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The design of sample flow cells, commonly used in online analytics and especially for medium resolution NMR spectroscopy (MR-NMR) in low magnetic fields, was experimentally and theoretically investigated by 1H-NMR and numerical simulations. The flow pattern was characterised to gain information about the residence time distribution and mixing effects. Both 1H-NMR imaging and spectroscopy were used to determine the characteristics of flow cells and their significance for on-line measurements such as reaction monitoring or hyphenated separation spectroscopy. The volume flow rates investigated were in the range from 0.1 to 10 ml/min, typically applied in the above mentioned applications. When compared to those commonly used in high-field NMR, the special characteristics of flow cells for MR-NMR were revealed by various NMR experiments and compared with CFD simulations. The influence of the design of the inlet and outlet on the flow pattern was investigated as well as the effect of the length of the cell. For practical use, a numerical estimation of the inflow length was given. In addition, it was shown how experiments on the polarisation build-up revealed insight into the flow characteristics in MR-NMR.
As presented at the NAMUR general meeting 2015, the technology roadmap "Process Sensors 4.0" identifies the necessary requirements as well as the communication abilities of such process sensors. We report on the progress of discussions in trialogue between users, software and device manufacturers as well as the research.
An important key is the definition of an appropriate and uniform topology for such smart sensors, which will be driven forward in a new NAMUR AK 3.7 "smart sensors" in mutual exchange with device and software manufacturers and research institutions.
Recent technical developments of NMR instruments such as in acquisition electronics and probe design allow detection limits of components in liquid mixtures in the lower ppm range (approx.. 5–10 ppm amount of substance). The major advantage of quantitative NMR spectroscopy (qNMR) is that it is a direct ratio method of analysis without the need of calibration. This means that the signal for a specific NMR-active nucleus (e.g., a proton) in an analyte can be compared and quantified by reference to a different nucleus of a separate compound, comparable to a counting of spins in the active volume of the spectrometer.
Technical mixtures can be investigated online directly next to a process setup by using flow probes. This makes it a promising method for process analytical applications, especially during process development in laboratory and pilot plant scale. With the growing market of Benchtop devices based on permanent magnets nowadays an integration of NMR spectroscopy in an industrial environment becomes reasonable.
A special application of qNMR in technical mixtures is the observation in the gas phase, which is rarely applied compared to liquid and solid NMR studies. Because of the low density it results in a reduced sensitivity, which can be improved by applying pressure. Therefore a high-pressure NMR setup was developed based on a commercially available NMR tube made of zirconia. This is currently tested up to 20 MPa, but can be extended up to 100 MPa with regard to pressure rating of its components. This work shows results of gas-phase application on natural-gas like reference gas mixtures produced at BAM, as well as investigations on liquefied gas mixtures with high accuracy provided in piston cylinders.
Besides that amine gas treatment and hydroformylation in a microemulsion represent two other examples of applications in process analytical technology. These show the potential of combination of online NMR spectroscopy with other spectroscopic methods, especially during model development for data evaluation.
The preservation and the improvement of the fertility of soils by agricultural management measures requires carefully planned decisions which are based on a detailed capture of the soil qualities and a detailed understanding of soil processes. Profit losses can be caused on the one hand by conventional, surface-uniform managements (e.g., fertilization) by too low management intensity on one part of the surface, while other parts of the field receive too high doses and it thereby comes to environmental impacts or to waste of resources.
X-ray fluorescence analysis (XRF) and the Laser-induced Breakdown Spectroscopy (LIBS) are possible technologies which permit online analyses of the chemical composition.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied. NMR spectroscopy has a high potential for direct loop process control. Compact NMR instruments based on permanent magnets are robust and inexpensive analysers, which feature advantages like low maintenance, ease of use, and cryogen-free operation. Instruments for online NMR measurements equipped with a flow-through cell, possessing a good signal-to-noise-ratio, robustness, and meeting the requirements for integration into industrial plants (i.e., explosion safety and fully automated data analysis) are currently not available off the rack.
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. Otherwise there is a huge risk of producing large amounts of out-of-spec (OOS) products. This is addressed in the European Union’s Research Project CONSENS (www.consens-spire.eu) by development and integration of smart sensor modules for process monitoring and control within such modular plant setups.
The presented NMR module is provided in an explosion proof housing with a module size of 57 x 57 x 85 cm and involves a compact 43.5 MHz NMR spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction) and evaluation. Indirect Hard Modeling (IHM) was selected for data analysis of the low-field NMR spectra. A set-up for monitoring continuous reactions in a thermostated 1/8” tubular reactor using automated syringe pumps was used to validate the IHM models by using high-field NMR spectroscopy as analytical reference method.
Within the Collaborative Research Center InPROMPT a novel process concept for the hydroformylation of long-chained olefins is studied in a mini-plant, 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 high sensitivity of this multi-phase system with regard to changes in temperature and composition demands a continuous observation of the reaction to achieve a reliable and economic plant operation. For that purpose, we tested the potential of both online NMR and Raman spectroscopy for process control. The lab-scale experiments were supported by off-line GC-analysis as a reference method.
A fiber optic coupled probe of a process Raman spectrometer was directly integrated into the reactor. 25 mixtures with varying concentrations of olefin (1-dodecene), product (n-tridecanal), water, n-dodecane, and technical surfactant (Marlipal 24/70) were prepared according to a D-optimal design. Online NMR spectroscopy was implemented by using a flow probe equipped with 1/16” PFA tubing serving as a flow cell. This was hyphenated to the reactor within a thermostated bypass to maintain process conditions in the transfer lines.
Partial least squares regression (PLSR) models were established based on the initial spectra after activation of the reaction with syngas for the prediction of unknown concentrations of 1-dodecene and n-tridecanal over the course of the reaction in the lab-scale system. The obtained Raman spectra do not only contain information on the chemical composition but are further affected by the emulsion properties of the mixtures, which depend on the phase state and the type of micelles. Based on the spectral signature of both Raman and NMR spectra, it could be deduced that especially in reaction mixtures with high 1-dodecene content the formation of isomers as a competitive reaction was dominating. Similar trends were also observed during some of the process runs in the mini-plant. The multivariate calibration allowed for the estimation of reactants and products of the hydroformylation reaction in both laboratory setup and mini-plant.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control.
The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs.
The talk also generally covers current aspects of high-field and low-field online NMR spectroscopy for reaction monitoring and process control giving also an overview on direct dissolution studies of API cocrystals.
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.
Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short down-times between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as , e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications.