Filtern
Erscheinungsjahr
Dokumenttyp
- Zeitschriftenartikel (39)
- Vortrag (26)
- Beitrag zu einem Tagungsband (18)
- Posterpräsentation (14)
- Corrigendum (1)
- Forschungsdatensatz (1)
Schlagworte
- Chemometrics (12)
- NIR (9)
- Microplastics (8)
- Raman (8)
- Process analytical technology (6)
- Prozessanalytik (6)
- Raman spectroscopy (6)
- Hydroformylation (5)
- Reaction monitoring (5)
- Chemometrie (4)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (18)
- 1.4 Non-Target-Analytik (17)
- 6 Materialchemie (7)
- 6.1 Oberflächen- und Dünnschichtanalyse (3)
- 6.6 Digitale Materialchemie (3)
- 1.3 Instrumentelle Analytik (1)
- 1.6 Anorganische Referenzmaterialien und Gasanalytik (1)
- 4 Material und Umwelt (1)
- 4.4 Thermochemische Reststoffbehandlung und Wertstoffrückgewinnung (1)
- 6.3 Strukturanalytik (1)
Paper des Monats
- ja (2)
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.
Medium-resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and processmonitoring. In contrast to high-resolution onlineNMR (HR-NMR),MR-NMRcan be operated under rough environmental conditions. A continuous re-circulating stream of reaction mixture fromthe reaction vessel to the NMR spectrometer enables a non-invasive, volume integrating online analysis of reactants and products. Here, we investigate the esterification of 2,2,2-trifluoroethanol with acetic acid to 2,2,2-trifluoroethyl acetate both by 1H HR-NMR (500MHz) and 1H and 19F MRNMR (43MHz) as amodel system. The parallel online measurement is realised by splitting the flow,which allows the adjustment of quantitative and independent flow rates, both in the HR-NMR probe as well as in the MR-NMR probe, in addition to a fast bypass line back to the reactor. 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 are treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprise (i) direct integration, (ii) automated line fitting, (iii) indirect hard modelling (IHM) and (iv) partial least squares regression (PLS-R). To assess the potential of these evaluation strategies for MR-NMR, prediction results are compared with the line fitting data derived from the quantitative HR-NMR spectroscopy. Although, superior results are obtained from both IHM and PLS-R for 1H MR-NMR, especially the latter demands for elaborate data pretreatment, whereas IHM models needed no previous alignment.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environ¬ments for advanced process monitoring and control, as demonstrated within the European Union’s Horizon 2020 project CONSENS.
We present a range of approaches for the automated spectra analysis moving from conventional multivariate statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants or derivatives and robust automation schemes.
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).
Supernatants from a fermentation process of Pichia pastoris were investigated by Raman spectroscopy. Using partial least squares regression, the principal substrates glycerol and methanol could be predicted, however not the expressed protein. To gain further insight, a priori prepared calibration samples were studied by vibrational-, UV/Vis-, and fluorescence spectroscopy. For the quantification of glycerol and methanol, Raman spectroscopy was identified as the most sensitive technique, and superior to near-infrared spectroscopy, but not for protein contents below 1 g L–1. Both UV/Vis absorption and fluorescence spectroscopy are well suited for the quantification of protein, however, best results were obtained with UV/Vis absorption.
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.
Der Beitrag beinhaltet die Vorstellung eines gemeinsamen Projekts zwischen der BAM und der TU Berlin (Process Dynamics and Operations Group). Mittels Raman Spektroskopie werden Hydroformylierungsreaktionen in einer Miniplant der TU prozessbegleitend untersucht. Kalibrationsstrategien, Laboruntersuchungen sowie Vorhersagen von Prozessmessungen basierend auf chemometrischen Modellen werden vorgestellt. Zum gegenwärtigen Zeitpunkt wird die Strategie als erfolgsversprechend bewertet, jedoch sind weitere Untersuchungen insbesondere zum Einfluss der Microemulsion auf die Ramanspektren notwendig.
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.
Zur Onlineüberwachung von Fermentationsprozessen werden zunehmend schwingungsspektroskopische (Raman-, Mittel- und Nahinfrarotspektroskopie (NIRS) und UV-/VIS- Methoden(Absorptions- und Fluoreszenzspektroskopie) in Kombination mit multivariater Auswertung eingesetzt. Anliegen dieser Arbeit war es, zu testen, welche Verfahren für die spektroskopische On- und Offlineüberwachung des Fermentationsprozesses zur biotechnologischen Herstellung einer Malariavaccine grundlegend geeignet sind und welche Messbereiche und Genauigkeiten der Vorhersage im Idealfall bei der Abwesenheit von Hefezellen erzielt werden können.
