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A major industrial reaction based on homogeneous catalysis is hydroformylation for the production of aldehydes from alkenes and syngas. Hydroformylation in microemulsions, which is currently under investigation at Technische Universität Berlin on a mini-plant scale, was identified as a cost efficient approach which also enhances product selectivity. Herein, we present the application of online Raman spectroscopy on the reaction of 1-dodecene to 1-tridecanal within a microemulsion. To achieve a good representation of the operation range in the mini-plant with regard to concentrations of the reactants a design of experiments was used. Based on initial Raman spectra partial least squares regression (PLSR) models were calibrated for the prediction of 1-dodecene and 1-tridecanal. Limits of predictions arise from nonlinear correlations between Raman intensity and mass fractions of compounds in the microemulsion system. Furthermore, the prediction power of PLSR models becomes limited due to unexpected by-product formation. Application of the lab-scale derived calibration spectra and PLSR models on online spectra from a mini-plant operation yielded promising estimations of 1-tridecanal and acceptable predictions of 1-dodecene mass fractions suggesting Raman spectroscopy as a suitable technique for process analytics in microemulsions.
UV-induced transformation of dissolved
organic matter (DOC) is often accompanied by reduction
of molecular weight and aromaticity and an increase of
low-molecular weight (LMW) matter that can be utilized as
a substrate by heterotrophic bacteria. Moreover, the generation
of reactive transients and mineralization of DOC
occurs. For a better understanding of the modification that
starts after irradiation and to distinguish between possible
chemical and biological modifications, we selected different
natural organic matter (NOM) from Norway and
Germany. The aqueous solutions were treated by UV
irradiation and divided into two aliquot samples. NaN3
anti-bacterial treatment was applied to one sample, and
high-pressure size-exclusion chromatography (HPSEC)
analysis was used for both. In all samples, we found typical
modifications of NOM after UV irradiation. Incubation
(>7 days) of UV-irradiated NOM samples resulted in
lower levels of LMW matter and increased aromaticity.
Parallel to these changes of carbon fractions, an increase in
bacterial cell numbers was observed. Addition of NaN3 to
NOM, however, inhibited the reduction of LMW matter,
indicating that microbial activity accounted for the
observed changes in NOM. Analysis of the bacterial
community composition by denaturing gradient gel electrophoresis
(DGGE) of the amplified 16S rRNA genes
revealed that bacterial communities of non-irradiated and
UV-irradiated NOM were different and that UV selected
for specific members of α-proteobacteria, β-proteobacteria,
and Bacteriodetes. Our results imply that after UV-irradiation
of NOM, specific bacterial members are well adapted
to low pH, high LMW DOC concentrations, and oxidative
stress, and therefore thrive well on UV-irradiated humic
matter.
The authenticity of objects and artifacts is often
the focus of forensic analytic chemistry. In document fraud
cases, the most important objective is to determine the
origin of a particular ink. Here, we introduce a new
approach which utilizes the combination of two analytical
methods, namely Raman spectroscopy and laser-induced
breakdown spectroscopy (LIBS). The methods provide
complementary information on both molecular and elemental
composition of samples. The potential of this hyphenation
of spectroscopic methods is demonstrated for ten blue
and black ink samples on white paper. LIBS and Raman
spectra from different inks were fused into a single data
matrix, and the number of different groups of inks was
determined through multivariate analysis, i.e., principal
component analysis, soft independent modelling of class
analogy, partial least-squares discriminant analysis, and
support vector machine. In all cases, the results obtained
with the combined LIBS and Raman spectra were found to
be superior to those obtained with the individual Raman or
LIBS data sets.
Hydrothermal carbonization (HTC) can be used for converting the biomass into a carbon-rich material, whose application as a fuel requires higher heating value, whereas soil amendment needs stable carbon. This work was focused on the characterization of hydrochars derived from microcrystalline cellulose. The chars were investigated using elemental analysis, Brunauer–Emmett–Teller technique, nuclear magnetic resonance spectroscopy, Raman, Fourier transform infrared, and electron spin resonance spectroscopy. Severity in temperature between 230 and 270 °C with reaction times between 2 and 10 h only affect the carbon content moderately. The results show that aromatization of HTC chars correlates well with temperature, which was further supported by the increase of organic radicals with decreasing g values at higher temperatures. Based on these results, the energetic use of chars favors mild HTC (T < 230 °C and t ≤ 6 h), while the soil amendement favors serve conditions (T ≥ 230 °C, and t > 6 h).
The leaching behavior of scandium (Sc) from bauxite residues can differ significantly when residues of different geological backgrounds are compared. The mineralogy of the source rock and the physicochemical environment during bauxitization affect the association of Sc in the bauxite i.e., how Sc is distributed amongst different mineral phases and whether it is incorporated in and/or adsorbed onto those phases. The Sc association in the bauxite is in turn crucial for the resulting Sc association in the bauxite residue. In this study systematic leaching experiments were performed on three different bauxite residues using a statistical design of experiments approach. The three bauxite residues compared originated from processing of lateritic and karstic bauxites from
Germany, Hungary, and Russia. The recovery of Sc and Fe was determined by ICP-OES measurements. Mineralogical changes were analyzed by X-ray-diffraction and subsequent Rietveld refinement. The effects of various parameters including temperature, acid type, acid concentration, liquid-to-solid ratio and residence time were studied. A response surface model was calculated for the selected case of citric acid leaching of Hungarian bauxite residue. The investigations showed that the type of bauxite residue has a strong influence. The easily leachable fraction of Sc can vary considerably between the types, reaching ~20–25% in German Bauxite residue and ~50% in Russian bauxite residue. Mineralogical investigations revealed that a major part of this fraction was released from secondary phases such as cancrinite and katoite formed during Bayer processing of the bauxite.
The effect of temperature on Sc and Fe recovery is strong especially when citric acid is used. Based on the exponential relationship between temperature and Fe-recovery it was found to be particularly important for the selectivity of Sc over Fe. Optimization of the model for a maximum Sc recovery combined with a minimum Fe
recovery yielded results of ~28% Sc recovery at <2% Fe recovery at a temperature of 60 ◦C, a citric acid normality of 1.8, and a liquid-to-solid ratio of 16 ml/g. Our study has shown that detailed knowledge about the Sc association and distribution in bauxite and bauxite residue is key to an efficient and selective leaching of Sc
from bauxite residues.
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.
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.
Nitroaromaten und insbesondere Trinitrotoluol (TNT) sind weit verbreitete Spreng- und Umweltschadstoffe. Die größte Herausforderung bei der Detektion von TNT in der Gasphase ist der geringe Dampfdruck. Derzeit werden vielerorts günstige, schnelle, handliche und einfach zu bedienende Alternativen zur klassischen TNT-Analytik entwickelt. Aktuell existieren keine einheitlichen Richtlinien für Sprengstoffsensoren. Hier wird die Entwicklung eines Messplatzes zur Validierung von Sprengstoffsensoren sowie die Erprobung eines kompakten Mustersensors vorgestellt.
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.
Green Fenton-like magnetic nanocatalysts: Synthesis, characterization and catalytic application
(2015)
Five iron oxalate core–shell magnetite nanoparticles catalysts are evaluated as magnetic heterogeneous materials. Simple and efficient procedures for the preparation of magnetic iron oxalate coated nanoparticles are presented. The catalysts are fully characterized using various investigation techniques. Additionally, the formation of photo-sensitized oxygen by spin-trapping using electron spin resonance is investigated. The catalytic activity of two model substrates (carbamazepine and bisphenol A) is also evaluated. The effect of operational parameters (catalyst and H2O2 concentration, UVA light) on the degradation performance of the oxidation process is investigated. The obtained reaction rates depend on the nature of the compound and increase with iron oxide shell thickness of the catalyst. Moreover, these materials show a significant activity during two consecutive tests. The optimum experimental parameters are found to be 1.0 g L-1 of catalysts, 10 mM H2O2, under UVA irradiation. More than 99% of both substrates are removed after 30 min of reaction time under the experimental conditions given above. The results obtained show that the catalysts are suitable candidates for the removal of pollutants in wastewaters by means of the Fenton heterogeneous reaction.
There is a high demand of monitoring in the era of QbD in industrial scale require new approaches to gain data rapidly and of sufficient quality in real time. Raman spectroscopy technology has great potential but not yet shown it fully in process on-line monitoring due to limitations such as i) uncomplete separation between cells and growth media alone, ii) general weak Raman signals of analytes in complex solutions and iii) strong background signals such as the auto-fluorescence, cosmic rays and surrounding lights overlapping the weak Raman signals. Here we demonstrate a Proof-of-Concept on an the example lactic acid bacteria process using a Streptococcus thermophiles fermentation. Results from three different Raman approaches are presented: 1) Time-Gated Raman Spectroscopy (TG-Raman), 2) Surface Enhanced Raman Spectroscopy (SERS) and 3) Raman process spectroscopy with NIR excitation combined with multivariate data analysis (MVDA) using Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR).
The use of magnetic materials as heterogeneous catalysts has attracted increasing attention in the last years since they proved to be promising candidates for water treatment. In the present study, two types of surface-modified magnetite (Fe3O4) nanoparticles, coated with non-hazardous naturally occurring agents—either tannic acid (TA) or dissolved natural organic matter—were evaluated as magnetic heterogeneous catalysts. Chemical synthesis (co-precipitation) was chosen to yield the nanocatalysts due to its well-established simplicity and efficiency. Subsequently, the properties of the final products were fully assessed by various characterization techniques. The catalytic activity in heterogeneous oxidation of aqueous solutions containing a model pollutant, Bisphenol A (BPA), was comparatively studied. The effect of operational parameters (catalyst loading, H2O2 dosage, and UV light irradiation) on the Degradation performance of the oxidation process was investigated. The optimum experimental parameters were found to be 1.0 g/L of catalysts and 10 mM H2O2, under UV irradiation. The highest mineralization rates were observed for Fe3O4-TA catalyst. More than 80 % of BPA was removed after 30 min of reaction time under the specified experimental conditions. The obtained results showed that the two catalysts studied here are suitable candidates for the removal of pollutants in wastewaters by means of heterogeneous reaction using a green sustainable treatment method.
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.
The increasing pollution of terrestrial and aquatic ecosystems with plastic debris leads to the accumulation of microscopic plastic particles of still unknown amount. To monitor the degree of contamination analytical methods are urgently needed, which help to quantify microplastics (MP). Currently, time-costly purified materials enriched on filters are investigated both by micro-infrared spectroscopy and/or micro-Raman. Although yielding precise results, these techniques are time consuming, and are restricted to the analysis of a small part of the sample in the order of few micrograms. To overcome these problems, here we tested a macroscopic dimensioned NIR process-spectroscopic method in combination with chemometrics. For calibration, artificial MP/soil mixtures containing defined ratios of polyethylene, polyethylene terephthalate, polypropylene, and polystyrene with diameters < 125 µm were prepared and measured by a process FT-NIR spectrometer equipped with a fiber optic reflection probe. The resulting spectra were processed by chemometric models including support vector machine regression (SVR), and partial least squares discriminant analysis (PLS-DA). Validation of models by MP mixtures, MP-free soils and real-world samples, e.g. and fermenter residue, suggest a reliable detection and a possible classification of MP at levels above 0.5 to 1.0 mass% depending on the polymer. The benefit of the combined NIRS chemometric approach lies in the rapid assessment whether soil contains MP, without any chemical pre-treatment. The method can be used with larger sample volumes and even allows for an online prediction and thus meets the demand of a high-throughput method.
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.
Die Untersuchungen sind durch das das DFG Schwerpunktprogramm 1374 für Biodiversitätsforschung motiviert. Anhand des überwachten Abbaus von Totholz soll untersucht werden, welche Auswirkung unterschiedliche Formen und Intensitäten der Landnutzung auf die Biodiversität innerhalb von drei Exploratorien zeigen. Bei den vorangegangenen Studien wurden Nahrungs¬netzte auf organismischer Ebene sowie Klima- und Umgebungsdaten untersucht und die Veränderung des ausgebrachten Totholzes als Masseverlust erfasst. Es wird jedoch erwartet, dass in Anhängigkeit der beteiligten Organismen und Umgebungsparameter verschiedene Mechanismen des Holzabbaus vorliegen, die in unterschiedlichen Abbauraten der Holzkomponenten Lignin, Cellulose und Hemicellulose resultieren. Aus diesem Grund ist die quantitative Untersuchung des Ligningehalts an Hölzern ein wesentlicher Schritt für ein verbessertes Verständnis der Biodiversität in den untersuchten Exploratorien. Um der hohen Probenanzahl, die sich aus der Kontrolle von jeweils 100 Proben (Plots) in den drei Exploratorien für Hölzer aus 13 Baumarten ergibt, gerecht zu werden, wird eine schnelle und effiziente Untersuchungsmethode benötigt. Diese wird derzeit in Form einer NIR-spektroskopischen Bestimmung des Ligningehalts entwickelt. Um basierend auf den NIR Spektren vermahlener Holzproben Lignin und weitere Holzkomponenten korrekt vorherzusagen, muss zunächst basierend auf nasschemischen Analysen ein chemometrisches Modell kalibriert werden. Dazu ist die Charakterisierung von mindestens 20 – 30 Proben, die eine hohe Varianz des Ligningehalts aufweisen, notwendig. Im Vortrag werden erste Untersuchungs¬ergebnisse für die Vorhersage des Ligningehalts von Kiefernhölzern, die für ein Jahr in dem Exploratorium Schorfheide exponiert wurden, vorgestellt. Die anschließende explorative Datenanalyse (PCA) unter Verwendung von insgesamt 28 Variablen zur Beschreibung klimatischer und Umgebungsparameter weist eine Reihe interessanter Korrelationen auf. Demnach ist der Ligningehalt auf der ersten Hauptkomponente (29% erklärte Varianz) positiv mit dem C/N-Verhältnis und negativ mit Landnutzungsindex korreliert. Masseverlust und Temperatur hingegen dominieren die zweite Hauptkomponente (12% erklärte Varianz).
The transformation of a base-catalyzed, mechano-assisted Knoevenagel condensation of mono-fluorinated benzaldehyde derivatives (p-, m-, o-benzaldehyde) with malonodinitrile was investigated in situ and in real time. Upon milling, the para-substituted product was found to crystallize initially into two different polymorphic forms, depending on the quantity of catalyst used. For low catalyst concentrations, a mechanically metastable phase (monoclinic) was initially formed, converting to the mechanically stable phase (triclinic) upon further grinding. Instead, higher catalyst concentrations crystallize directly as the triclinic product. Inclusion of catalyst in the final product, as evidenced by mass spectrometric analysis, suggests this complex polymorphic pathway may be due to seeding effects. Multivariate analysis for the in situ Raman spectra supports this complex formation pathway, and offers a new approach to monitoring multi-phase reactions during ball milling.
Two iron-based molten salts comprising an imidazolium and Schiff base were evaluated as catalysts for removal of carbamazepine (CBZ) from water. The catalysts were fully characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectrometry (EDX), nuclear magnetic resonance spectroscopy (NMR), electrospray ionisation–mass spectrometry (ESI–MS), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR) and nitrogen adsorption–desorption isotherms (BET). Additionally, the formation of photo-sensitized oxygen was investigated by spin-trapping using electron spin resonance (ESR). The catalytic activity in heterogeneous oxidation of the micropollutant (CBZ) was also evaluated. The effects of catalyst loading, pH, H2O2 dosage and UV light on the oxidation of the selected compound were investigated. After 15 min of UVA irradiation in the presence of 200 μM H2O2, CBZ was completely removed over both catalysts.
The catalytic behavior of iron phthalocyanine (FePc)-sensitized magnetic nanocatalysts was evaluated for their application in the oxidative treatment of Bisphenol A (BPA) under mild environmental conditions. Two types of FePc (Fe(II)Pc and Fe(III)Pc), which are highly photosensitive compounds, were immobilized on the surface of functionalized magnetite. The nanomaterials were characterized by high resolution transmission electron microscopy (HR-TEM), X-ray difraction (XRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analyses (TGA). The generation of singlet Oxygen by nanomaterials was also investigated. In the presence of UVA light exposure (365nm) and 15mM H2O2, the M@Fe(III)Pc photocatalyst gave the best results; for a catalyst concentration of 2.0gL −1, around 60% BPA was removed after 120min of reaction. These experimental conditions were further tested under natural solar light exposure, for which also M@Fe(III)Pc exhibited enhanced oxidative catalytic activity, being able to remove 83% of BPA in solution. The water samples were less cytotoxic after treatment, this being confrmed by the MCF-7 cell viability assay.
Exploratory analysis of hyperspectral FTIR data obtained from environmental microplastics samples
(2020)
Hyperspectral imaging of environmental samples with infrared microscopes is one of the preferred methods to find and characterize microplastics. Particles can be quantified in terms of number, size and size distribution. Their shape can be studied and the substances can be identified. Interpretation of the collected spectra is a typical problem encountered during the analysis. The image datasets are large and contain spectra of countless particles of natural and synthetic origin. To supplement existing Analysis pipelines, exploratory multivariate data analysis was tested on two independent datasets. Dimensionality reduction with principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) was used as a core concept. It allowed for improved visual accessibility of the data and created a chemical two-dimensional image of the sample. Spectra belonging to particles could be separated from blank spectra, reducing the amount of data significantly. Selected spectra were further studied, also applying PCA and UMAP. Groups of similar spectra were identified by cluster analysis using k-means, density based, and interactive manual clustering. Most clusters could be assigned to chemical species based on reference spectra. While the results support findings obtained with a ‘targeted analysis’ based on automated library search, exploratory analysis points the attention towards the group of unidientified spectra that remained and are otherwise easily overlooked.
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.
The increasing enrichment of water bodies and soils with plastic waste leads to the accumulation of microscopic plastic particles, so-called microplastics (MP). There is an urgent need for analytical methods that help to identify and quantify MP. At present, mainly thermo-analytical and microscopic methods such as micro-infrared spectroscopy or micro-Raman are used for this purpose. The latter are usually tied to time-consuming sample enrichment and preparation, only small sample quantities (micrograms) can be examined and the evaluation of the obtained spectra can be demanding. In the context of this presentation, two approaches are presented which, via the multi-variate analysis of spectroscopic data, allow i) a new methodological approach to screening MP in contaminated soils and ii) an alternative evaluation of large (micro)-spectroscopic data sets.
First, a NIR spectroscopic method is presented which allows MP consisting of polyethylene, polyethylene terephthalate, polypropylene and polystyrene to be detected in the range of up to 0.5 mass percent. Due to short measurement times and robust technology, this approach has the potential, in contrast to thermo-analytical and micro-spectroscopic methods, to examine larger sample quantities with minimal pre-treatment.
The second approach deals with the evaluation of large data sets, as typically obtained as a result of micro-FTIR using modern FPA detectors. The micro-FTIR technique is based on the spectral recording, imaging and subsequent identification of vibration bands typical of synthetic polymers. The image data sets are large and contain spectra of numerous particles of natural and synthetic origin. Exploratory multivariate data analysis has been tested to complement existing approaches based on e.g. spectrum library searches. The core concept used was dimensionality reduction. The results not only represent an orthogonal method for checking the results obtained by an automated library search, but also revealed a group of spectra that were not recorded in the existing spectrum libraries.
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.
Green Fenton-like magnetic nanocatalysts: Synthesis, characterization and catalytic application
(2015)
Five iron oxalate core–shell magnetite nanoparticles catalysts are evaluated as magnetic heterogeneous materials. Simple and efficient procedures for the preparation of magnetic iron oxalate coated nanoparticles are presented. The catalysts are fully characterized using various investigation techniques. Additionally, the formation of photo-sensitized oxygen by spin-trapping using electron spin resonance is investigated. The catalytic activity of two model substrates (carbamazepine and bisphenol A) is also evaluated. The effect of operational parameters (catalyst and H2O2 concentration, UVA light) on the degradation performance of the oxidation process is investigated. The obtained reaction rates depend on the nature of the compound and increase with iron oxide shell thickness of the catalyst. Moreover, these materials show a significant activity during two consecutive tests. The optimum experimental parameters are found to be 1.0 g L−1 of catalysts, 10 mM H2O2, under UVA irradiation. More than 99% of both substrates are removed after 30 min of reaction time under the experimental conditions given above. The results obtained show that the catalysts are suitable candidates for the removal of pollutants in wastewaters by means of the Fenton heterogeneous reaction.
Two types of surface modified magnetite (Fe3O4) nanoparticles, coated with either tannic acid (TA) or dissolved natural organic matter (NOM), were evaluated as magnetic heterogeneous catalysts. Simple and efficient procedures for the synthesis of the magnetic catalysts were employed, their properties being fully assessed by various characterization techniques. The catalytic activity in heterogeneous oxidation of aqueous solutions containing Bisphenol A (BPA) over the catalysts was comparatively studied. The optimum experimental parameters were: 1g/L of catalysts, 10 mM H2O2, under UV irradiation. The highest mineralization rates were observed for Fe3O4-TA catalyst. More than 80% of BPA were removed after 30 minutes of reaction time under the specified experimental conditions. The results showed that the obtained catalysts are suitable candidates for the removal of pollutants in wastewaters by means of heterogeneous reaction
With a more and more general acceptance of accreditation in the field of reference materials production, and an ever increasing number of RMP accredited, accreditation bodies face applications from RMP active in the field of qualitative RM production.
While (the still valid and used for accreditation purposes) ISO Guides 34 and 35 describe in detail requirements applicable to RMP dealing with quantitative RM, accreditation bodies normally claim lack of normative requirements with respect to quantitative RM. The new ISO 17034:2016 which will be introduced in the accreditation practice over the next two to three years solves the problem pragmatically, allowing strategies for RM certification other than those for (purely) quantitative materials.
In fact, both ISO Guide 34 and the new ISO 17034 are written in a form that, at least for the overwhelming majority of requirements, may be applied to RMP of both qualitative and quantitative RM. Peculiarities may occur in homogeneity and stability testing, and the uncertainty of a purely qualitative result is still under discussion. The problem of traceability might be solved for most of the application fields considered.
The talk gives an overview of the specific problems encountered, and provides some possible solutions both for homogeneity and stability testing, the expression of uncertainty, and the statement of traceability in certificates.
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.
Ziele und Durchführung eines geplanten Ringversuchs zur Untersuchung eines Dreikomponentensystems mittels NIR werden vorgestellt. Der Vortrag enthält einen kurzen Rückblick auf einen 2014 durchgeführten Ringversuch, wobei ein flüssiges Zweikomponentensystem untersucht wurde. Im Anschluss erfolgt die Erläuterung der verwendeten Komponenten, es werden Teilnahmebedingungen und mögliche Zeiträume bekannt gegeben.
More than 80 representatives of SMEs, industrial companies and research institutes met on September 12 at the workshop "Challenges in Additive Manufacturing: Innovative Materials and Quality Control" at BAM in Adlershof to discuss the latest developments in materials and quality control in additive manufacturing.
In special lectures, researchers, users and equipment manufacturers reported on the latest and future developments in additive manufacturing. Furthermore, funding opportunities for projects between SMEs and research institutions on a national and European level were presented.
Im DFG-Schwerpunktprogramm 1374, Teilprojekt FunWood IV, erfolgt in Kooperation mit dem Institut für Bioanalytik an Hochschule für angewandte Wissenschaften, Coburg und dem Helmholtz-Zentrum für Umweltforschung (UFZ), Leipzig die Untersuchung des Ligningehalts von natürlich gealterten Hölzern. Zu diesem Zweck soll an der BAM eine NIR spektroskopische Methode entwickelt werden, die auch zur Untersuchung großer Stückzahlen geeignet ist. Insgesamt liegen exponierte Proben von 13 verschiedenen Hölzern vor, die sukzessive durch die Kooperationspartner kryovermahlen und getrocknet werden. Für jede der 13 Arten wurden jeweils 300 Holzstücken ausgebracht, exponiert und im Sommer 2018 wieder eingesammelt. Die Ergebnisse sollen als Grundlage für die Bewertung eines Langzeitversuchs zum Einfluss von Waldbewirtschaftungsintensität und Baumartenidentität über mehrere geographische Dimensionen dienen.
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.
Multivariate data analysis is a universal tool for the evaluation of process spectroscopic data. In process analytics, huge amounts of information are produced i) by the many variables contained in one spectrum often exceeding 1000 (wavenumbers, wavelength, shifts…), and ii) the high number of spectra that is generated within the measurement period. Multivariate data analysis, often also called Chemometrics, help to extract the relevant information which is needed to examine and even control processes. Therefore, calibration models must be precise and robust, and moreover, must cover a wide range of variation of factors posing an influence on the process.
In this pre-conference course an introduction to both, explorative data analysis by PCA (Principal Component Analysis), and regression analysis by the most frequently used method, i.e. PLSR (Partial Least Squares Regression) is given. In principal, all optical spectroscopic methods are suited for multivariate evaluation. It will be demonstrated that under certain preconditions, even process NMR spectra can be predicted by PLSR models.
At first, basic principles of multivariate data analysis will be provided. This includes a short introduction into the concept of model building and interpretation of results. Detailed aspects of data pretreatment and calibration & validation strategies for chemometric models will be provided with own data from NIR, Raman and NMR spectroscopy.
In a first example, the development of an online compatible method for the quantification of methanol in biodiesel by PLSR is presented. This also includes the classification of biodiesel feedstocks by PCA and statistical tools which allow for the estimation of a full uncertainty budget.
The Raman spectroscopic prediction of Hydroformylation reaction in a miniplant is used to discuss shortcomings and pitfalls which may occur with the transfer of off-line models to the real processes. Design of experiment and strategies for suitable lab-scale experiments are presented as a possible way to overcome problems.
In a third application the prediction of the reactants of an esterification reaction based on process NMR data is demonstrated.
The interaction of microcroplastics (MP) with dissolved organic matter, especially humic substances, is of great importance in understanding the behavior of microplastics in aquatic ecosystems. Surface modification by humic substances plays an essential role in transport and interaction of MP with abiotic and biotic components. Previous studies on the interaction between MP and humic substances were largely based on a model compound, humic acid (Sigma-Aldrich). In our work, we therefore investigated the interaction of natural organic matter (NOM) sampled from a German surface water with low-density polyethylene particles (LDPE). Highpressure size exclusion chromatography (HPSEC) and UV/vis absorption and fluorescence spectroscopy were used to characterize the incubation solutions after modifications due to the presence of LDPE, and Raman spectroscopy was used to characterize the incubated microplastics. While the studies of the solutions generally showed only very small effects, Raman spectroscopic studies allowed clear evidence of the binding of humic fractions to MP. The comparison of the incubation of NOM and a lignite fulvic acid which also was tested further showed that specific signatures of the humic substances used could be detected by Raman spectroscopy. This provides an elegant opportunity to conduct broader studies on this issue in the future.
In Deutschland werden jährlich rund 20 Millionen Tonnen künstliche Mineralwolle für die Dämmung von Dächern und Fassaden sowie für Brandschutzprodukte verwendet. Um künstliche Mineralwolle aus Rückbaumaßnahmen in den Produktionsprozess zurückführen zu können, ist eine Trennung in Glas- und Steinwolle erforderlich, um eine Vermischung der beiden Produkte, die unterschiedliche Schmelztemperaturen aufweisen, zu vermeiden. Anstatt die Mineralwolle in spezielle Labors zu schicken, was zeitaufwendig und teuer ist, wurde das Potenzial eines tragbaren Nahinfrarot-Spektrometers (NIR) für den Einsatz vor Ort getestet. 140 verschiedene Mineralwolleproben wurden untersucht, um eine NIR-basierte Methode für die Vor-Ort-Unterscheidung zwischen Glas- und Steinwolle zu etablieren. Die Validierung der Methode mit Testproben und die Anwendung auf Materialien, die aus BigBags für Deponien entnommen wurden, haben gezeigt, dass die Methode präzise und robust ist. Als Referenzmethode wurde die Röntgenfluoreszenzspektroskopie (RFA) mit einer Kalibrierung auf der Grundlage der VDI 3492 verwendet.
Modular plants using intensified continuous processes represent an appealing concept to produce pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes, and it enables plug-and-produce reconfiguration for fast product changes. To facilitate this flexibility by real-time quality control, we developed a solution that can be adapted quickly to new processes and includes a compact Nuclear Magnetic Resonance (NMR) spectrometer for online quality monitoring as well as a new model-based control approach. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including ro-bust evaluation of sensor data.
Here, we present alternatives for the quantitative determination of the analytes using modular, physically motivated models. These models can be adapted to new substances solely by the use of their corresponding pure component spectra, which can either be derived from experimental spectra as well as from quantum mechanical models or NMR predictors. Modular means that spec-tral models can simply be exchanged together with alternate reagents and products. Beyond that, we comprehensively calibrated an NIR spectrometer based on online NMR process data for the first time within an industrial plant. The integrated solution was developed for a metal organic reac-tion running on a commercial-scale modular pilot plant and it was tested under industrial conditions.
Raman spectroscopy for online monitoring of a homogeneous hydroformylation process in microemulsion
(2021)
An important industrial reaction is hydro¬formylation for the production of aldehydes from alkenes and syngas on the basis of homogeneous catalysis. The main cost factors of the processes currently used are product selectivity and the loss of the catalysts used. Therefore, various concepts for the hydroformylation of long-chain olefins have been developed, including hydroformylation in microemulsions, which is being investigated on a mini-plant scale at the Technical University of Berlin [1]. In this study, online Raman spectroscopy of the reaction of 1-dodecene to 1-tri¬decanal in a microemulsion was performed [2]. First, an experimental design was used to obtain a good representation of the operating range in the mini plant with respect to the concentrations of five reactants in a laboratory setup [3]. Based on the Raman spectra, Partial Least Squares (PLS) models for the prediction of 1-dodecene and 1-tride-decanal were calibrated and with these the reactions were predicted on a laboratory scale. In the next step, the PLS models were applied to online spectra from a mini-plant. This resulted in promising estimates of 1-tridecanal and acceptable predictions of 1-dodecene mass fractions. The predictive power of PLS models in this particular case was limited by unexpected by-product formation which, however, can easily be compensated by an extended calibration. Hence, Raman spectroscopy is a promising technique for process analysis in microemulsions.