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Für die Rückführung von aus Rückbauprojekten anfallender künstlicher Mineralwolle in ihren Herstellungsprozess ist es notwendig, Stein- und Glaswolle zu unterscheiden und voneinander getrennt zu halten. Zu diesem Zweck wurde das Potential von NIR-Spektroskopie (NIRS) für einen werks- oder baustellenseitigen Einsatz getestet. NIRS wird aufgrund kurzer Messzeiten, minimaler Probenvorbereitung und hoher Robustheit der Spektrometer häufig in der Prozessanalytik eingesetzt. Untersucht wurden 70 verschiedene Mineralwollen, wobei sich der Probenumfang sowohl aus werksneuen Proben mit Herstellerangaben als auch unbekannten Proben ohne Spezifikation zusammensetzen, die auf verschiedenen Baustellen in den Jahren 2016–2017 entnommen oder von Deponien zur Verfügung gestellt worden waren. Als Referenzmethode wurde die Röntgenfluoreszenzanalyse verwendet, um den Mineralwolle-Typ über den Elementgehalt nach VDI 3492 zu identifizieren. Mit Hilfe eines multivariaten Datenanalyseverfahrens konnte schließlich eine Methode etabliert werden, die eine zuverlässige Identifikation von unbekannten Mineralwollen anhand deren NIR-Spektren als Stein- bzw. Glaswolle ermöglicht.
Hydroformylation of short-chained olefins has been established as a standard industrial process for the production of C2 to C6 aldehydes. Using aqueous solutions of transition metal complexes these processes are carried out homogeneously catalyzed. A biphasic approach allows for highly efficient catalyst recovery. Regarding renewable feedstocks, the hydroformylation of long-chained alkenes (> C10) in a biphasic system, using highly selective rhodium catalysts has yet not been shown. Therefore, the Collaborative Research Center SFB/TR 63 InPROMPT develops new process concepts, involving innovative tuneable solvent systems to enable rather difficult or so far nonviable synthesis paths. One possible concept is the hydroformylation of long-chained alkenes in microemulsions. For this, a modular mixer-settler concept was proposed, combining high reaction rates and efficient catalyst recycling via the application of technical grade surfactants. The feasibility of such a concept is evaluated in a fully automated, modular mini-plant system within which the characteristics of such a multiphase system pose several obstacles for the operation. Maintaining a stable phase separation for efficient product separation and catalyst recycling is complicated by small and highly dynamic operation windows as well as poor measurability of component concentrations in the liquid phases. In this contribution, a model-based strategy is presented to enable concentration tracking and phase state control within dynamic mini-plant experiments. Raman spectroscopy is used as an advanced process analytical tool, which allows for online in-situ tracking of concentrations. Combined with optical and conductivity analysis optimal plant trajectories can be calculated via the solution of dynamic optimization problem under uncertainty. Applying these, a stable reaction yield of 40 % was achieved, combined with an oil phase purity of 99,8 % (total amount of oily components in the oil phase) and catalyst leaching below 0.1 ppm.
Physical adsorption at cryogenic temperature (cryoadsorption) is a reversible mechanism that can reduce the pressure of conventional compressed gas storage systems. Metal–organic framework (MOF) materials are remarkable candidates due to the combination of high specific surface area and density which, in some cases, provide a high volumetric storage capacity. However, such extensive use of MOFs for this application requires the selection of affordable structures, easy to produce and made from feasible metallic and organic components. Herein, we introduce a MOF database detailing the crystallographic and porous properties of 3600 existing MOFs made from industrially relevant metals and their organic composition. The comparison of the available minimum costs of linkers allowed the creation of a database to select affordable structures with high potential for volumetric hydrogen storage by cryoadsorption, considering their composition based on individual or mixed building blocks. A user interface, available online, facilitates the selection of MOFs based on the properties or names of structures and linkers.
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).
Zur Onlineüberwachung von Fermentationsprozessen werden zunehmend schwingungsspektroskopische (Raman-, Mittel- und Nahinfrarotspektroskopie (NIRS) und UV-/VIS- Methoden(Absorptions- und Fluoreszenzspektroskopie) in Kombination mit multivariater Auswertung eingesetzt. Anliegen dieser Arbeit war es, zu testen, welche Verfahren für die spektroskopische On- und Offlineüberwachung des Fermentationsprozesses zur biotechnologischen Herstellung einer Malariavaccine grundlegend geeignet sind und welche Messbereiche und Genauigkeiten der Vorhersage im Idealfall bei der Abwesenheit von Hefezellen erzielt werden können.
Die chemische Industrie steht derzeit, wie viele andere Industriebereiche, vor den Herausforderungen einer Digitalisierung der Produktion. Sie ist der Schlüssel für die Flexibilisierung von Prozessen und Anlagen, für die Verkürzung von Produkteinführungszeiten sowie für den Zuschnitt der Produktion auf wechselnde Nachfrage und kürzere Produktlebenszyklen. Die Messtechnik und Sensorik spielt neben der intelligenten Datenverarbeitung eine Schlüsselrolle für die Digitalisierung. Flexiblere Anlagen benötigen Sensorik zur Überwachung des Anlagenzustandes, zur Früherkennung nicht bestimmungsgemäßer Betriebszustände sowie für eine bedarfsgerechte Wartung. Da die Entwicklung neuer und verbesserter Messtechnik und Sensorik grundlegend aus verschiedenen Richtungen gedacht werden muss, haben sich Akteure aus verschiedenen Branchen zusammengetan und dieses Positionspapier erstellt. Es basiert auf einer grundlegenden Analyse des Ist-Stands sowie des Bedarfs der Industrie, die unter anderem auf einem eigens dafür durchgeführten Workshop mit Sensorentwicklern, Anlagenherstellern sowie Anlagenbetreibern am 18. Juni 2019 bei der DECHEMA in Frankfurt a. M. diskutiert wurden. Diese Aktivitäten wurden maßgeblich von der Initiative Wanted Technologies der ProcessNet sowie dem AMA Verband für Sensorik und Messtechnik e.V. initiiert.
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.
Recently, AI procedures have also been successfully used for NMR data evaluation. In order to overcome the typical limitation of too small data sets from process developments, a new method was tested, which allows a physically motivated multiplication of the available reference data together with context information in order to obtain a sufficiently large data set for the training of machine learning algorithms.
In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
New developments in spectroscopic techniques for process control are, in general, driven by shortcomings of existing technology, for example, when sensitivity, selectivity, robustness, and so forth do not meet the demands. The perfect process analytical method would be based on a robust and easy to handle customized technique operating in real time, come without any need for calibration, that is, be an absolute method, have a professional support, and be compliant to increasing regulatory requirements. However, there are at least trends toward such an all-in-one device suitable for every purpose.
Small, low-field NMR systems equipped with permanent magnet technology have been developed and allow for quantitative analysis as on-line instruments in a production environment. Quantitative high-resolution on-line NMR spectroscopy contributes to process understanding in pilot plant and research environments.
Laser spectroscopy is a promising field in process analysis owing to its sensitivity and selectivity. Laser-induced breakdown spectroscopy LIBS is a promising field for direct in situ analysis and remote sensing. Applications of quantum-cascade lasers for process analytical applications are a promising technique. Techniques such as cavity ring-down spectroscopy (CRDS), tunable diode laser absorption spectroscopy (TDLAS), and photothermal techniques are briefly introduced.
Recent developments of new detectors have improved X-ray fluorescence analysis (XRF) for qualitative and quantitative on-line evaluation of the elementary composition of liquid or solid samples, regardless of whether compact or bulk material.
The chapter also introduces miscellaneous techniques such as ion mobility spectroscopy (IMS), microwave and dielectric spectroscopy, terahertz spectroscopy, ultrasonic acoustic spectroscopy, and other methods.
Ohne die vielfältigen Messmethoden der Prozessanalysentechnik (PAT) sind viele moderne Anlagen der verfahrenstechnischen Industrie heute nicht mehr wirtschaftlich oder sicher zu betreiben. Dementsprechend erfährt die sich mittlerweile immer mehr als selbstständig etablierende Branche Prozessanalysentechnik einen großen Zuwachs und eine spannende Dynamik. Sie ermöglicht eine Produktion in der geforderten Produktqualität unter optimaler Ausnutzung von Rohstoffen, Anlagen und Energie.
Mit den Technologie-Roadmaps „Prozesssensoren 2005–2015“ [1] (2006) und „Prozesssensoren 2015+“ [2] und [3] (2009) wurden Grundlagen für alle Unternehmen der Prozessindustrie geschaffen, um zielgerichtet auf Kundenbedürfnisse der Prozessindustrie zugeschnittene Produktentwicklungen, technologische Weiterentwicklungen und Forschungsprojekte zum Erfolg zu bringen. Die Roadmap „Prozesssensoren 2015+“ fand große Akzeptanz aufgrund der soliden Betrachtung der Prozesse und der daraus abgeleiteten Thesen. Diese Aussagen haben in vollem Umfang weiterhin Gültigkeit. Im Rückblick auf die damals formulierten Entwicklungsziele wurden viele dieser Ziele im prognostizierten Zeithorizont auf den Weg gebracht und teilweise bereits umgesetzt. In dieser Technologie-Roadmap werden einige Beispiele dazu aufgezeigt.
Due to recent advances in technical developments of NMR instruments such as acquisition electronics and probe design, detection limits of components in liquid mixtures were improved into the lower ppm range (approx. 5–10 ppm amount of substance). This showed that modern NMR equipment is also suitable for the observation of hydrocarbon samples in the expanded fluid phase or gas phase. Since Quantitative NMR spectroscopy (qNMR) is a direct ratio method of analysis without the need of calibration it was used to determine impurities in appropriate liquid and liquefied hydrocarbon isomers up to C6, which are used for preparation of primary gas standards, e.g., natural gas or exhaust gas standards. At the same time it is possible to yield structural information with a minimum of sample preparation. Thus, cross contaminations between different isomers of the observed hydrocarbons and their (NMR-active) impurities can be identified and quantified.
In general, most quantitative organic chemical measurements rely on the availability of highly purified compounds to act as calibration standards. The traceability and providence of these standards is an essential component of any measurement uncertainty budget and provides the final link of the result to the units of measurement, ideally the SI. The more recent increase in the use of qNMR for the direct assessment of chemical purity however can potentially improve the traceability and reduce the uncertainty of the measured chemical purity at a reduced cost and with less material. For example the method has beneficially been used by National Measurement institutes for recent CCQM comparisons including the CCQM–K55 series of purity studies.
Traditional ‘indirect’ methods of purity analysis require that all impurities are identified and quantified, leading to a minimum of 4 individual analytical methods (organic impurities, water, solvents, inorganic residue). These multiple technique approaches measure an array of different chemical impurities normally present in purified organic chemical compounds. As many analytical methodologies have compound-specific response factors, the accuracy and traceability of the purity assessment is dependent on the availability of reference materials of the impurities being available.
qNMR provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The development of CRMs addressing qNMR specific measurement issues will give analysts compounds ideally suited for the analytical method and also provide full characterisation of qNMR related parameters to enable more realistic uncertainty budgets. These materials will give users the tools to exploit qNMR more easily and enable them to speed up analytical method development and reduce the time and financial burden of multiple analytical testing.
Der Vortrag stellt die aktuellen Forschungsschwerpunkte zum Thema Prozessanalytik an der Bundesanstalt für Materialforschung und -prüfung (BAM) vor und nennt aktuelle Entwicklungsfelder mit dem Ziel gemeinsamer F&E-Projekte. Zunächst wird die Prozessindustrie und ihre Wertschöpfungskette vorgestellt. Daraus ergibt sich eine Motivation für Prozessanalytik. Zwischen der Prozessanalytik in der Pharmazeutische Industrie und der Chemischen Industrie bzw. Verfahrenstechnik gibt es Unterschiede, die herausgearbeitet werden. Der Vortrag schließt mit Technologiewünschen und Technologievisionen und nennt Konkrete Beispiele für Visionen für PAT, insbesondere im Kontext des Zukunftsprojekts „Industrie 4.0“
Quantitative NMR Spectroscopy (qNMR) provides the most universally applicable form of direct purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. Broadly accepted validation methods of qNMR spectroscopy will give users the tools to exploit qNMR more easily and enable them to speed up analytical method development and reduce the time and financial burden.
The first initiative towards a worldwide agreement goes back to a panel discussion at PANIC 2014 (Practical Applications of NMR in Industry Conference) in Chicago. Since that, the Validation Workshop takes place following the PANIC Conference each year, last in 2017 with a turnout of over 50 people. The group aims at identifying a network of NMR people concerned with validation that can ultimately assist each other through the validation process, harmonize the terminology and a standard approach for NMR validations and position the guidelines produced by consensus of the NMR community so that accreditation agencies can use this process.
Prozess-Sensoren 4.0 vereinfachen ihre Einbindung über Plug and Play, obwohl sie komplexer werden. Sie bieten Selbstdiagnose, Selbstkalibrierung und erleichterte Parametrierung. Über die Konnektivität ermöglichen die Prozess-Sensoren den Austausch ihrer Informationen als Cyber-physische Systeme mit anderen Prozess-Sensoren und im Netzwerk. Der Aufbruch von der aktuellen Automation zum smarten Sensor hat bereits begonnen. Automatisierungstechnik und Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. Wenn die Prozessindustrie dieses nicht definiert, tun es andere.
Für 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 über zusätzliche Kommunikationskanäle zwischen Sensor und mobilen Endgeräten über vollständig bidirektionale Kommunikation bis hin zur Einbindung der Cloud und des Internets in virtualisierte Umgebungen.
Um zu einer störungsfreien Kommunikation aller Sensoren untereinander zu kommen, muss mindestens ein einheitliches Protokoll her, das alle Sensoren sprechen und verstehen. Der derzeit greifbarste offengelegte Standard, der moderne Kommunikationsanforderungen erfüllt, ist OPC Unified Architecture (OPC-UA). Viele halten das Sortieren der Kommunikationsstandards für eines der wesentlichen Errungenschaften von Industrie 4.0.
Eine Topologie für smarte Sensoren, das Zusammenwirken mit daten- und modellbasierte Steuerungen bis hin zur Softsensorik sowie weitere Anforderungen an Sensoren sind jedoch heute noch nicht angemessen beschrieben. Wir müssen jetzt schnell die Weichen für eine smarte und sichere Kommunikationsarchitektur stellen, um zu einer störungsfreien Kommunikation aller Sensoren auf Basis eines einheitlichen Protokolls zu kommen, welches alle Sensoren ausgeben und verstehen.
Aktuelle und zukünftige öffentliche Förderung von Industrie 4.0-Projekten sind eine gute Investition. Wegen der hohen Komplexität und Interdisziplinarität gelingt die Umsetzung nur gemeinsam zwischen Anwendern aus der Prozessindustrie, Software- und Geräteherstellern und Forschungsgruppen. Anwender sind gefragt, diese neue Technologie durch eine beschleunigte Validierung und Akzeptanz umzusetzen. Sie erhalten die einzigartige Chance, ihre Prozesse und Anlagen wettbewerbsfähig zu halten. Kooperativ betriebenen F&E-Zentren und gemeinsam anerkannten Applikationslaboren kommt dafür eine hohe Bedeutung zu.
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.