Klas Meyer

Simultaneous (19)F-(1)H medium resolution NMR spectroscopy for online reaction monitoring.

Medium resolution nuclear magnetic resonance (MR-NMR) spectroscopy is currently a fast developing field, which has an enormous potential to become an important analytical tool for reaction monitoring, in hyphenated techniques, and for systematic investigations of complex mixtures. The recent developments of innovative MR-NMR spectrometers are therefore remarkable due to their possible applications in quality control, education, and process monitoring. MR-NMR spectroscopy can beneficially be applied for fast, non-invasive, and volume integrating analyses under rough environmental conditions. Within this study, a simple 1/16″ fluorinated ethylene propylene (FEP) tube with an ID of 0.04″ (1.02mm) was used as a flow cell in combination with a 5mm glass Dewar tube inserted into a benchtop MR-NMR spectrometer with a 1H Larmor frequency of 43.32MHz and 40.68MHz for 19F. For the first time, quasi-simultaneous proton and fluorine NMR spectra were recorded with a series of alternating 19F and 1H single scan spectra along the reaction time coordinate of a homogeneously catalysed esterification model reaction containing fluorinated compounds. The results were compared to quantitative NMR spectra from a hyphenated 500MHz online NMR instrument for validation. Automation of handling, pre-processing, and analysis of NMR data becomes increasingly important for process monitoring applications of online NMR spectroscopy and for its technical and practical acceptance. Thus, NMR spectra were automatically baseline corrected and phased using the minimum entropy method. Data analysis schemes were designed such that they are based on simple direct integration or first principle line fitting, with the aim that the analysis directly revealed molar concentrations from the spectra. Finally, the performance of 1/16″ FEP tube set-up with an ID of 1.02mm was characterised regarding the limit of detection (LOQ (1H)=0.335molL-1 and LOQ (19F)=0.130molL-1 for trifluoroethanol in D2O (single scan)) and maximum quantitative flow rates up to 0.3mLmin-1. Thus, a series of single scan 19F and 1H NMR spectra acquired with this simple set-up already presents a valuable basis for quantitative reaction monitoring.

Automated data evaluation and modelling of simultaneous 19F–1H medium-resolution NMR spectra for online reaction monitoring

Medium‐resolution nuclear magnetic resonance spectroscopy (MR‐NMR) currently develops to an important analytical tool for both quality control and process monitoring. In contrast to high‐resolution online NMR (HR‐NMR), MR‐NMR can be operated under rough environmental conditions. A continuous re‐circulating stream of reaction mixture from the 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 (500 MHz) and 1H and 19F MR‐NMR (43 MHz) as a model 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. Copyright

2.1 - Innen hui und außen pfui – Smarte Prozess-Sensoren in der gegenwärtigen Automatisierungslandschaft der Prozessindustrie

Prozess-Sensoren 4.0 vereinfachen ihre Einbindung uber Plug and Play, obwohl sie komplexer werden. Sie bieten Selbstdiagnose, Selbstkalibrierung und erleichterte Parametrierung. Uber die Konnektivitat ermoglichen die Prozess-Sensoren den Austausch ihrer Informationen als Cyber-physische Systeme mit anderen Prozess-Sensoren und im Netzwerk. Der Wandel von der aktuellen Automation zum smarten Sensor ist im vollen Gange. Automatisierungstechnik und Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. Eine Topologie fur smarte Sensoren, die das Zusammenwirken mit daten- und modellbasierte Steuerungen bis hin zur Softsensorik beschreibt gibt es heute jedoch noch nicht. Wir mussen jetzt schnell die Weichen fur eine smarte und sichere Kommunikationsarchitektur stellen, um zu einer storungsfreien Kommunikation aller Komponenten auf Basis eines einheitlichen Protokolls zu kommen. Unnotiges Schnickschnack ist nicht erwunscht. Wenn die Prozessindustrie dieses nicht definiert, tun es andere. Fur die weitere Entwicklung von der Ist‐Situation zu einer Industrie-4.0-Welt in der Prozessindustrie werden mehrere Szenarien diskutiert. Diese reichen vom erleichterten Abruf sensorbezogener Daten uber zusatzliche Kommunikationskanale zwischen Sensor und mobilen Endgeraten uber vollstandig bidirektionale Kommunikation bis hin zur Einbindung der Cloud und des Internets in virtualisierte Umgebungen. Um zu einer storungsfreien Kommunikation aller Komponenten untereinander zu kommen, muss mindestens ein einheitliches Protokoll her, das alle sprechen und verstehen. Der derzeit greifbarste offengelegte Standard, der moderne Kommunikationsanforderungen erfullt, ist OPC Unified Architecture (OPC-UA). Viele halten das Sortieren der Kommunikationsstandards fur eines der wesentlichen Errungenschaften von Industrie 4.0. Der Vortrag greift die Anforderungen der Technologie-Roadmap „Prozess-Sensoren 4.0“ auf und zeigt Moglichkeiten zu ihrer Realisierung am Beispiel eines Online-NMR-Analysators, der im Rahmen des EU-Projekts „CONSENS“ (www.consens-spire.eu) entwickelt wurde. Aktuelle und zukunftige offentliche Forderung von Industrie 4.0-Projekten sind eine gute Investition. Wegen der hohen Komplexitat und Interdisziplinaritat gelingt die Umsetzung nur gemeinsam zwischen Anwendern aus der Prozessindustrie, Software- und Gerateherstellern sowie Forschungsgruppen. Anwender sind gefragt, diese neue Technologie durch eine beschleunigte Validierung und Akzeptanz umzusetzen. Sie erhalten die einzigartige Chance, ihre Prozesse und Anlagen wettbewerbsfahig zu halten. Kooperativ betriebenen F&E-Zentren und gemeinsam anerkannten Applikationslaboren kommt dafur eine hohe Bedeutung zu.

Mathematical and statistical tools for online NMR spectroscopy in chemical processes

Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which are calibration intensive. 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 environments for advanced process monitoring and control. Within the European Union’s Research Project CONSENS (Integrated CONtrol and SENsing, www.consens-spire.eu) by development and integration of a smart NMR module for process monitoring was designed and delivers online spectra of various reactions. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. For reaction monitoring and process control using NMR instruments after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods. When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. Additionally, the multiplet structure becomes more dominant because of the comparably low-field strengths which results in overlapping of multiple signals. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models. We present a range of approaches for the automated spectra analysis moving from 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.

Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures

Due to its direct correlation to the number of spins within a sample quantitative NMR spectroscopy (qNMR) is a promising method with absolute comparison abilities in complex systems in technical, as well as metrological applications. Most of the samples studied with qNMR are in liquid state in diluted solutions, while gas-phase applications represent a rarely applied case. Commercially available NMR equipment was used for purity assessment of liquid and liquefied hydrocarbons serving as raw materials for production of primary reference gas standards. Additionally, gas-phase studies were performed within an online NMR flow probe, as well as in a high-pressure NMR setup to check feasibility as verification method for the composition of gas mixtures.