1.4 Prozessanalytik
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Eingeladener Vortrag
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Für die Rückführung von aus Rückbauprojekten anfallender künstlicher Mineralwolle in ihren Herstellungsprozess ist es notwendig, Stein- und Glaswolle zu unterscheiden und voneinander getrennt zu halten. Zu diesem Zweck wurde das Potential von NIR-Spektroskopie (NIRS) für einen werks- oder baustellenseitigen Einsatz getestet. NIRS wird aufgrund kurzer Messzeiten, minimaler Probenvorbereitung und hoher Robustheit der Spektrometer häufig in der Prozessanalytik eingesetzt. Untersucht wurden 70 verschiedene Mineralwollen, wobei sich der Probenumfang sowohl aus werksneuen Proben mit Herstellerangaben als auch unbekannten Proben ohne Spezifikation zusammensetzen, die auf verschiedenen Baustellen in den Jahren 2016–2017 entnommen oder von Deponien zur Verfügung gestellt worden waren. Als Referenzmethode wurde die Röntgenfluoreszenzanalyse verwendet, um den Mineralwolle-Typ über den Elementgehalt nach VDI 3492 zu identifizieren. Mit Hilfe eines multivariaten Datenanalyseverfahrens konnte schließlich eine Methode etabliert werden, die eine zuverlässige Identifikation von unbekannten Mineralwollen anhand deren NIR-Spektren als Stein- bzw. Glaswolle ermöglicht.
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.
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.
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.
Künstliche Mineralfasern (KMF) werden weltweit in vielfältiger Weise als Dämmstoffe verwendet. Jährlich fallen in Deutschland ungefähr 20 Millionen Tonnen KMF an, die nach dem Abriss auf Deponien entsorgt werden müssen. Grundsätzlich besteht jedoch die Möglichkeit der Rückführung dieser Materialien in den Produktionsprozess. Dafür ist es notwendig, anfallende KMF sowohl nach Material (Glaswolle, Steinwolle) als auch nach Alter zu sortieren.
Auf der Suche nach einer Methode, die es grundsätzlich gestattet eine schnelle Untersuchung vor Ort auf einer Baustelle durchzuführen, wurde die Nah-Infrarot (NIR) Spektroskopie unter Verwendung eines Prozessspektrometers mit Reflexionssonde getestet. Anhand von Laboruntersuchungen an 70 KMF Proben, die entweder betriebsneu waren oder bundesweit auf Baustellen gesammelt wurden, konnte eine NIR-basierte Methode zur Unterscheidung in Glas- und Steinwolle entwickelt werden. Mittels Partial Least Square Diskriminanzanalyse (PLS-DA) der NIR Spektren wurde basierend auf 40 zufällig ausgewählten Proben ein chemometrisches Modell kalibriert, das erfolgreich zur Klassifizierung der verbleibenden 30 Proben eingesetzt werden konnte. Unabhängig von Farbe, Dichte oder Alter der untersuchten KMF Proben war es möglich, eine 100% korrekte Zuordnung des Materials zu erzielen. Die nötigen Referenzwerte wurden unter Nutzung eines Röntgenfluoreszenzspektroskopischen Verfahrens über den Elementgehalt nach VDI 3492 ermittelt.
Insgesamt ist der experimentelle Aufwand für die Durchführung und Auswertung der NIR Messungen gering und manifestiert sich vor allem in der Kalibrierphase, die in diesem Fall die Untersuchung von 8-fach aliquotierten Probestücken der 70 KMF umfasste. Nur bei deutlich feuchtem Material muss ein zusätzlicher Trocknungs-schritt berücksichtigt werden. Das vorgestellte Verfahren wurde nachfolgend zu einem Patent angemeldet. Untersuchungen zu einer weiteren Unterscheidung der KMF nach Alter sind geplant.
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.
In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum.
The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.
In the following the contents of the files are explained.
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.
Spectroscopic methods possess important advantages for the observation of bioprocesses: they are robust, gain many data within a short time scale, and allow for the measurement of multiple relevant information at the same time. Next to Near-infrared spectroscopy, Raman spectroscopy is increasingly applied as a powerful online tool to monitor bioprocesses. However, Raman spectra may be obscured by straylight, cosmic rays and fluorescence. To achieve the best performance, optimal conditions for spectral quality and stability should be pursued. This comprises not only the choice of highly-sensitive equipment, but also the way of implementation into the process. Here we compared the potential of introducing a sterilized fiber optical Raman probe, and a flow-through cell into the bypass of a stirred tank reactor to monitor an autotrophic cultivation of Ralstonia eutropha where gasses are the energy and carbon sources. Raman spectra were continuously recorded over seven days and 22 samples were taken for the reference analytics of biomass, optical density, and protein. In addition, data for of phosphate and ammonium were available. The quantitative Evaluation of Raman spectra by Partial Least Squares Regression (PLSR) yielded comparable results for both approaches, however, there was a general trend of lower prediction errors with the immersion probe.
The better performance of the non-contact optic may be either related to a more representative interaction of the measurement optics with the probe or simply to the absence of probe-fouling, which was observed with the immersion optic in the interstice between window and metal frame.
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.