Analytische Chemie
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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 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. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.
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. 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).
Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu).
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.
Improvement in deep process understanding is a mandatory prerequisite for the application of modern concepts like Industrial Internet of Things (IIoT) or “Industrie 4.0”. This is particularly relevant in new process concepts such as intensified production in modularized plants. The direct hyphenation with online methods of process analytical technology (PAT) allows profound insights into the actual reactions within chemical and pharmaceutical production steps and provides necessary information for associated advanced control strategies.
While the industrial application of online Raman spectroscopy has already been successfully demonstrated, low-field NMR spectroscopy is not yet adequately developed as an online method for use in process industry. The high Information content combined with the low calibration effort makes NMR spectroscopy a highly promising method for modern process automation with a high flexibility due to short set-up times and novel calibration concepts. This is a Major advantage especially within multi-purpose production plants, as well as for processes suffering from fluctuating quality of raw materials.
The concept was evaluated on several example processes of pharmaceutical and chemical industry. The one presented here represents a stage of the synthesis of the industrially important solvent tetrahydrofuran consisting of the catalytic hydrogenation of 2-butine-1,4-diol was monitored. This reaction is proceeding via an intermediate product and suffers from competitive reaction paths. In this application, different spectroscopic methods were combined with the data obtained from classical process sensors, e.g., pressure, temperature, and flow transducers for the development of innovative control concepts.
Such an analyzer for direct implementation in an industrial process environment based on a commercially available laboratory benchtop NMR instrument was recently developed within the EU project CONSENS (www.consens-spire.eu), challenging hyphenation to the production plant as well as compliance to all requirements of chemical industry such as explosion safety regulations (ATEX), robust automation, and modern, as well as classical communication interfaces such as OPC-UA or 4–20 mA communication.
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.