Filtern
Erscheinungsjahr
Dokumenttyp
Referierte Publikation
- ja (30) (entfernen)
Schlagworte
- Chemometrics (4)
- Multivariate data analysis (3)
- NIR (3)
- Process analytical technology (3)
- Acid (2)
- CONSENS (2)
- Characterization (2)
- Electron-acceptors (2)
- Ferric iron (2)
- Groundwater (2)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (15)
- 1.4 Prozessanalytik (14)
- 6 Materialchemie (2)
- 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)
- 6.3 Strukturanalytik (1)
Paper des Monats
- ja (1)
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.
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.
Reaction monitoring in disperse systems, such as emulsions, is of significant technical importance in various disciplines like biotechnological engineering, chemical industry, food science, and a growing number other technical fields. These systems pose several challenges when it comes to process analytics, such as heterogeneity of mixtures, changes in optical behavior, and low optical activity. Concerning this, online nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for process monitoring in complex reaction mixtures due to its unique direct comparison abilities, while at the same time being non-invasive and independent of optical properties of the sample. In this study the applicability of online-spectroscopic methods on the homogeneously catalyzed hydroformylation system of 1-dodecene to tridecanal is investigated, which is operated in a mini-plant scale at Technische Universität Berlin. The design of a laboratory setup for process-like calibration experiments is presented, including a 500 MHz online NMR spectrometer, a benchtop NMR device with 43 MHz proton frequency as well as two Raman probes and a flow cell assembly for an ultraviolet and visible light (UV/VIS) spectrometer. Results of high-resolution online NMR spectroscopy are shown and technical as well as process-specific problems observed during the measurements are discussed.
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.
Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies.
We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (Indirect Hard Modelling – IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analysed by IHM with low calibration effort, compared to a multivariate PLS-R (Partial Least Squares Regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy.
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.
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 application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here, we compare time-gated Raman (TG-Raman)-, continuous wave NIRprocess Raman (NIR-Raman), and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP, and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids, and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis.
Flexible automation with compact NMR spectroscopy for continuous production of pharmaceuticals
(2019)
Modular plants using intensified continuous processes represent an appealing concept for the production of pharmaceuticals. It can improve quality, safety, sustainability, and profitability compared to batch processes; besides, 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 is based on a compact nuclear magnetic resonance (NMR) spectrometer. The NMR sensor is a benchtop device enhanced to the requirements of automated chemical production including robust evaluation of sensor data. Beyond monitoring the product quality, online NMR data was used in a new iterative optimization approach to maximize the plant profit and served as a reliable reference for the calibration of a near-infrared (NIR) spectrometer. The overall approach
was demonstrated on a commercial-scale pilot plant using a metal-organic reaction with pharmaceutical relevance.