Filtern
Dokumenttyp
- Vortrag (11)
- Beitrag zu einem Tagungsband (4)
- Zeitschriftenartikel (2)
Schlagworte
- Reaction Monitoring (17) (entfernen)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (11)
Accelerating chemical process development and manufacturing along with quick adaption to changing customer needs means consequent transformation of former batch to continuous (modular) manufacturing processes. These are justified by an improved process control through smaller volumes, better heat transfer, and faster dynamics of the examined reaction systems.
As an example, for such modular process units we present the design and validation of an integrated nuclear magnetic resonance (NMR) micro mixer tailor‐made for a desired chemical reaction based on computational modelling. The micro mixer represents an integrated modular production unit as an example for the most important class of continuous reactors. The quantitative online NMR sensor represents a smart process analytical field device providing rapid and non‐invasive chemical composition information without need for calibration. We describe the custom design 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 an esterification reaction as an example for a chemical reaction process.
Systems utilizing such an online NMR analyser benefits through short development and set‐up times based on “modular” spectral models. Such models can simply be built upon pure component NMR spectra within minutes to a few hours (i.e., assignment of the NMR signals to the components) instead of tedious DoE 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). The approach was validated for typical industrial reactions, such as hydrogenations or lithiations.
Der Vortrag stellt einige aktuelle Herausforderungen für die Prozessanalytik und mögliche Antworten vor.
Gepulste Raman-Spektrometer akkumulieren das Raman-Signal mit Hilfe schneller optischer Schalter im Picosekunden-Bereich, bevor langlebigere Fluoreszenzanregung entsteht. Damit lassen sich stark fluoreszierende Materialien untersuchen, die bislang nicht zugänglich sind. Eine weitere interessante Entwicklung ist etwa die Shifted excitation Raman difference spectroscopy (SERDS) die besonders für biologische Anwendungen interessant ist.
Flexible, modulare Produktionsanlagen stellen einen vielversprechenden Ansatz für die kontinuierliche Produktion von Fein- und Spezialchemikalien dar. In einem EU-Projekt wird derzeit die Feldintegration eines Online-NMR-Sensormoduls als smartes Modul für die Prozesskontrolle vorangebracht. Dieses Modul basiert auf einem kommerziell erhältlichen Niederfeld-NMR-Spektrometer, welche 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.
Eine sehr gut anwendbare analytische Messtechnik zur Kontrolle der elementaren Zusammensetzung von verschiedensten Materialien ist die laserinduzierte Plasmaspektroskopie (LIPS, engl. LIBS - Laser-induced Breakdown Spectroscopy). Bei der LIBS wird ein kurz gepulster Laser auf eine Probe fokussiert, um ein Leuchtplasma zu erzeugen. Das dabei erzeugte Atomemissionsspektrum ermöglicht eine qualitative und quantitative Analyse der Zusammensetzung der Probe bezüglich praktisch aller Elemente des Periodensystems. In einem aktuellen Projekt wird diese Methode neben anderen zur Online-Analyse von Ackerböden für die ortsspezifischer Bewirtschaftung (Precision Agriculture) weiterentwickelt und bewertet.
Modular chemical production is a tangible implementation of the digital transformation of the specialty chemicals process industry. In particular, it enables acceleration of process development and thus faster time to market by flexibly interconnecting and orchestrating standardized physical modules and bringing them to life. For this purpose, specific (chemical) sensors of process analytics are needed, preferably without lengthy calibration or spectroscopic model development.
An excellent example of a "direct" analytical method is online nuclear magnetic resonance (NMR) spectroscopy. NMR spectroscopy meets the requirements of a direct analytical method because of the direct correlation between the signal area in the spectrum ("counting" the nuclear spins) and the analyte amount of substance concentrations. It is also extremely linear over the concentration range.
With the availability of compact benchtop NMR instruments, it is now possible to bring NMR spectroscopy directly into the field, in close proximity to specialized laboratory facilities, pilot plants, and even industrial-scale production facilities. The first systems are in TRL 8 (Qualified System with Proof of Functionality in the Field).
The presentation will discuss the many building blocks of online nuclear magnetic resonance spectroscopy, from flow cells to automated data analysis.
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.
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 relatively inexpensive analysers, which feature advantages like low
cost, 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, sufficient 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. If these are not available, there is a huge risk of
producing large amounts of out-of-spec (OOS) products. This is addressed in the
European Unionʼs Research Project CONSENS (Integrated Control and Sensing)
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 of 57 x 57 x
85 cm module size 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.
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.
Accelerating chemical process development and manufacturing along with quick adaption to changing customer needs means consequent transformation of former batch to continuous (modular) manufacturing processes. These are justified by an improved process control through smaller volumes, better heat transfer, and faster dynamics of the examined reaction systems.
As an example, for such modular process units we present the design and validation of an integrated nuclear magnetic resonance (NMR) micro mixer tailor‐made for a desired chemical reaction based on computational modelling. The micro mixer represents an integrated modular production unit as an example for the most important class of continuous reactors. The quantitative online NMR sensor represents a smart process analytical field device providing rapid and non‐invasive chemical composition information without need for calibration. We describe the custom design 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 an esterification reaction as an example for a chemical reaction process.
Systems utilizing such an online NMR analyser benefits through short development and set‐up times based on “modular” spectral models. Such models can simply be built upon pure component NMR spectra within minutes to a few hours (i.e., assignment of the NMR signals to the components) instead of tedious DoE 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). The approach was validated for typical industrial reactions, such as hydrogenations or lithiations.
This work wants to show the benefit of NMR spectroscopy as online analytical technique in industrial applications for improving process understanding and efficiency. Especially development and set‐up times based on “modular” data analysis models will enable new production concepts, which are currently discussed with respect to digitization of process industry.
PANIC is the ideal forum for such discussions in the application of NMR spectroscopy and its data analysis to the everyday problems in process industry.
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. 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.
In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. 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.
In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
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 possessing short set-up times. Here, we report on a fast and reliable calibration-free online NMR monitoring approach for technical mixtures. It combines a versatile fluidic system, continuous-flow measurement of 1H spectra with a time interval of 20 s per spectrum, and a robust, fully automated algorithm to interpret the obtained data. As a proof-of-concept, the thiol-ene coupling between N-boc cysteine methyl ester and allyl alcohol was conducted in a variety of non-deuterated solvents while its time-resolved behaviour was characterized with step tracer experiments. Overlapping signals in online spectra during thiol-ene coupling could be deconvoluted with a spectral model using indirect hard modeling and were subsequently converted to either molar ratios (using a calibrationfree approach) or absolute concentrations (using 1-point calibration). For various solvents the kinetic constant k for pseudo-first order reaction was estimated to be 3.9 h-1 at 25 °C. The obtained results were compared with direct integration of non-overlapping signals and showed good agreement with the implemented mass balance.