Analytische Chemie
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- 1.4 Prozessanalytik (59) (entfernen)
Eingeladener Vortrag
- nein (38)
The mechanism of action of zirconium permanent modifiers on graphite surfaces was investigated in order to understand its influence on the analytical signal in atomic and molecular absorption spectrometry (AAS/MAS). For this, the molecule formation of CaF was studied, which is used for the indirect analytical determination of fluorine in high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). The kinetics of this reaction was established by monitoring its molecular spectrum at different atomisation temperatures. An Arrhenius plot showed a pseudo-first order reaction with respect to fluorine (n = 1). An intermediate state was isolated, and its structure was elucidated by spectroscopic methods: scanning electron microscopy with energy dispersive X-ray spectroscopy (SEMEDX), X-ray photoelectron spectroscopy (XPS), X-ray absorption spectroscopy (XANES and EXAFS), and Raman microspectroscopy. We propose here a mechanism, where ZrO2 acts as a heterogeneous catalyst: after a pyrolytic step, an intermediate state of ZrO(OCaF) is activated, and at higher temperatures, CaF(g) is released from the zirconium-coated graphite surface. No evidence of the formation of zirconium carbide was found. Consequently, as the CaF formation is catalysed by a heterogeneous catalyst, surface modifications with ZrO2 nanoparticles and ZrO xerogels were investigated in order to increase the surface area. Their influence was evaluated in the molecule formation of CaF, CaCl, CaBr, and CaI. Graphite furnace modification with zirconium oxide nanoparticles proves to be the best choice for fluorine analysis with a signal enhancement of more than eleven times with respect a non-coated graphite furnace. However, the influence of zirconium modifications in the analytical signals of Cl, and I is lower than the F signals or even negative in case of the Br. Understanding zirconium modifiers as heterogeneous catalysts offers a new perspective to AAS and MAS, and reveals the potential of surface analytical methods for development of improved permanent modifiers and graphite furnace coatings.
qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties. The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy.
Die ehemals wegen komplexer Technik und vergleichsweise hohen Wartungskosten beim Anwender ungeliebte Prozessanalysentechnik (PAT) erfährt sich mittlerweile immer mehr als etablierender Bereich mit einem großen Zuwachs und Dynamik. Die Prozesskontrolle und -steuerung über physikalische Kenngrößen wie Druck und Temperatur lässt eine weitere Optimierung der Anlagen kaum mehr zu. Nur mittels stoffspezifischer Analysen lassen sich Rohstoffschwankungen, Ausbeuten und Energieeinsatz konsequent optimieren.
Der systematische Einsatz der Prozessanalysentechnik verändert Prozesse und Produktionsumgebungen und hat damit die Chance, Kernstück dezentral automatisierter Produktionseinheiten zu werden. Ein neuer Arbeitskreis der NAMUR AK 3.7 „Smarte Sensorik, Aktorik und Kommunikation“ wird diesem verstärkt Rechnung tragen. Es werden reale Anwendungsbeispiele aufgezeigt, die eine schnelle Amortisation von PAT im Prozess untermauern.
Unternehmen der chemischen Industrie müssen neuen Pfade beschreiten, um in einem veränderten Umfeld erfolgreich bestehen zu können. Dazu gehört insbesondere, das Potenzial digitaler Technologien zu nutzen. Die volle Integration und intelligente Vernetzung von Systemen und Prozessen kommt allerdings nur zögerlich voran. Dieser Beitrag ist ein Loblied auf die Feldebene. Er möchte dazu ermutigen, die Digitalisierung der Prozessindustrie auf Basis smarter Sensorik, Aktorik und Kommunikation ganzheitlicher zu denken und informiert über aktuelle technische Perspektiven, wie das Ein-Netzwerk-Paradigma, Ad-hoc-Vernetzungen, Edge-Computing, FPGAs, virtuelle Maschinen oder Blockchain. Diese geben smarter Sensorik, Aktorik und Kommunikation eine völlig neue Perspektive.
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.
What is the future of Analytical Sciences? The talk starts with a definition, comparing the current view with that from 1968. How do wie set trends? How do we get Analytics inside? Some examples of "Big Science" are given and discussed in relation to a definition of AS. How does AS face the current Grand Challenges?
As exaples for something significant, several exaples are presented, such as Climate Change of Hydrogen Storage. Another important trand are eScience and automation concepts for AS, which are highlighted.
But (Analytical) Science has to be politcal in our times to face Fake News and to breake barriers!
Gegenstand des Projekts ist die Prüfung der Umweltbeständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polycarbonat, Polytetrafluorethylen, Polystyrol und Polypropylen zum Einsatz. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden, die es gestatten, Schnellprüfverfahren zu etablieren, die die Simulation der realen Beanspruchungen im Zeitraffermodell anwendbar machen. Somit sollen standardisierbare Schnellbeanspruchungs-verfahren erarbeitet werden, die als Prüfeinrichtungen etabliert werden und von externen Auftraggebern zur Prüfung der Umweltbeständigkeit und -verträglichkeit von neuen Materialien genutzt werden können. Die Umweltwirkungen (chemisch-physikalisch und mikrobiologisch) sollen so definiert eingesetzt werden, dass eine reproduzierbare Prüfung möglich wird. Aus diesen Verfahren und Methoden sollen Normen abgeleitet werden, die eine standardisierte Materialprüfung ermöglichen.
Temperaturindikatoren in mittelalterlichen Hochbrandgipsen: Eine Ramanmikrospektroskopische Studie
(2018)
Infolge der beschränkten Kontrollmöglichkeiten über die in einem Meiler oder Feldofen herrschenden Parameter konstituiert mittelalterliche Hochbrandgipse ein Gemisch aus verschiedenen Anhydritstufen. Basierend auf modernen Versuchsbränden dienen in der gealterten Gipsmatrix nicht oder nur teilweise hydratisiert erhaltene Brenngutkörner üblicherweise anhand der morphologischen Eigenschaften der Anhydritkristalle der groben Einschätzung der zumindest lokal im Ofen bzw. im stückigen Brenngut erreichten Temperaturwerte. Die bildgebende Ramanmikroskopie ermöglicht die kornspezifische Bestimmung der Hitzeeinwirkung über den Grad der sich im Ramanspektrum abbildenden thermischen Beeinträchtigung der Thermoanhydritphasen, als auch deren Unterscheidung von primärem Anhydrit aus der Gipslagerstätte, da diesen eine höhere Kristallinität kennzeichnet. Hier beispielhaft diskutierte Ramananalysen an zwei reliktischen Brenngutkörnern lassen auf Brenntemperaturen von 650°C bzw. 800°C schließen. Pyrometamorphe Phasenneubildungen der natürlichen Verunreinigungen des Rohgipses liefern aufgrund ihres Bildungs- und Stabilitätsbereiches zusätzliche Hinweise. Im Beitrag erörtert werden die an die Dehydratation von magnesiumreichem Chlorit korrelierte Genese von Forsterit sowie die Zersetzung von Dolomit zu Calcit und Periklas, welcher beim Anmachen des Mörtels zu Brucit gelöscht wird und im Laufe der Zeit in der Gipsmatrix zu Magnesit carbonatisiert; beide pyrometamorphen Reaktionen
erfordern Temperaturen von über 800°C.
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 and gives also an overview on direct dissolution studies of API cocrystals.
Um in einem veränderten Umfeld erfolgreich bestehen zu können, müssen Chemieunternehmen neue Pfade beschreiten. Dazu gehört insbesondere das Potential digitaler Technologien. Die volle Integration und intelligente Vernetzung von Systemen und Prozessen kommt zögerlich voran.
Dieser Vortrag ist ein Loblied auf die Feldebene. Er möchte dazu ermutigen, die Digitalisierung der Prozessindustrie auf Basis smarter Sensorik, Aktorik und Kommunikation ganzheitlicher zu denken und informiert über aktuelle technische Perspektiven, wie das „Ein-Netzwerk-Paradigma“, Ad-hoc-Vernetzungen, Edge-Computing, FPGAs, virtuelle Maschinen oder Blockchain. Diese geben smarter Sensorik, Aktorik und Kommunikation eine völlig neue Perspektive.
In case study one of the CONSENS project, two aromatic substances were coupled by a lithiation reaction, which is a prominent example in pharmaceutical industry. The two aromatic reactants (Aniline and o-FNB) were mixed with Lithium-base (LiHMDS) in a continuous modular plant to produce the desired product (Li-NDPA) and a salt (LiF). The salt precipitates which leads to the formation of particles. The feed streams were subject to variation to drive the plant to its optimum.
The uploaded data comprises the results from four days during continuous plant operation time. Each day is denoted from day 1-4 and represents the dates 2017-09-26, 2017-09-28, 2017-10-10, 2017-10-17.
In the following the contents of the files are explained.
qNMR provides the most universally applicable form of direct concentration or purity determination without need for reference materials of impurities or the calculation of response factors but only exhibiting suitable NMR properties.
The workshop presents basic terms of statistics and uncertainty analysis, which are the basis for qNMR spectroscopy and data analysis such as, e.g., standard deviations, linear regression, significance tests, etc. and gives typical examples of applications in qNMR spectroscopy.
The impact of nanoparticles, NPs, at the single cell level has become a major field of toxicological research and different analytical methodologies are being investigated to obtain biological and toxicological information to better understand the mechanisms of cell–NP interactions. Here, inductively coupled plasma mass spectrometry in the single cell measurement mode (SC-ICP-MS) is proposed to study the uptake of silver NPs, AgNPs, with a diameter of 50 nm by human THP-1 monocytes in a proof-ofprinciple experiment. The main operating parameters of SC-ICP-MS have been optimized and applied for subsequent quantitative analysis of AgNPs to determine the number of particles in individual cells using AgNP suspensions for calibration. THP-1 cells were incubated with AgNP suspensions with concentrations of 0.1 and 1 µg/mL for 4 and 24 hours. The results reveal that the AgNP uptake by THP-1 monocytes is minimal at the lower dose of 0.1 µg/mL (roughly 1 AgNP per cell was determined), whereas a large cell-to-cell variance dependent on the exposure time is observed for a 10 times higher concentration (roughly 7 AgNPs per cell). The method was further applied to monitor the AgNP uptake by THP-1 cells differentiated macrophages incubated at the same AgNP concentration levels and exposure times demonstrating a much higher AgNP uptake (roughly from 9 to 45 AgNPs per cell) that was dependent on exposure concentration and remained constant over time. The results have been compared and validated by sample digestion followed by ICP-MS analysis as well as with other alternative promising techniques providing single cell analysis.
Der Vortrag gibt eine Übersicht über aktuelle qNMR-Aktivitäten im Fachbereich 1.4. Dies umfasst beispielsweise die Online-Anwendung zur Prozessüberwachung, aber auch die Reinheitsuntersuchung von Reinstoffkomponenten für die Herstellung von Referenzgasgemischen. Zusätzlich wird ein Ausblick in die aktuelle Strategie hinsichtlich der Rückführung von qNMR-Ergebnissen mittels primärer Referenzmaterialien gegeben.
Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte
(2018)
Der Übergang von der aktuellen Automatisierungslandschaft zur nächsten Generation von Automatisierungskonzepten für die Prozessindustrie hat bereits begonnen. Intelligente Funktionen der Sensoren vereinfachen ihre Anwendung und ermöglichen eine Plug-and-Play-Integration, auch wenn sie auf den ersten Blick komplexer erscheinen mögen. Dies ist die Basis für die Digitalisierung der Prozessindustrie und hilft uns, komplexere Prozesse schneller umzusetzen.
Der Vortrag fasst die derzeit diskutierten allgemeinen Anforderungen an „Smarte Feldgeräte“ zusammen und diskutiert dieses am Beispiel eines smarten Online-NMR-Sensors. NMR-Spektroskopie bietet sich durch den Vorteil der direkten Vergleichsmethode (ohne Kalibrierung) für die Prozess-Steuerung an und verringert somit die Rüstzeiten. Zudem basiert der Sensor auf physikalisch motivierten Modellen (Indirect Hard Modeling, IHM), die sich modular kombinieren lassen. Die Methoden wurden anhand eines vorgegebenen pharmazeutischen Reaktionsschrittes im Rahmen des „Horizon 2020“-Projekts CONSENS der Europäischen Union demonstriert und validiert.
Zuletzt werden Anforderungen an die Weiterentwicklung der Datenauswertemethoden diskutiert, um letztlich die semantische Information aus den Messdaten herauszulesen oder das in der Industrie 4.0 geforderte „durchgehende Engineering“ für die Automatisierungskomponenten zu ermöglichen.
Produzieren Sie schon oder kalibrieren Sie noch? – Online-NMR-Spektrometer als Smarte Feldgeräte
(2018)
Der Vortrag zeigt allgemeine Anforderungen an "smarte Feldgeräte" und deren Entwicklung in den vergangenen Jahren. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, wird die Umsetzung der Anforderung aufgezeigt. Schließlich werden weitere Technologieanforderungen und Lösungsansätze vorgestellt.
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.
Process monitoring with online NMR spectroscopy – An enabler for “Industrie 4.0” in process industry
(2018)
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 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 low requirements regarding validation. This is a major advantage especially within multi-purpose production plants, as well as for processes suffering from fluctuating quality of raw materials. NMR spectroscopy has a high potential for direct quantitative information, while cutting the calibration and validation needs to a minimum and thus exhibiting short set-up times.
Within the EU project CONSENS, an NMR analyzer for direct implementation in an industrial process environment was developed based on a commercially available laboratory instrument. The challenge was not only the hyphenation to the production plant itself, but also to fulfill all requirements of chemical industry, e.g., explosion safety regulations (ATEX), robust automation and modern, as well as classical communication interfaces. The presented NMR module involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation. 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.
The concept was evaluated on two processes of pharmaceutical and chemical industry. As the first example the continuous synthesis of 2-nitrodiphenylamine starting from aniline and o-fluoronitrobenzene, activated by an organometallic lithium reagent, was studied. This application is highly demanding for a reliable automated evaluation of the obtained NMR spectra, which was realized by developing a physically motivated model-based approach.
In the second example, a stage of the synthesis of the industrially important solvent tetrahydrofurane 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.
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.
Generell ist es Ziel der Prozessführung, Reaktions- und Trennprozesse wirtschaftlich optimal zu betreiben. Hierzu werden in großen Anlagen modellbasiere Echtzeitoptimierungsverfahren (Real-time Optimization, RTO) eingesetzt. Die Qualität der Ergebnisse der Optimierung hängt dabei entscheidend von der Güte des verwendeten Modells ab. Die Entwicklung hochgenauer Modelle ist allerdings aufwändig, was für kleine Produktionsvolumina ein wesentliches Hindernis zur Nutzung solcher Methoden darstellt. Mit Hilfe der sogenannten Modifier-Adaptation ist eine iterative Betriebspunktoptimierung auch mit ungenauen Modellen möglich, wenn Messungen der für die Bewertung relevanten Größen (beispielsweise Produktkonzentrationen im Ausgangsstrom) verfügbar sein. Für eine Lithiierungsreaktion in einem bei INVITE kontinuierlich betriebenen Reaktor wurde im Rahmen des EU-Projekts CONSENS eine solche iterative Optimierung auf der Grundlage einer Messung der Zusammensetzung des Ausgangsstroms des Reaktors mit einem Online-NMR-Spektrometer realisiert. Das Spektrometer wurde an den Betrieb in einer explosionsgefährdeten Umgebung angepasst. Es konnte gezeigt werden, dass die Messdaten genau genug sind, um darauf eine Optimierung der Produktausbeute aufzubauen. Die iterative Optimierung führt den Prozess ausgehend vom mit dem Modell berechneten Betriebspunkt schrittweise zum wirtschaftlichen Optimum für die reale Anlage. Dabei reagiert die Optimierung auch auf unbekannte Abweichungen im Prozess (wie die Zusammensetzung des Feeds) und fährt iterativ den jeweils optimalen Betriebspunkt an.
Die Arbeiten wurden im Rahmen des EU-SPIRE-Projekts CONSENS, Förderkennzeichen 636942, durchgeführt.
Im Zuge der Digitalisierung der Prozessindustrie werden zunehmend modellbasiere Echtzeitoptimierungsverfahren eingesetzt, sog. „Advanced Process Control“. Mithilfe der sogenannten Modifier-Adaptation ist eine iterative Betriebspunktoptimierung auch mit ungenauen Modellen möglich, sofern zuverlässige Prozessdaten zur Verfügung stehen. Am Beispiel eines smarten Online-NMR-Sensors, der in einem EU-Projekt von der BAM entwickelt wurde, konnte das Konzept in einer modularen Produktionsanlage zur Herstellung eines pharmazeutischen Wirkstoffs erfolgreich getestet werden.
Spectroscopic methods possess important advantages for the observation of bioprocesses: they are robust, gain many data within a short time scale, and allow for the measurement of multiple relevant information at the same time. Next to Near-infrared spectroscopy, Raman spectroscopy is increasingly applied as a powerful online tool to monitor bioprocesses. However, Raman spectra may be obscured by straylight, cosmic rays and fluorescence. To achieve the best performance, optimal conditions for spectral quality and stability should be pursued. This comprises not only the choice of highly-sensitive equipment, but also the way of implementation into the process. Here we compared the potential of introducing a sterilized fiber optical Raman probe, and a flow-through cell into the bypass of a stirred tank reactor to monitor an autotrophic cultivation of Ralstonia eutropha where gasses are the energy and carbon sources. Raman spectra were continuously recorded over seven days and 22 samples were taken for the reference analytics of biomass, optical density, and protein. In addition, data for of phosphate and ammonium were available. The quantitative Evaluation of Raman spectra by Partial Least Squares Regression (PLSR) yielded comparable results for both approaches, however, there was a general trend of lower prediction errors with the immersion probe.
The better performance of the non-contact optic may be either related to a more representative interaction of the measurement optics with the probe or simply to the absence of probe-fouling, which was observed with the immersion optic in the interstice between window and metal frame.
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.
Compact nuclear magnetic resonance (NMR) instruments make NMR spectroscopy and relaxometry accessible in industrial and harsh environments for reaction characterization 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. Additionally, if fast reactions are monitored, suitable mixing devices need to be placed in close vicinity to the measuring volume to mix the reactants properly.
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. Especially, the applicability of 3D printed zirconium dioxide for innovative flow cell designs was of interest. 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 tubing were assessed and compared for high-field as well as low-field NMR spectrometers.
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). 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.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.
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).
Ziele und Durchführung eines geplanten Ringversuchs zur Untersuchung eines Dreikomponentensystems mittels NIR werden vorgestellt. Der Vortrag enthält einen kurzen Rückblick auf einen 2014 durchgeführten Ringversuch, wobei ein flüssiges Zweikomponentensystem untersucht wurde. Im Anschluss erfolgt die Erläuterung der verwendeten Komponenten, es werden Teilnahmebedingungen und mögliche Zeiträume bekannt gegeben.
Gegenstand der vorzustellenden Arbeiten ist die Prüfung der Umweltbeständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polystyrol (PS) und Polypropylen (PP) zum Einsatz, die jeweils mit polybromierten Flammschutzmitteln (PBFSM) versehen sind. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Auch soll mit Hilfe der RFA und der LA-ICP-MS die Abreicherung der PBFSM in den Modellmaterialien beschrieben werden. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden.
Automatisierungstechnik, sowie die Informations- und Kommunikationstechnik (IKT) verschmelzen zunehmend. In der Prozessindustrie tut man sich aber schwer, die heu-te schon möglichen daten- oder modellbasierten Steuerungen auf Basis smarter Sen-soren und Aktoren einzusetzen oder allein Anforderungen daran vorzugeben. Viele aktuelle Entwicklungen der Zulieferer werden verwehrt und man wartet lieber ab.
Es bilden sich schon jetzt rasant schnell neue digitale Geschäftsmodelle in der Pro-zessindustrie, wie es schon mit der zunehmenden Verbreitung des Internets beobach-tet werden konnte. Wenn die Automatisierer und Anlagenspezialisten jetzt nicht ge-stalten, tun es andere.
Früher war es umgekehrt: Informations- und Kommunikationstechnik für Profis konn-ten sich nur die Großkonzerne leisten. Die Technologie vom Personalcomputer bis zum Smart-Gerät und ihre Peripherie wurden und werden ausschließlich durch den Massenmarkt vorangetrieben. Also müssen wir umdenken und Wege finden, die rasch voranschreitende Informations- und Kommunikationstechnik geschickt für die Digitalisierung umbiegen.
Der Beitrag erörtert aktuelle Diskussionen über netzartige Verbindungen der Feldge-räte (Sensoren und Aktoren) untereinander und zur Cloud sowie über virtuelle Server-verbünde und Applikationen, die auf Cloud-Diensten basieren. Mit einem solchen System ist die Einrichtung beliebiger Dienstleistungen und Funktionen auf der Basis der jeweils gängigen Methoden und Technologie des Internets möglich. Beispiele für Dienstleistungen sind beispielsweise auf prozessanalytische oder Sensordaten auf-bauende Instandhaltungsdienste oder Energiedienste für Anlagen.
For the first time, an international comparison was conducted on the determination of the purity of a high purity element. Participants were free to choose any analytical approach appropriate for their institute’s applications and services. The material tested was a high purity zinc, which had earlier been assessed for homogeneity and previously used in CCQM-K72 for the determination of six defined metallic impurities. Either a direct metal assay of the Zn mass fraction was undertaken by EDTA titrimetry, or an indirect approach was used wherein all impurities, or at least the major ones, were determined and their sum subtracted from ideal purity of 100 %, or 1 kg/kg. Impurity assessment techniques included glow discharge mass spectrometry, inductively coupled plasma mass spectrometry and carrier gas hot extraction/combustion analysis. Up to 91 elemental impurities covering metals, non-metals and semi-metals/metalloids were quantified. Due to the lack of internal experience or experimental capabilities, some participants contracted external laboratories for specific analytical tasks, mainly for the analysis of non-metals. The reported purity, expressed as zinc mass fraction in the high purity zinc material, showed excellent agreement for all participants, with a relative standard deviation of 0.011 %. The calculated reference value, w(Zn) = 0.999 873 kg/kg, was assigned an asymmetric combined uncertainty of + 0.000025 kg/kg and – 0.000028 kg/kg. Comparability amongst participating metrology institutes is thus demonstrated for the purity determination of high purity metals which have no particular difficulties with their decomposition / dissolution process when solution-based analytical methods are used, or which do not have specific difficulties when direct analysis approaches are used. Nevertheless, further development is required in terms of uncertainty assessment, quantification of non-metals and the determination of purity of less pure elements and/or for those elements suffering difficulties with the decomposition process.
Environmental sustainability and –stability of Materials concerning the Migration of pollutants
(2018)
MaUS is an acronym for ”Material und Umweltsimulationen“. Plastics are in the focus of environmental politics due to their long-term behaviour and therefore to their persistence. Not only that they appear as visible contaminants in the sea and on the beach, but their unknown behaviour concerning their additives as well as the related transformation products are anxious. Therefore, we wish to establish a certified reference method to provide a method for testing plastics.
Aim of this project is the development of fast motion standard reference methods for testing plastics regarding to their environmental compatibility. To establish these testing methods, we use polystyrene (PS) and polypropylene (PP) with environmental relevant brominated flame retardants, known for their persistent bioaccumulative and toxic (PBT) properties. In case of PS the material contains 1 wt% of 1,2,5,6,9,10-hexabromocyclododecan (HBCD) and in case of PP 0.1 wt% bromodiphenylether (BDE-209), which is known as a substance of very high concern (SVHC). Furthermore, we use polycarbonate (PC), which is still used as material in baby flasks and releases Bisphenol A (BPA), an estrogenic active substance.
As an additional material PTFE is used for its importance as a source for two ubiquitous environmental substances (PFOS and PFOA), whose toxicological effects are still incompletely known.
The focus in this current work is set on the transfer of potential pollutants out of applied materials mentioned above into environmental compartments like water or soil. Here an accelerated aging concept should be developed to shortened time consuming natural processes. For these resulting simulations we use a programmable weathering chamber with dry and wet periods and with high and low temperatures. These programmes run for several weeks and according to a defined sampling schedule we take water samples, run a clean-up procedure by SPE (Molecular imprinted polymers (MiPs) resp. polymer-based cartridges (Waters Oasis HLB)) and analyse them by HPLC-UV resp. LC-MS/MS. Of most interest in case of flame retardants are photocatalytic transformation products. Therefore, we conduct a non-target-screening resp. a suspected target-screening by LC-MS/MS and HRMS.
In respect of an efficient cultivation of agricultural cropland, a site-specific fertility management is necessary. Therefore, affordable and extensive mapping methods are needed. The research projects I4S (intelligence for soil) has the goal to develop a system for this purpose. I4S is one of ten interdisciplinary research project associations of the innovation programme called BonaRes, which is funded by the German Federal Ministry of Education and Research (BMBF).
The system includes a sensor platform, which contains different sensors, like XRF, VIS-NIR, Gamma and LIBS. The main task of LIBS measurements in this project is the real-time determination of the elemental contents of major and minor nutrients in soils, like calcium, magnesium, potassium. LIBS (laser-induced breakdown spectroscopy) is known as a fast and simultaneous multi-element analysis with little or no sample preparation. The main task of LIBS measurements in this project is the real-time determination of the elemental contents of nutrients in soils, like calcium, magnesium, potassium. For this purpose, a special setup has been designed. The sample uptake operates with the help of a rotatable sample plate which circulates with different velocities to simulate the application on the field. To provide a higher intensity and a better reproducibility of the obtained signal, a double-pulse Nd:YAG laser (1064 nm)was used. In order to minimize dust formation from the soil during the operation of the laser, a dust removal by suction has been integrated. When using relative methods such as LIBS, a suitable calibration curve is needed for absolute quantification. The complex matrix of soils, as well as the influence of moisture and grain size in soils makes the absolute quantification by LIBS challenging. To overcome these influences, chemometric methods were used. With the principal component analysis (PCA) a classification of soils into different soil types was performed and a calibration curve based on partial least squares regression (PLSR) was generated. With this calibration model’s elemental distribution maps for different German agricultural fields were created.
In respect of an efficient cultivation of agricultural cropland, a site-specific fertility management is necessary. Therefore, affordable and extensive mapping methods are needed. For this purpose, the research project I4S (intelligence for soil) has the goal to develop an integrated system. This system includes a sensor platform, which contains different sensors, like XRF, VIS-NIR, Gamma and LIBS.
LIBS (laser-induced breakdown spectroscopy) is known as a fast and simultaneous multi-element analysis with little or no sample preparation. The main task of LIBS measurements in this project is the real time determination of the elemental contents of nutrients in soils, like calcium, magnesium, potassium. For this purpose, a special setup has been designed. The sample uptake operates with the help of a rotatable sample plate which circulates with different velocities to simulate the application on the field. To provide a higher intensity and a better reproducibility of the obtained signal, a double-pulse Nd:YAG laser (1064 nm) was used. In order to minimize dust formation from the soil during the operation of the laser, a dust removal by suction has been integrated.[1] When using relative methods such as LIBS, a suitable calibration curve is needed for absolute quantification. The complex matrix of soils, as well as the influence of moisture and grain size in soils makes the absolute quantification by LIBS challenging. To overcome these influences, chemometric methods were used. With the principal component analysis (PCA) a classification of soils into different soil types was performed and a calibration curve based on partial least squares regression (PLSR) was generated. With this calibration model’s elemental distribution maps for different German agricultural fields were created.
Von der zunehmenden Digitalisierung sind alle Bereiche von Wirtschaft, Industrie und Gesellschaft betroffen. Die Digitalisierung führt zu einer verstärkten virtuellen Nutzung von Ressourcen und zu einer hochdynamischen Entwicklung der zugehörigen Forschungs- und Technologiefelder. Neue Technologien sind die Basis für die erfolgreiche Weiterentwicklung des Wirtschaftsstandortes Deutschland und für eine Wertschöpfung in globalen Märkten. Die nachhaltige Sicherheit neuer Technologien schafft das Vertrauen der Bürger in den Wandel und sichert unsere Zukunft.
Im Vortrag werden Anforderungen und Lösungsvorschläge für das Labor der Zukunft diskutiert. Industrie 4.0 bzw. das Labor 4.0 hilft uns, komplexere Prozesse schneller umzusetzen. Entwicklung von Anlagen und Prozessen beginnt im Labor 4.0. Dazu werden offene, nicht proprietäre Schnittstellen und Standards bei Laborgeräten und Feldgeräten dringend benötigt. Der Standard OPC-UA wird derzeit als gesetzt gesehen. Als nächstes ist die Festlegung der Semantik (Companion Specification) erfordert. Als Bitte an die Zulieferer und Geräterhersteller wird gerichtet, möglichst keine Alleingänge hinsichtlich Schnittstellen, Standards oder GUI zu unternehmen, sondern diese mit den Anwendern abzustimmen. Auf diese Weise ergibt sich das in Industrie 4.0 geforderte "durchgehende Engineering“.
Die Sicherung der Wettbewerbsfähigkeit des Standorts Deutschland/Europa ergibt sich dann gleich in doppelter Hinsicht: Sichere, verfügbare und effiziente Herstellung international wettbewerbsfähiger Produkte für die Anwender sowie weltweiter Export von Mess- und Regeltechnik für die Messtechnikbranche.
The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here, we compare time-gated Raman (TG-Raman)-, continuous wave NIRprocess Raman (NIR-Raman), and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP, and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids, and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis.
Aim of the Federal Institute for Materials Research and Testing (BAM) in the frame of I4S - “Intelligence for Soil” is the characterization of an X-ray fluorescence (XRF) based sensor for robust online-application of arable land.Fast soil mapping for agricultural purpose allows the site-specific optimized introduction of plant essential nutrients like S, K, Ca, and Fe. This is important given that the distribution of minor and trace elements varies widely. The non-destructive and contactless XRF is suitable for rapid in-situ analysis on the field due to minimal sample preparation and simultaneous multi-element analysis.
Soils are already considered as a complex matrix due to their wide range of elements in different contents, especially light elements with low atomic numbers (Z<19). Problems by measuring soil samples also arise from heterogeneity of the sample and matrix effects. Large grain size distribution causes strong inhomogeneity and matrix effects occur through physical properties related to high concentration of main components. Matrix-specific calibration strategies for determination of total major and minor plant essential nutrients are particularly important regarding these difficulties. For accurate calibration, data treatment and evaluation must also be considered. Empirical univariate and multivariate data analysis were compared regarding their analytical figures of merit. Using principal component analysis (PCA) it was possible to classify German soils in different groups as sand, clay and silt. A calibration curve was obtained by partial least squares regression (PLSR) and the elemental content of German soils was predicted. Elemental distribution maps for different German arable lands were created and the results compared to reference measurements. The correlation between predicted values and reference values were in good agreement for most major and minor nutrients.
As part of the BonaRes research initiative funded by the German Federal Ministry of Education and Research (BMBF), strategies are being developed to use soil as a sustainable resource in the bioeconomy. The interdisciplinary subproject I4S - “Intelligence for soil” - is responsible for the development of an integrated system for site-specific management of soil fertility. For this purpose, a platform is constructed and various sensors are installed. Real-time data will be summarized in models and decision-making algorithms will be used to control fertilization and accordingly improve soil functions. This would allow investigations in close meshed dynamic grid and fast analysis of large areas to generate higher yields. This is important given that the distribution of minor and trace elements varies widely. Aim of the Federal Institute for Materials Research and Testing (BAM) in the frame of I4S is the characterization of an X-ray fluorescence (XRF) based sensor for robust online-analysis of arable land. The non-destructive and contactless XRF is suitable for rapid in-situ analysis on the field due to minimal sample preparation and simultaneous multi-element analysis.
Soils are already considered as a complex matrix due to their wide range of elements in different contents, especially light elements with low atomic numbers (Z<19). Problems by measuring soil samples also arise from heterogeneity of the sample and matrix effects. Large grain size distribution causes strong inhomogeneity and matrix effects occur through physical properties related to high concentration of main components. Matrix-specific calibration strategies for determination of total major and minor plant essential nutrients are particularly important regarding these difficulties. For accurate calibration, data treatment and evaluation must also be considered. Univariate and multivariate data analysis were compared regarding their analytical figures of merit. Using principal component analysis (PCA) it was possible to classify German soils in different groups as sand, clay and silt. Calibration models were obtained by partial least squares regression (PLSR) and the content of macro- and micronutrients in German soils was predicted. Elemental distribution maps for different German arable lands were created and the results compared to reference measurements. The correlation between predicted values and reference values were in good agreement for most major and minor nutrients.
Gegenstand der vorzustellenden Arbeiten ist die Prüfung der Umwelt-beständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polystyrol (PS) und Polypropylen (PP) zum Einsatz. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden.
Gegenstand der vorzustellenden Arbeiten ist die Prüfung der Umweltbeständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polystyrol (PS) und Polypropylen (PP) zum Einsatz, die jeweils mit polybromierten Flammschutzmitteln (PBFSM) versehen sind. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Auch soll mit Hilfe der RFA und der LA-ICP-MS die Abreicherung der PBFSM in den Modellmaterialien beschrieben werden. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden.
Bestimmung von Makro- und Mikronährstoffen in Böden mittels laserinduzierter Plasmaspektroskopie
(2018)
In respect of an efficient cultivation of agricultural cropland, a site-specific fertility management is necessary. Therefore, affordable and extensive mapping methods are needed. The research projects I4S (intelligence for soil) has the goal to develop a system for this purpose. I4S is one of ten interdisciplinary research project associations of the innovation programme called BonaRes, which is funded by the German Federal Ministry of Education and Research (BMBF).
The system includes a sensor platform, which contains different sensors, like XRF, VIS-NIR, Gamma and LIBS. The main task of LIBS measurements in this project is the real-time determination of the elemental contents of major and minor nutrients in soils, like calcium, magnesium, potassium. LIBS (laser-induced breakdown spectroscopy) is known as a fast and simultaneous multi-element analysis with little or no sample preparation. The main task of LIBS measurements in this project is the real-time determination of the elemental contents of nutrients in soils, like calcium, magnesium, potassium. For this purpose, a special setup has been designed. The sample uptake operates with the help of a rotatable sample plate which circulates with different velocities to simulate the application on the field. To provide a higher intensity and a better reproducibility of the obtained signal, a double-pulse Nd:YAG laser (1064 nm) was used. In order to minimize dust formation from the soil during the operation of the laser, a dust removal by suction has been integrated. When using relative methods such as LIBS, a suitable calibration curve is needed for absolute quantification. The complex matrix of soils, as well as the influence of moisture and grain size in soils makes the absolute quantification by LIBS challenging. To overcome these influences, chemometric methods were used. With the principal component analysis (PCA) a classification of soils into different soil types was performed and a calibration curve based on partial least squares regression (PLSR) was generated. With this calibration model’s elemental distribution maps for different German agricultural fields were created.
Im DFG-Schwerpunktprogramm 1374, Teilprojekt FunWood IV, erfolgt in Kooperation mit dem Institut für Bioanalytik an Hochschule für angewandte Wissenschaften, Coburg und dem Helmholtz-Zentrum für Umweltforschung (UFZ), Leipzig die Untersuchung des Ligningehalts von natürlich gealterten Hölzern. Zu diesem Zweck soll an der BAM eine NIR spektroskopische Methode entwickelt werden, die auch zur Untersuchung großer Stückzahlen geeignet ist. Insgesamt liegen exponierte Proben von 13 verschiedenen Hölzern vor, die sukzessive durch die Kooperationspartner kryovermahlen und getrocknet werden. Für jede der 13 Arten wurden jeweils 300 Holzstücken ausgebracht, exponiert und im Sommer 2018 wieder eingesammelt. Die Ergebnisse sollen als Grundlage für die Bewertung eines Langzeitversuchs zum Einfluss von Waldbewirtschaftungsintensität und Baumartenidentität über mehrere geographische Dimensionen dienen.
Der Vortrag gibt einen Überblick über die aktuellen Diskussionen zu Feldgerätekommunikation in der Prozessindustrie. Diese verfolgt seitens der Anwender in der NAMUR das NOA-Konzept (NOA = NAMUR Open Architecture). In gemeinsamen Aktivitäten mit dem ZVEI werden mit Zielstellung Mitte/Ende 2019 folgende Konzepte vorangebracht: NOA Informationsmodell in OPC UA,
Informationssicherheit und das Konzept des „Verification of Request“. Gemeinsam mit Geräte- und Softwareherstellern sollen auch M+O-Sensoren (Maintenance und Optimization) konzipiert werden.
Aus dem NAMUR AK 3.7 heraus wurde im Oktober ein Erweiterter Arbeitskreis „Smarte Sensoren, Aktoren und Kommunikation“ kontituiert, dem auch Geräte- und Softwarehersteller und das BSI angehören. Hier werden konkrete Anwendungsfälle für smarte Feldgeräte und Anforderungen an M+O-Sensoren erarbeitet, um die Bereitstellung und den Einsatz smarter Automatisierungskomponenten zu beschleunigen.
Zukünftig werden das „Smarte Labor“ und die „Smarte Produktion“ stärker zusammenwachsen.
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 an overview from direct dissolution studies of API cocrystals to studies of emulsions for a hydroformylation.
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).
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.
Industry 4.0, IIoT, or Lab 4.0 will enable us to handle more complex processes in shorter time. Intensified production concepts require for adaptive analytical instruments and control technology to realize short set-up times, modular control strategies. They are based on a digitized Laboratory 4.0.
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).
The CLEAN ENERGY Flagship is an initiative designed to utilize recent game changing developments in digital, materials and manufacturing technologies to catalyze a radical paradigm shift towards clean, reliable, efficient and cost-optimal energy.
Unifying and drastically accelerating radically new energy material design, processing and integration across the entire value chain addressing energy production, conversion, storage and systems.
CLEAN ENERGY participants are all distinguished research organisations that each benefit from their own industry networks and contacts with regions and state-level activities and have a long history of collaborating with each other (for 10 years now under the umbrella of EERA) within a European collaborative framework.
Through EERA, CLEAN ENERGY aims to become a crucial partner in the SET-Plan, supporting long-lasting approaches through its established networks and internal collaborations.
Already Analyzing or Still Calibrating? - Demonstration of an online NMR analyzer in pilot scale
(2018)
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).
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 wurde 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 kalibrierfreie 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.
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 used for process characterisation and optimisation.
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 online NMR spectroscopy 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 module 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).
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 sus-tainable fashion, and to adapt quickly to changing customer needs. The transition of process industry due to the mounting digitalization of technical devices and their pro-vided data used in chemical plants proceeds. Though, the detailed characteristics and consequences for the whole chemical and pharmaceutical industry are still unfore-seeable, 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 in-dustry lack of sufficient system and development concepts with commercial advantage from this trend.
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 pro-duce 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 sensor1,2 (as addressed, e.g., in the CONSENS project3).
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 reaction3. As an example for such a modular process unit, we present the design and validation of an integrated NMR micro mixer based on computational mod-elling 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.
References:
[1] M. V. Gomez et al., Beilstein J. Org. Chem. 2017, 13, 285-300
[2] K. Meyer et al., Trends Anal. Chem. 2016, 83, 39-52
[3] S. Kern et al., Anal Bioanal Chem. 2018, 410, 3349-3360
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.
Digitalisierung und Industrie 4.0 verändern komplette Geschäftsmodelle, heben neue Effizienzpotenziale und stärken die Wettbewerbsfähigkeit. Auf dem 57. Tutzing-Symposion vom 15.–18.04.2018 wurde mit Vorträgen und Kreativworkshops erkundet, welche speziellen Anforderungen die Prozessindustrie hat, welche digitalen Innovationen bereits umgesetzt wurden und wo noch Handlungsbedarf besteht. Ein Workshop befasste sich mit den Themenfeldern Datenkonzepte, Datenanalyse, Big Data und künstliche Intelligenz. Es geht nicht um die Digitalisierung von heute. Im Angesicht der wachsenden Digitalisierung unserer Prozesse stellt sich die Frage, ob wir den Prozess wirklich gut kennen. Ob alle Verfahrensschritte detailliert hinterlegt wurden. Nur mit einem heuristischen Ansatz kann das vorhandene Wissen nicht digitalisiert werden.
Sehr schnell werden die Mechanismen eines Massenmarktes mit denen einer Nische verwechselt. Nicht jeder Mechanismus, den wir von großen Suchmaschinen oder Einkaufsportalen kennen, gibt uns einen Hinweis auf Nutzen und Verfügbarkeit für die Prozess- oder pharmazeutische Industrie. Eine gute Analyse der Anforderungen in der Zukunft mit einem Abgleich der derzeitigen technischen Möglichkeiten ist Voraussetzung für eine Verbesserung der derzeitigen digitalen Umsetzung. Dabei ist es sinnvoll unkonventionelle Methoden einzusetzen.