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The future competitiveness of the process industry and their providers depends on its ability to deliver high quality and high value products at competitive prices in a sustainable fashion, and to adapt quickly to changing customer needs. The transition of process industry due to the mounting digitalization of technical devices and their provided data used in chemical plants proceeds. Though, the detailed characteristics and consequences for the whole chemical and pharmaceutical industry are still unforeseeable, new potentials arise as well as questions regarding the implementation. As the digitalization gains pace fundamental subjects like the standardization of device interfaces or organization of automation systems must be answered. Still, process industry lack of sufficient system and development concepts with commercial advantage from this trend.
Intensified continuous processes are in focus of current research. Compared to traditional batch processes, intensified continuous production allows new and difficult to produce compounds with better product uniformity and reduced consumption of raw materials and energy. Flexible (modular) chemical plants can produce various products using the same equipment with short down-times between campaigns, and quick introduction of new products to the market.
Full automation is a prerequisite to realize such benefits of intensified continuous plants. In continuous flow processes, continuous, automated measurements and closed-loop control of the product quality are required. Consequently, the demand for smart sensors, which can monitor key variables like component concentrations in real-time, is increasing. Low-Field NMR spectroscopy presents itself as such an upcoming smart sensor (as addressed, e.g., in the CONSENS project – http://www.consens-spire.eu/).
Systems utilizing such an online NMR analyzer benefits through short development and set-up times when applied to modular production plants starting from a desired chemical reaction. As an example for such a modular process unit, we present the design and validation of an integrated NMR micro mixer based on computational modelling suited for a desired chemical reaction. This method includes a proper design of a continuous reactor, which is optimized through computational fluid dynamics (CFD) for the demands of the NMR sensor as well as for the given reaction conditions. The system was validated with a chemical reaction process.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. An increasing number of applications are reported. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. Tis paves the way for industrial automation in real process environments.
Automated data preparation and analysis are cornerstones for a breakthrough of NMR techniques for process control. Particularly, robust chemometrics as well as automated signal processing methods have to be (further) developed especially for NMR spectroscopy in process control. This becomes even more important for so called “smart sensors” providing the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality.
Monitoring chemical reactions is the key to 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 cutting the calibration and validation needs to an minimum and thus exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control.
Intensified continuous processes are in focus of current research. Flexible (modular) chemical plants can produce different products using the same equipment with short down-times between campaigns and quick introduction of new products to the market. In continuous flow processes online sensor data and tight closed-loop control of the product quality are mandatory. Data analysis techniques are available but currently mostly used for off-line data analysis to detect the causes of variations in the product quality.
This is addressed within the EU’s Research Project CONSENS by the development and integration of a smart NMR module for process monitoring. The presented NMR module is provided in a mobile explosion proof housing and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. Such “smart sensors” provide the basis for the future project “Industrie 4.0”, and Industrial Internet of Things (IIoT), along with current requirements to process control, model based control, or soft sensing. The module transforms the acquired online spectra of various technically relevant reactions to either conventional 4‒20 mA signals as well as WiFi based OPC-UA communication protocols, which enables NMR-based advanced process control and funny discussions with plant managers along with automation and safety engineers.
Assessment and validation of various flow cell designs for quantitative online NMR spectroscopy
(2017)
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction and process control. Robust field integration of NMR systems have to face explosion protection or integration into process control systems with short set-up times. This paves the way for industrial automation in real process environments.
The design of failsafe, temperature and pressure resistant flow through cells along with their NMR-specific requirements is an essential cornerstone to enter industrial production plants and fulfill explosion safety requirements. NMR-specific requirements aim at full quantitative pre-magnetization and acquisition with maximum sensitivity while reducing sample transfer times and dwell-times. All parameters are individually dependent on the applied NMR instrument. Luckily, an increasing number of applications are reported together with an increasing variety of commercial equipment. However, these contributions have to be reviewed thoroughly.
The performance of sample flow cells commonly used in online analytics and especially for low-field NMR spectroscopy was experimentally and theoretically investigated by 1H-NMR experiments and numerical simulations. Here, we demonstrate and discuss an automated test method to determine the critical parameters of flow through cells for quantitative online NMR spectroscopy. The setup is based on randomized setpoints of flow rates in order to reduce temperature related effects. Five flow cells and tubings were assessed and compared for high-field as well as low-field NMR spectrometers.
Currently, research in chemical manufacturing moves towards flexible plug-and-play approaches focusing on modular plants, capable of producing small scales on-demand with short down-times between individual campaigns. This approach allows for efficient use of hardware, a faster optimization of the process conditions, and thus, an accelerated introduction of new products to the market. Driven mostly by the search for chemical syntheses under biocompatible conditions, so-called “click” chemistry rapidly became a growing field of research. The resulting simple one-pot reactions are so far only scarcely accompanied by an adequate optimization via comparably straightforward and robust analysis techniques.
Here we report on a fast and reliable calibration-free online high field NMR monitoring approach for technical mixtures. It combines a versatile fluidic system, continuous-flow measurement with a time interval of 20 s per spectrum, and a robust, automated algorithm to interpret the obtained data. All spectra were acquired using a 500 MHz NMR spectrometer (Varian) with a dual band flow probe having a 1/16-inch polymer tubing working as a flow cell. Single scan 1H NMR spectra were recorded with an acquisition time of 5 s, relaxation delay of 15 s. As a proof-of-concept, the thiol-ene coupling between N-boc cysteine methyl ester and allyl alcohol was conducted in non-deuterated solvents while its time-resolved behaviour was characterised with step tracer experiments.
Through the application of spectral modeling the signal area for each reactant can be deconvoluted in the online spectra and thus converted to the respective concentrations or molar ratios. The signals which were suitable for direct integration were used herein for comparison purposes of both methods.
Hydroformylation represents an important homogeneous catalyzed process, which is widely used within chemical industry. Usually applied with simple alkenes like Propene and Butene aldehydes obtained from alkenes >C6 are relevant intermediates in production of plasticizers, surfactants and polymers. Today the active catalyst species is often based on valuable Rhodium complexes in aqueous solution. This implies the problem of limited water solubility of the reactands, which is acceptable for short chain lengths, but states a problem in case of higher alkenes. Along with that efficient separation and recycling of the catalyst becomes more complicated. There are different approaches tackling this problem, e.g., by using of salt formation in the BASF process or downstream distillation within the Shell process
The Collaborative Research Center InPROMPT aims to establish a novel process concept for the hydroformylation of long-chained olefins, using a rhodium complex as catalyst in the presence of syngas. Recently, the hydroformylation in micro-emulsions, which allows for the efficient recycling of the expensive rhodium catalyst, was found to be feasible. However, the temperature and concentration sensitive multi-phase system demands a continuous observation of the reaction to achieve an operational and economically feasible plant operation. For that purpose, we tested the potential of both NMR and Raman spectroscopy for process control assistance. The lab-scale experiments were supported by sampling for off-line GC-analysis as reference analytics. The results of the NMR experiments will be part of another contribution.
Flexible, modulare Produktionsanlagen auf der Basis von verfahrenstechnischen Teilmodulen stellen einen vielversprechenden Ansatz für die kontinuierliche Produktion von Fein- und Spezialchemikalien dar. Der Schwerpunkt des Horizont-2020-Projekts der Europäischen Kommission CONSENS (Integrated Control and Sensing) liegt in der Implementierung von innovativen Sensorkonzepten zur Prozessüberwachung und -regelung innerhalb von containerbasierten modularen Produktionsan lagen. In diesem Artikel wird die Feldintegration eines Online-NMR-Sensors als smartes Modul für die Prozesskontrolle beschrieben. Dieses Modul basiert auf einem kommerziell erhältlichen Niederfeld-NMRSpektrometer, das zurzeit für die Anwendung im Laborbereich erhältlich ist. Für die Feldintegration wurde ein ATEX-zertifiziertes, explosionsgeschütztes Gehäuse entwickelt sowie Automationsschemen für den unbeaufsichtigten Betrieb und für die spektrale Datenauswertung erstellt. Nachdem die Machbarkeit und Leistungsfähigkeit des Sensorkonzeptes in Laborexperimente an einer aromatischen Substitutionsreaktion bereits erfolgreich demonstriert wurde, ist die Inbetriebnahme des NMR-Sensormoduls in
industrieller Umgebung für 2017 geplant.
The project InPROMPT aims to establish a robust hydroformylation reaction process of the alkene n-dodecene to the aldehyde n-tridecanal using a rhodium complex as catalyst in the presence of syngas. This industrial relevant production process demands further research for optimization and expansion. For that purpose, the fiber optic coupled probe of a process Raman spectrometer is directly introduced in the product stream, which enables the recording of spectra within short control intervals.
Medium resolution nuclear magnetic resonance spectroscopy (MR-NMR) currently develops to an important analytical tool for both quality control and process monitoring. 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 were treated by an automated baseline and phase correction using the minimum entropy method. The evaluation strategies comprised direct integration, automated line fitting, indirect hard modeling, and partial least squares regression.