstofftechnik (1)
- 5.3 Polymere Verbundwerkstoffe (1)
Paper des Monats
- ja (1)
Eingeladener Vortrag
- nein (24)
A first pilot study on the sorption of environmental pollutants on various microplastic materials
(2017)
With the drastic increase in plastic production, the input of plastic particles into the environment has become a recognised problem.
Xenobiotics are able to sorb to polymer materials, and this process is further enhanced where they Encounter microplastics (plastic fragments <5 mm). In this work we studied the sorption of metformin, a type-2 diabetes drug, and difenoconazole, a fungicide, onto the virgin polymer materials polyamide (PA), polypropylene (PP), and polystyrene (PS). Additionally, PP was cryo-milled and PA was treated with acid to investigate the influence of an increase in surface area and chemical modification. The material properties were also studied by dynamic scanning calorimetry (DSC), gel permeation chromatography (GPC) and Fourier transform infrared spectroscopy (FTIR). Sorption experiments were performed on the basis of a full factorial design examining the effect of agitation, pH value, and salinity. Experimental results showed that difenoconazole sorbs readily to all microplastics, whereas the more polar analyte metformin did not show any affinity to the materials used. For difenoconazole the governing factor in all cases is agitation, while both pH and salinity exhibited only a slight influence. The modification of polymers leads to enhanced sorption, indicating that an increase in surface area (cryo-milled PP) or inner volume (acid-treated PA) strongly favours adsorption. Moreover, long-term experiments demonstrated that the time until equilibrium is reached depends strongly on the particle size.
A process spectroscopic approach for the monitoring of microplastics in environmental samples
(2018)
The potential of Raman and NIR process-spectroscopic as a rapid approach for the estimation of microplastics (MP) in soil matrix were tested. For this purpose, artificial MP/soil mixture samples consisting of standard soils or sand with defined ratios of MP (0,5 – 10 mass% polymer) from polyethylene (PE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET) were prepared. MP particles with diameters < 2 mm and < 125 µm were obtained from industrial polymer pellets after cryo-milling. Spectra of these mixtures were collected by (i) a process FT-NIR spectrometer equipped with a reflection probe, (ii) by a cw-process Raman spectrometer and (iii) by a time-gated Raman spectrometer using fiber-optic probes. The evaluation of process-spectra was performed by chemometric methods. Whereas MP could be detected by Raman spectroscopy in coastal sand at 0.5 mass%, in standard soil detection of MP was limited to 10 – 5 mass% with the large fraction, but samples containing particles of the 125µm mass-fraction yielded no positive result at all. One reason for the lacking sensitivity could be fluorescence by soil organic matter and thus, in a next test time-gated Raman spectroscopy was applied. However, although being indeed more sensitive to the small particles this method failed at MP < 5 mass% indicating that fluorescence was not the major problem. Finally, FT-NIR was tested. Depending on the polymer, MP contents of 0,5 or 1 mass%, respectively, could be detected in standard soils and polymers identified. Furthermore, this approach could be used for the investigation of mixtures of up to four polymers and in real-world samples from bio-waste fermenter residues.
Due to the increasing presence of microplastic particles (MP) in the Environment and the unknown risks arising from them, there is an urgent need for analytical methods that allow for an efficient identification and quantification of microplastics (MP), i.e. particles < 5 mm, in environmental samples. So far, mostly timeconsuming (micro) infrared or micro-Raman spectroscopic methods are applied. Here an faster alternative Approach is presented based on a Raman processspectrometer with fiber-optical probes in combination with multivariate data analysis.
Abstract. Biodiesel quality control is a relevant issue as biodiesel properties influence diesel engine performance and integrity. Within the European Metrology Research Program (EMRP) ENG09 project “Metrology for Biofuels”, an on-line /at-site suitable near-infrared spectroscopy (NIRS) method has been developed in parallel with an improved EN14110 headspace GC analysis method for methanol in biodiesel. Both methods have been optimized for a methanol content of 0.2 mass% as this represents the maximum limit of methanol content in FAME according to EN 14214:2009. The NIRS method is based on a mobile NIR spectrometer equipped with a fiber-optic coupled probe. Due to the high volatility of methanol, a tailored air-tight adaptor was constructed to prevent methanol evaporation during measurement. The methanol content of biodiesel was determined from evaluation of NIRS spectra by Partial Least Squares Regression (PLS). Both GC analysis and NIRS exhibited a significant dependence on biodiesel feedstock. The NIRS method is applicable to a content range of 0.1 % (m/m) to 0.4 % (m/m) of methanol with uncertainties at around 6% relative for the different feedstocks. A direct comparison of headspace GC and NIRS for samples of FAMEs yielded that the results of both methods are fully compatible within their stated uncertainties.
An alternative spectroscopic approach for the monitoring of microplastics in environmental samples
(2017)
The increasing pollution of terrestrial and aquatic ecosystems with plastic debris leads to the accumulation of microscopic plastic particles of still unknown fate. To monitor the degree of contamination and to understand the underlying processes of turnover, analytical methods are urgently needed, which help to identify and quantify microplastic (MP). Currently, costly collected and purified materials enriched on filters are investigated both by micro-infrared spectroscopy and micro-Raman. Although yielding precise results, these techniques are time consuming and restricted to sample aliquots in the order of micrograms precluding prompt and representative information on both, larger sample numbers and realistic material volumes. To overcome these problems, here we tested Raman and NIR process-spectroscopic methods in combination with multivariate data analysis.
For this purpose, artificial MP/soil mixture samples consisting of standard soils or sand with defined ratios of MP (0,5 – 10 mass% polymer) from polyethylene, polypropylene, and polystyrene were prepared. MP particles with diameters < 2 mm and < 125 µm were obtained from industrial polymer pellets after cryomilling. Spectra of these mixtures were collected by (i) a process FT-NIR spectrometer equipped with a reflection probe, (ii) by a cw-process Raman spectrometer and (iii) by a time-gated Raman spectrometer using fiber optic probes. For the calibration of chemometric models (partial least squares regression, PLSR) 5 – 10 spectra of defined MP/soil mixtures (consisting of 1 – 4 g material each) were collected. The obtained PLSR models served for the prediction of both, polymer type and content based on the spectra of “unknown” test samples.
Whereas MP could be detected by Raman spectroscopy in coastal sand at 0.5 mass%, in standard soils detection of MP was limited to 10 – 5 mass%. The sensitivity of Raman spectroscopy could be improved by mild treatment with hydrogen peroxide. FT-NIR was suitable for the investigation of MP in standard soils in the range of 5 – 1 mass%, however, here a non-linear effect was observed at higher polymer concentrations. When mixtures of several polymers at low concentration levels were milled together, FT-NIR spectroscopy yielded false positive polymers together with unprecise quantitative information. Recently, the investigation of “real-world” samples shall be tested and compared to the results obtained by micro-FTIR and micro-Raman.
Spatial heterodyne spectroscopy (SHS) is used for quantitative analysis and classification of liquid samples. SHS is a version of a Michelson interferometer with no moving parts and with diffraction gratings in place of mirrors. The instrument converts frequency-resolved information into spatially resolved one and records it in the form of interferograms. The back-extraction of spectral information is done by the Fast Fourier transform. A SHS instrument is constructed with the resolving power 5000 and spectral range 522 - 593 nm. Two original technical solutions are used as compared to previous SHS instruments: the use of a high frequency diode pumped solid state (DPSS) laser for excitation of Raman spectra and a microscope-based collection system. Raman spectra are excited at 532 nm at the repetition rate 80 kHz. Raman shifts between 330 cm-1 and 1600 cm-1 are measured. A new application of SHS is demonstrated: for the first time it is used for quantitative Raman analysis to determine concentrations of cyclohexane in isopropanol and glycerol in water. Two calibration strategies are employed: univariate based on the construction of a calibration plot and multivariate based on partial least square regression (PLSR). The detection limits for both cyclohexane in isopropanol and glycerol in water are at a 0.5 mass% level. In addition to the Raman-SHS chemical analysis, classification of industrial oils (biodiesel, poly(1-decene), gasoline, heavy oil IFO380, polybutenes, and lubricant) is performed using their Raman-fluorescence spectra and principal component analysis (PCA). The oils are easily discriminated as they show distinct non-overlapping patterns in the space of principal components.
Der Einsatz moderner Prozessanalysentechnik führt zu einer Datenflut, deren Verarbeitung und Nutzung häufig nicht ohne den Einsatz von Chemometrie zu realisieren ist. Dafür stehen zahlreiche multivariate Verfahren, wie z.B. Hauptkomponentenanalyse (PCA) und Regressionsanalyse (PLSR) für die Klassifizierung und für die quantitative Analyse zur Verfügung. Darüber hinaus können in Spezialfällen, insbesondere in der Spektroskopie, Methoden des „Indirect Hard Modeling“ eingesetzt werden. Anhand einer Industrie-relevanten Reaktion, der Hydroformylierungsreaktion zur Bildung langkettiger Aldehyde aus der Reaktion von Alkenen und Synthesegas, die sowohl im Labormaßstab als auch in einer Miniplant in Kooperation mit der TU Berlin untersucht wurde, werden Kalibrationsstrategien (Design of Experiment, DoE) und Auswertungsansätze mittels PLSR prozessbegleitender Raman Spektren dargelegt. Auf Grundlage des chemometrischen Ansatzes ist eine on-line Überwachung der Reaktion hinsichtlich der Hauptreaktanden, 1-Dodecene und 1-Tridecanal, möglich. Weiterhin konnte mittels Raman Spektroskopie die Bildung eines unerwünschten Nebenprodukts nachgewiesen werden.
Qualitative reference materials (RM) cover a wide range of the overall RM market. Proficiency testing providers attract up to a thousand of participants in PT schemes purely oriented on qualitative results. The RM used for these kinds of PT are poorly regulated, nevertheless with a more and more general acceptance of accreditation in the field of RM production and PT provision, there is an ever increasing interest in assessing producers and providers according to rules already well accepted in the field of quantitative analysis.
The basic governing document, ISO 17034:2016, is written in a form that, at least for the overwhelming majority of requirements, may be applied to both qualitative and quantitative RM. However, problems remain. In particular, the expression of uncertainty of a purely qualitative result is still unresolved, and under discussion, the latter now lasting already dozens of years.
Some handles would be needed. In the poster, existing approaches and some pragmatic, new ways to tackle the problem are displayed and discussed.
Arsenic is a redox-active metalloid whose toxicity and mobility strongly depends on its oxidation state, with arsenite (As(III)) being more toxic and mobile than arsenate (As(V)). Humic substances (HS) are also redox-active and can potentially react with arsenic and change its redox state. In this study we show that semiquinone radicals produced during microbial or chemical reduction of a HS model quinone (AQDS, 9,10-anthraquinone-2,6-disulfonic acid) are strong oxidants. They oxidize arsenite to arsenate, thus decreasing As toxicity and mobility. This reaction depends strongly on pH with more arsenite (up to 67.3%) being oxidized at pH 11 compared to pH 7 (12.6% oxidation) and pH 3 (0.5% oxidation). In addition to As(III) oxidation by semiquinone radicals, hydroquinones that were also produced during quinone reduction reduced As(V) to As(III) at neutral and acidic pH values (less than 12%) but not at alkaline pH. In order to understand redox reactions between arsenite/arsenate and reduced/oxidized HS, we quantified the radical content in reduced quinone solutions and constructed Eh-pH diagrams that explain the observed redox reactions. The results from this study can be used to better predict the fate of arsenic in the environment and potentially explain the occurrence of oxidized As(V) in anoxic environments.
Medium resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and process monitoring. One of the fundamental acceptance criteria for online MR-MNR spectroscopy is a robust data treatment and evaluation strategy with the potential for automation. The MR-NMR spectra were treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprised direct integration, automated line fitting, indirect hard modeling, and partial least squares regression.