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qNMR - The handbook
(2023)
Quantitative NMR (qNMR) has been around for a long time, but also has great potential to solve future problems in any quantitative analysis. As a primary method, it differs fundamentally from chromatographic methods: it is better described as a quantum mechanical balance. Succesful implementation of qNMR requires certain attention to detail. "qNMR - the handbook" is intended to be a guide for analysts to help understand the fundamental principles of NMR and the significant points relating to its implementation for quantitation. Regulatory considerations of qNMR adoption are explained. NMR fundamentals are explained to provide understanding. Together with many useful examples, the book is a compelling addition to the laboratory's reference library, providing all the tools that any practitioner should know to successfully implement qNMR.
The authors are qNMR pioneers and come from a variety of backgrounds including business, government and academia.
Plastic pollution is the biggest environmental concern of our time. Breakdown products like micro- and nanoplastics inevitably enter the food chain and pose unprecedented health risks. In this scenario, bio-based and biodegradable plastic alternatives have been given a momentum aiming to bridge a transition towards a more sustainable future. Polyhydroxyalkanoates (PHAs) are one of the few thermoplastic polymers synthesized 100 % via biotechnological routes which fully biodegrade in common natural environments. Poly(hydroxybutyrate-cohydroxyhexanoate) [P(HB-co-HHx)] is a PHA copolymer with great potential for the commodity polymers industry, as its mechanical properties can be tailored through fine-tuning of its molar HHx content. We have recently developed a strategy that enables for reliable tailoring of the monomer content of P(HB-co-HHx).
Nevertheless, there is often a lack of comprehensive investigation of the material properties of PHAs to evaluate whether they actually mimic the functionalities of conventional plastics. We present a detailed study of P(HB-co-HHx) copolymers with low to moderate hydroxyhexanoate content to understand how the HHx monomer content influences the thermal and mechanical properties and to link those to their abiotic degradation. By increasing the HHx fractions in the range of 2 – 14 mol%, we impart an extension of the processing window and application range as the melting temperature (Tm) and glass temperature (Tg) of the copolymers decrease from Tm 165 ◦C to 126 ◦C, Tg 4 ◦C to − 5.9 ◦C, accompanied by reduced crystallinity from 54 % to 20 %.
Elongation at break was increased from 5.7 % up to 703 % at 14 mol% HHx content, confirming that the range examined was sufficiently large to obtain ductile and brittle copolymers, while tensile strength was maintained throughout the studied range. Finally, accelerated abiotic degradation was shown to be slowed down with an increasing HHx fraction decreasing from 70 % to 55 % in 12 h.
In industrialised countries more than 80% of the time is spent indoors. Products, such as building materials and furniture, emit volatile organic compounds (VOCs), which are therefore ubiquitous in indoor air. VOC in combination may, under certain environmental and occupational conditions, result in reported sensory irritation and health complaints. Emission concentrations can become further elevated in new or refurbished buildings where the rate of air exchange with fresh ambient air may be limited due to improved energy saving aspects. A healthy indoor environment can be achieved by controlling the sources and by eliminating or limiting the release of harmful substances into the air. One way is to use (building) materials proved to be low emitting. Meanwhile, a worldwide network of professional commercial and non-commercial laboratories performing emission tests for the evaluation of products for interior use has been established. Therefore, comparability of test results must be ensured. A laboratory’s proficiency can be proven by internal and external validation measures that both include the application of suitable emission reference materials (ERM). For the emission test chamber procedure according to EN 16516, no artificial ERM is commercially available. The EU-funded EMPIR project MetrIAQ aims to fill this gap by developing new and improved ERMs. The goal is to obtain a material with a reproducible and temporally constant compound release (less than 10 % variability over 14 days). Two approaches were tested: the impregnation of porous materials with VOC, and the encapsulation of VOC in polymer microcapsules. Impregnation is performed with help of an autoclave and supercritical CO2. The encapsulation is done by interfacial polymerisation on VOC droplets. For both approaches, synthesis and/or material parameters were varied to obtain an optimal ERM. Findings about the optimisation of ERM generation, as well as performance of the best emission reference materials, will be presented.
Establishing ZIF‐8 as a reference material for hydrogen cryoadsorption: An interlaboratory study
(2024)
AbstractHydrogen storage by cryoadsorption on porous materials has the advantages of low material cost, safety, fast kinetics, and high cyclic stability. The further development of this technology requires reliable data on the H2 uptake of the adsorbents, however, even for activated carbons the values between different laboratories show sometimes large discrepancies. So far no reference material for hydrogen cryoadsorption is available. The metal‐organic framework ZIF‐8 is an ideal material possessing high thermal, chemical, and mechanical stability that reduces degradation during handling and activation. Here, we distributed ZIF‐8 pellets synthesized by extrusion to 9 laboratories equipped with 15 different experimental setups including gravimetric and volumetric analyzers. The gravimetric H2 uptake of the pellets was measured at 77 K and up to 100 bar showing a high reproducibility between the different laboratories, with a small relative standard deviation of 3–4 % between pressures of 10–100 bar. The effect of operating variables like the amount of sample or analysis temperature was evaluated, remarking the calibration of devices and other correction procedures as the most significant deviation sources. Overall, the reproducible hydrogen cryoadsorption measurements indicate the robustness of the ZIF‐8 pellets, which we want to propose as a reference material.
The application of compact NMR instruments to continuously flowing samples at higher temperatures or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is typically not designed for compensation of such effects. Passive insulation is restricted by the small dimensions within the magnet borehole.
Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements using an optical thermo-graphy setup, a model predictive control was set up to minimize any disturbance effect on the permanent magnet from the probe or sample temperature.
This methodology will facilitate the application of variable-temperature shielding and, therefore, potentially extend the application of compact NMR instruments to flowing samples at higher temperature than the permanent magnet.
Die NMR-Spektroskopie ist eine der zentralen nicht-invasiven Analysenmethoden in der organischen Chemie und aus dem Laboralltag nicht mehr wegzudenken. Die direkte Proportionalität zwischen der Anzahl der Atomkerne im Messvolumen und der Signalfläche im Spektrum ist vergleichbar mit einem „Zählen der Kernspins“. Der Kalibrieraufwand für die Quantifizierung ist minimal und aus dem NMR-Spektrum sind Informationen zu Struktur und Identität zugänglich.
Online-NMR-Spektroskopie wird unter Zuhilfenahme von speziellen Durchflussproben-köpfen und Messzellen bereits seit Jahrzehnten erforscht und eingesetzt. Durch die hohen Anforderungen an die Aufstellung und den Betrieb von klassischen Hochfeld-NMR-Spektrometern konnte sie allerdings nie den Sprung vom Labor in den Prozess schaffen. Dies hat sich durch die Entwicklungen im Bereich mobil einsetzbarer Benchtop-NMR-Spektrometer grundlegend verändert. Geringere Investitions- und Betriebskosten, sowie die Robustheit und einfache Bedienbarkeit dieser Systeme sind entscheidende Faktoren. Damit rückt eine Anwendung als Online-PAT-Methode technisch in greifbare Nähe. Designierte Prozess-NMR-Spektrometer sucht man heutzutage allerdings auf dem Markt meist noch vergebens.
Die Reaktionsverfolgung im Labormaßstab konnte an unterschiedlichen Systemen erfolgreich demonstriert werden. Dabei zeigten sich allerdings Limitierungen in Hinblick auf einen möglichen Prozesseinsatz. Insbesondere die Temperaturempfindlichkeit der Magnetsysteme ist hier zu nennen. Anhand eines Prototyps wurde eine aktive Temperaturisolation mittels temperierter Luftströmungen entwickelt und erprobt.
Eine Feldintegration von Laborsystemen geht sowohl technisch als auch regulatorisch mit zahlreichen Herausforderungen einher. Das raue Umfeld von Produktionsanlagen, sowie die Anforderungen an Explosionsschutz erfordern eine zugelassene Einhausung. Auf Basis von Erfahrungen mit einem ersten Prototyp erfolgte die gemeinsame Entwicklung eines möglichst flexibel einsetzbaren Analysenschranks. Neben der Hardware-Integration sind die automatisierte modellbasierte Auswertung der NMR-Spektren, sowie die Einbindung in die Prozessleittechnik essenziell für einen zuverlässigen Betrieb als PAT-Analysengerät.
Um die internationale Spitzenposition deutscher Unternehmen der Prozessindustrie auch in Zukunft sicher zu stellen, müssen die Unternehmen ihre Prozesse und Geschäftsabläufe digitalisieren und gemeinsam mit der Forschung innovative neue Methoden, Apparate, Anlagen, Sensoren und Automatisierungstechnik sowie Datenkonzepte entwickeln. All dies erfordert den Aufbau neuer Fähigkeiten, Investition in Talente, interdisziplinäre Kommunikation zwischen verschiedenen Personen und Abteilungen und eine Bereitschaft zur Veränderung.
The application of compact NMR instruments to hot flowing samples or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is not designed for such temperature compensation. Passive insulation is restricted by the small dimensions within the magnet borehole.
Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements through thermography, a model predictive control was set up to minimise any disturbance effect on the permanent magnet from the probe or sample temperature.
This methodology will facilitate the application of variable-temperature shielding and, therefore, extend the application of compact NMR instruments to flowing sample temperatures that differ from the magnet temperature.
Global demand for pigments is expected to increase to around 13.4 million tons per year by 2030, representing approximately $22 billion – 5% of which will be azo pigments as the main organic pigments. Azo pigments, i.e., especially the azo bridge required for them, are almost exclusively produced in technology by the so-called azo coupling reaction in large-scale approaches on the scale of 50–100 cubic meters. Among other things, one of the reasons why large-scale production itself is still essentially discontinuous is the lack of analytical methods for a continuous azo pigment synthesis.
In an azo coupling process, an aromatic amine is diazotized to form the diazonium compound (diazo compound), which then reacts with a coupling component, i.e., "couples". A slight excess of the coupler is desired for the end of the reaction, which stoichiometrically consumes the remaining (harmful) diazo compound, i.e., below 500 ppm. This is carried out with a manual spotting reaction of a fast-binding coupler.
To carry out continuous azo coupling, care must be taken to ensure that the actual coupling reaction proceeds as rapidly as possible, i.e., preferentially, compared with possible side reactions. Reliable measuring methods are thus a decisive criterion for the useful performance of a continuous azo pigment synthesis. An analytical online procedure is difficult due to several limitations at once: solid dispersions extremely limit the range of reproducible analytical procedures. In addition, the appearance of a signal (e.g., excess of a starting material) in the ppm range must be reliably detected against the matrix background.
The back-titration method and benchtop NMR spectroscopy were used to overcome these problems. We present a feasibility study for a suitable process analysis with benchtop NMR spectroscopy on disperse systems for equimolar dosing of the "diazotization" or "coupling" sub-step in azo coupling, which was carried out in cooperation with a chemical company. This could replace tedious manual spotting
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2023)
Companies of chemical industry find themselves more often in a rapidly changing environment, e.g., due to variability of raw material quality or energy costs and efficiency. Process optimization and new process concepts become more and more important. For example, flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds like exothermic reactions with high heat dissipation.
Highly automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis approach, which can even serve as reliable reference method for further calibration-dependent PAT applications (e.g., NIR or Raman spectroscopy).
Based on experiences from earlier field studies an improved NMR analyzer enclosure setup was developed and built, including the option of a secondary method (e.g., optical spectroscopy). Integrated control systems allow for a flexible implementation based on the available automation infrastructure at the chemical plant or pilot plant setup. In the future, fully integrated and intelligently interconnecting “smart” PAT systems and processes have the potential speed up the setup of production equipment for chemicals and pharmaceuticals and therefore help to reduce the time-to-market.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements
Volatile organic compound (VOC) emissions from consumer products contribute to human inhalation exposure and may cause adverse health effects. Existing methods to determine long-term VOC emissions from e.g. building products need to be verified for their suitability to reliably detect initial VOC emissions from consumer products within the first hours and days of use, which would facilitate realistic inhalation exposure assessments. To investigate this issue, VOCs emitted from a test sample were determined in a large-scale emission test chamber and in two micro-chambers of different volumes, and the results were compared.
Round robin tests of odour and VOC emissions from building products – What have we learned so far?
(2023)
Emission testing of volatile organic compounds (VOC) and odour from materials and products is commonly based on emission test chamber measurements. These measurements are often the basis of mandatory or voluntary labelling procedures. To ensure the comparability of results from different testing laboratories their performance must be verified. For this purpose, round robin tests (RRTs) are conducted. Bundesanstalt für Materialforschung und - prüfung (BAM) offers such a RRT every two years using well characterised test materials with defined VOC emissions. In addition to the VOC quantification, the evaluation of odour is also implemented in the round robin tests. At the beginning, only perceived intensity (PI) was tested but over the years also the acceptance evaluation was considered. In principle, the results of PI and acceptance evaluation are comparable. The advantage of PI is the lower number of panel members necessary for one evaluation.
This study uses conventional 87Sr/86Sr and 143Nd/144Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg and Ti as fingerprints for provenancing ordinary Portland cements (OPC). Herein, the first database of Sr and Nd isotope ratios investigated in OPCs, stemming from 29 cement plants located worldwide, was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 143Nd/144Nd in OPCs is not as large as the spread for 87Sr/86Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the OPCs investigated have measurable differences in their 87Sr/86Sr and 143Nd/144Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, divisive hierarchical clustering was employed to help overcome this issue. The construction of geochemical profiles allowed the computing of suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of the 29 ordinary Portland cements that were analysed.
The application of compact NMR instruments to hot flowing samples or exothermically reacting mixtures is limited by the temperature sensitivity of permanent magnets. Typically, such temperature effects directly influence the achievable magnetic field homogeneity and hence measurement quality. The internal-temperature control loop of the magnet and instruments is not designed for such temperature compensation. Passive insulation is restricted by the small dimensions within the magnet borehole. Here, we present a design approach for active heat shielding with the aim of variable temperature control of NMR samples for benchtop NMR instruments using a compressed airstream which is variable in flow and temperature. Based on the system identification and surface temperature measurements through thermography, a model predictive control was set up to minimise any disturbance effect on the permanent magnet from the probe or sample temperature. This methodology will facilitate the application of variable-temperature shielding and, therefore, extend the application of compact NMR instruments to flowing sample temperatures that differ from the magnet temperature.
Modular chemical production is a tangible implementation of the digital transformation of the specialty chemicals process industry. In particular, it enables acceleration of process development and thus faster time to market by flexibly interconnecting and orchestrating standardized physical modules and bringing them to life. For this purpose, specific (chemical) sensors of process analytics are needed, preferably without lengthy calibration or spectroscopic model development.
An excellent example of a "direct" analytical method is online nuclear magnetic resonance (NMR) spectroscopy. NMR spectroscopy meets the requirements of a direct analytical method because of the direct correlation between the signal area in the spectrum ("counting" the nuclear spins) and the analyte amount of substance concentrations. It is also extremely linear over the concentration range.
With the availability of compact benchtop NMR instruments, it is now possible to bring NMR spectroscopy directly into the field, in close proximity to specialized laboratory facilities, pilot plants, and even industrial-scale production facilities. The first systems are in TRL 8 (Qualified System with Proof of Functionality in the Field).
The presentation will discuss the many building blocks of online nuclear magnetic resonance spectroscopy, from flow cells to automated data analysis.
The use of benchtop-NMR instruments is constantly increasing during the recent years. Advantages of being affordable, portable and easy-to-operate without the need for trained staff make them especially interesting for industrial applications in quality control. However, applications of NMR spectroscopy as an online PAT tool are still very rare but offer a huge potential for process optimization and control. A key task to exploit this potential is hardware field integration of the lab-instruments in a rough environment of a chemical plant. Additionally, developments in automation and data evaluation are mandatory to ensure a robust unattended operation with low maintenance requirements. Here, we show an approach of a fully automated analyzer enclosure considering explosion safety, field communication, as well as environmental conditions in the field.
Temperature sensitivity is still a limitation of benchtop-NMR instruments in flow applications. Recent developments of manufacturers allow for limited operation at static temperature levels, however, a dynamic system for continuous operation is still not available. Using a prototype system offering a larger bore, active temperature shielding studies with thermostated air were performed evaluating the performance.
Automated data evaluation of NMR spectra using a modular indirect hard modeling (IHM) approach showed good results and flexibility. A second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously, offering new ways to simultaneously evaluating large numbers of different models.
Anhand von Beispielen wird in diesem Vortrag ein möglicher ganzheitlicherer Ansatz für die Digitalisierung und den Einsatz maschinengestützter Prozesse bei der Herstellung von Spezialchemikalien und Arzneimitteln durch die Einführung integrierter und vernetzter Systeme und Prozesse skizziert. Ein aktueller Ansatz und ein Beispiel in diesem Vortrag sind flexible und modulare chemische Produktionseinheiten, die Mehrzweckanlagen nutzen, um verschiedene hochwertige Produkte mit kurzen Stillstandszeiten zwischen den Kampagnen herzustellen und die Markteinführungszeit für neue Produkte zu verkürzen.
Als zweites Beispiel wird kurz die Testplattform Wasserstofftankstelle vorgestellt, die als moderne Anlage der Prozessindustrie betrachtet werden kann, vergleichbar mit einer Anlage aus der chemischen oder pharmazeutischen Industrie. An ihr lassen sich alle derzeit entlang der Digitalen Transformation diskutierten Konzepte implementieren, um sie zu standardisieren und zu validieren. Dazu gehören Konzepte zur Konnektivität von Sensoren und Aktoren aus der Feldebene in höhere Ebenen der Automatisierung oder zur Einbringung zusätzlicher Sensoren oder Sensornetzwerke, die zunehmend flexibler gestaltet werden soll, die sichere und nachvollziehbare Parametrierung von Automatisierungskomponenten – vielleicht aus einem digitalen Abbild (Verwaltungsschale bzw. „Digitaler Zwilling“) heraus, Konzepte zur vorausschauenden Wartung („Predictive Maintenance“), Konzepte zu digitalen Entscheidungsprozessen, Zertifikaten und Signaturen oder der zunehmende Einsatz von komplexen Auswertungsalgorithmen und Applikationen in der Feldebene („Embedded Computing“) oder der „Kante“ zu Cloudbasierten Systemen der Informationstechnik („Edge-Computing“).
Die beiden Beispiele sollen aktuelle Entwicklungsachsen des industriellen Messwesens im Rahmen der industriellen Automation aufzeigen, in denen Messwerte, deren Messunsicherheiten und Kontextinformationen eine wichtige Rolle einnehmen.
In Deutschland werden jährlich rund 20 Millionen Tonnen künstliche Mineralwolle für die Dämmung von Dächern und Fassaden sowie für Brandschutzprodukte verwendet. Um künstliche Mineralwolle aus Rückbaumaßnahmen in den Produktionsprozess zurückführen zu können, ist eine Trennung in Glas- und Steinwolle erforderlich, um eine Vermischung der beiden Produkte, die unterschiedliche Schmelztemperaturen aufweisen, zu vermeiden. Anstatt die Mineralwolle in spezielle Labors zu schicken, was zeitaufwendig und teuer ist, wurde das Potenzial eines tragbaren Nahinfrarot-Spektrometers (NIR) für den Einsatz vor Ort getestet. 140 verschiedene Mineralwolleproben wurden untersucht, um eine NIR-basierte Methode für die Vor-Ort-Unterscheidung zwischen Glas- und Steinwolle zu etablieren. Die Validierung der Methode mit Testproben und die Anwendung auf Materialien, die aus BigBags für Deponien entnommen wurden, haben gezeigt, dass die Methode präzise und robust ist. Als Referenzmethode wurde die Röntgenfluoreszenzspektroskopie (RFA) mit einer Kalibrierung auf der Grundlage der VDI 3492 verwendet.
Optimizing the Green Synthesis of ZIF-8 by Reactive Extrusion Using In Situ Raman Spectroscopy
(2023)
We report the scale-up of a batch solid synthesis of zeolitic imidazolate framework-8 (ZIF-8) for reactive extrusion. The crystalline product forms in the extruder directly under the mixture of solid 2-methylimidazole and basic zinc carbonate in the presence of a catalytic amount of liquid. The process parameters such as temperature, liquid type, feeding rate, and linker excess were optimized using the setup specifically designed for in situ Raman spectroscopy. Highly crystalline ZIF-8 with a Brunauer–Emmett–Teller (BET) surface area of 1816 m2 g–1 was quantitatively prepared at mild temperature using a catalytic amount of ethanol and a small excess of the linker. Finally, we developed a simple and comprehensive approach to evaluating the environmental friendliness and scalability of metal–organic framework (MOF) syntheses in view of their large-scale production.
ISO 14687 defines threshold limits for expectable impurities in hydrogen that is assigned for use in polymer electrolyte membrane (PEM) fuel cells. This work describes the establishment of the traceability of some selected impurities by preparation and analysis of reference gases with the lowest possible uncertainty in composition. Primary reference gases were produced by the gravimetric method according to ISO 6142-1 and the analysis was carried out by operating measurement protocols according to ISO 12963 on two customized trace GC analysers.
Introduction
NMR spectroscopy is one of the most important analytical methods in organic chemistry. While most analyses are carried out qualitatively with the aim of substance identification and structure elucidation, quantitative NMR spectroscopy (qNMR) is increasingly gaining importance in research and industry. 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.
Methods
One of the most attractive features of quantitative NMR spectroscopy is that the NMR peak areas can be used directly for concentration quantification without further calibration. Another advantage of NMR spectroscopy is that the method has a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical comparison method that is independent of the matrix. This enables automated robust data evaluation strategies that can be used for online applications of qNMR spectroscopy.
Jancke et al. proposed NMR spectroscopy as a relative primary analytical method because it can be fully described by mathematical equations from which a complete uncertainty budget can be derived, allowing it to be used at the highest metrological level. Weber et al. discussed in detail important aspects of the procedure that enable the realisation of low measurement uncertainties in qNMR measurements. Since certification of CRM requires expanded mea¬sure¬ment uncertainties of less than 0.5 % (relative), the work of Weber et al. demonstrated for the first time that qNMR can fulfil this criterion.
Results
To date, further comparative studies have been carried out in metrology and industry, demonstrating the performance of quantitative NMR spectroscopy and further reducing measurement uncertainties. The development of validation concepts and the commercial availability of suitable certified reference materials facilitate the application, especially in the usually highly regulated industrial environment. Users can thus accelerate the development of analytical methods. The talk will cover a wide range of topics from current metrological activities to new challenges for qNMR spectroscopy and also deals with aspects such as validation and accreditation.
Innovative aspects
• qNMR provides the most universally applicable form of direct purity determination
• Expanded measurement uncertainties lower than 0.15 % (relative) possible
• Benchtop NMR instruments increasingly used for qNMR spectroscopy
During its 25 years of existence, the Inorganic Analysis Working Group of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology (CCQM IAWG) has achieved much in establishing comparability of measurement results. Impressive work has been done on comparison exercises related to real-world problems in fields such as ecology, food, or health. In more recent attempts, measurements and comparisons were focused on calibration solutions which are the basis of most inorganic chemical measurements. This contribution deals with the question of how to achieve full and transparent SI traceability for the values carried by such solutions. Within this framework, the use of classical primary methods (CPMs) is compared to the use of a primary difference method (PDM). PDM is a method with a dual character, namely a metrological method with a primary character, based on the bundling of many measurement methods for individual impurities, which lead to materials with certified content of the main component. As in classical methods, where small corrections for interferences are accepted, in PDM, many small corrections are bundled. In contrast to classical methods, the PDM is universally applicable to all elements in principle. Both approaches can be used to certify the purity (expressed as mass fraction of the main element) of a high-purity material. This is where the metrological need of National Metrology Institutes (NMIs) for analytical methods meet the challenges of analytical methods. In terms of methods, glow discharge mass spectrometry (GMDS) with sufficient uncertainties for sufficiently small impurity contents is particularly noteworthy for the certification of primary transfer standards (PTS), and isotope dilution mass spectrometry (IDMS), which particularly benefits from PTS (back-spikes) with small uncertainties, is particularly noteworthy for the application. The corresponding relative uncertainty which can be achieved using the PDM is very low (< 10−4). Acting as PTS, they represent the link between the material aspect of the primary calibration solutions and the immaterial world of the International System of Units (SI). The underlying concepts are discussed, the current status of implementation is summarised, and a roadmap of the necessary future activities in inorganic analytical chemistry is sketched. It has to be noted that smaller measurement uncertainties of the purity of high-purity materials not only have a positive effect on chemical measurements, but also trigger new developments and findings in other disciplines such as thermometry or materials science.
In den letzten Jahren erfreut sich die Benchtop-NMR-Spektroskopie steigender Beliebtheit. Zusätzlich zu Anwendungen im Labor werden die kompakten Geräte auch zunehmend in industriellen Bereichen eingesetzt. Neben geringeren Investitions- und Betriebskosten sind insbesondere die Robustheit und einfache Bedienbarkeit dieser Systeme entscheidende Faktoren. Ein prozessnaher Einsatz kann sowohl nach Probenahme im Rahmen der Betriebsanalytik erfolgen als auch als Online-Analytik mit direkter Ankopplung an Prozesse. Insbesondere bei der direkten Kopplung mittels Durchflusszellen spielt der Probentransfer eine entscheidende Rolle. Dies zeigt sich auch am Beispiel eines Extraktionsprozesses im Labormaßstab. Das in einem Bioprozess aus tierischen Altfetten hergestellte Copolymer PHB(Co-HHX) wurde in einem Batch-Prozess mit organischen Lösungsmitteln aus gefrier-getrockneten Zellen extrahiert. Unter Variation der Parameter wurde der Prozess direkt in der mehrphasigen Suspension mittels Benchtop-NMR-Spektroskopie verfolgt.
Eine große Limitierung für den Einsatz als Online-Methode ist die Temperaturempfindlichkeit der Magnetsysteme. Während die Umgebungstemperatur gut kontrollierbar ist, stellt sich die Thematik der Probentemperatur komplexer dar. Bei größeren Abweichungen von der Magnettemperatur kommt es bereits nach kurzer Zeit zu Drift-Effekten, die die Lock-Systeme nur begrenzt kompensieren können. Ein Ansatz ist die Nutzung temperierter Luftströme, ähnlich bekannter VT-Einheiten ergänzt um eine aktive Isolierung zum Magneten. An einem Modellaufbau wurden dazu verschiedene Konstruktionen zunächst mittels Thermographie charakterisiert und anschließend die Anwendbarkeit in einem Prototyp-Gerät überprüft.
In der rauen industriellen Umgebung von Produktionsanlagen sind weitere Maßnahmen zum Betrieb eines Laborgerätes nötig (z.B. Temperierung, Witterungsschutz). Zusätzlich bestehen häufig strikte Anforderungen an den Explosionsschutz. Zu diesem Zweck wurde gemeinsam mit der Evonik Rheinfelden eine Einhausung entwickelt, die es ermöglicht neben der NMR-Spektroskopie auch eine weitere analytische Methode möglichst flexibel direkt an großtechnische Anlagen anzubinden.
The European project MefHySto addresses the need of large-scale energy storage, which is required for a shift to renewable energy supply. The project is funded by the European Metrology Programme on Innovation and Research (EMPIR) and consists of 14 consortium partners from all over Europe (www.mefhysto.eu). It is demonstrated, how MefHySto is contributing to the EMN for Energy Gases aiming at prioritisation of the measurement gaps and challenges interacting with the EMN stakeholders.
In industrialised countries more than 80% of the time is spent indoors. Products, such as building materials and furniture, emit volatile organic compounds (VOCs), which are therefore ubiquitous in indoor air. Different VOC combinations may, under certain environmental and occupational conditions, result in reported sensory irritation and health complaints. A healthy indoor environment can be achieved by controlling the sources and by eliminating or limiting the release of harmful substances into the air. One way is to use materials proven to be low emitting. Meanwhile, a worldwide network of professional commercial and non-commercial laboratories performing emission tests for the evaluation of products for interior use has been established. Therefore, comparability and metrological traceability of test results must be ensured. A laboratory’s proficiency can be proven by internal and external validation measures that both include the application of suitable reference materials. The emission test chamber procedure according to EN 16516 comprises several steps from sample preparation to sampling of test chamber air and chromatographic analysis. Quality assurance and quality control (QA/QC) must therefore be ensured. Currently, there is a lack of suitable reference products containing components relevant for the health-related evaluation of building products.
The EU-funded EMPIR project 20NRM04 MetrIAQ (Metrology for the determination of emissions of dangerous substances from building materials into indoor air) aims to develop 1) gaseous primary reference materials (gPRM), which are used for the certification of gaseous (certified) reference materials (gCRM) and 2) emission reference materials (ERM).
Most commercial gas standards of indoor-relevant compounds are not certified due to the lack of primary reference materials to which the project aims to contribute. The gPRM under development is a gas-phase standard containing trace levels of VOCs in nitrogen or air from the check standard according to EN 16516 (n-hexane, methyl isobutyl ketone, toluene, butyl acetate, cyclohexanone, o-xylene, phenol, 1,3,5-trimethylbenzene) with a target uncertainty of 5 %. The gPRM can be sampled into sorbent tubes to obtain transfer standards in the form of gCRM.
The well characterised ERM represents a sample of a test specimen, e.g. building material, that is loaded into the emission test chamber for a period of several days and is used to evaluate the whole emission test chamber procedure. It shall have a reproducible and temporally constant compound release of less than 10 % variability over 14 days. Different approaches for retarded VOC release, such as the encapsulation of pure compounds and the impregnation of porous materials, are being tested to reach this aim. Furthermore, the design of the ERM is accompanied by the development of a numerical model for the prediction of the emissions for each of the target VOCs. The current progress of the work on both materials will be presented.
Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification
(2023)
Hydrolysis of protein samples into amino acids facilitates the use of NMR spectroscopy for protein and peptide quantification. Different conditions have been tested for quantifying aromatic amino acids and proteins. The pH-dependent signal shifts in the aromatic region of amino acid samples were examined. A pH of 12 was found to minimize signal overlap of the four aromatic amino acids. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, were applied as internal standards. The quantification of amino acids from an amino acid standard was performed. Using the first two suggested internal standards, recovery was ~97% for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98% ± 2% and 88% ± 4%, respectively, at a protein concentration of 16 g/L or 250 µM.
This study shows remarkably different features between the oxidation of secondary and primary C₃-C₅ alcohols. The oxidation of primary alcohols is controlled by the oxidative removal of blocking adsorbates, such as CO, formed after the dissociative adsorption of alcohol molecules. Conversely, secondary alcohols do not undergo dissociative adsorption and therefore their oxidation is purely controlled by the energetics of the elementary reaction steps. In this respect, a different role of ruthenium is revealed for the electrooxidation of primary and secondary alcohols on bimetallic platinum-ruthenium catalysts. Ruthenium enhances the oxidation of primary alcohols via the established bifunctional mechanism, in which the adsorption of (hydr)oxide species that are necessary to remove the blocking adsorbates is favored. In contrast, the oxidation of secondary alcohols is enhanced by the Ru-assisted stabilization of an O-bound intermediate that is involved in the potential-limiting step. This alternative pathway enables the oxidation of secondary alcohols close to the equilibrium potential.
Cryoadsorption on the inner surface of porous materials is a promising solution for safe, fast, and reversible hydrogen storage. Within the class of highly porous metal−organic frameworks, zeolitic imidazolate frameworks (ZIFs) show high thermal, chemical, and mechanical stability. In this study, we selected ZIF-8 synthesized mechanochemically by twin-screw extrusion as powder and pellets. The hydrogen storage capacity at 77 K and up to 100 bar has been analyzed in two laboratories applying three different measurement setups showing a high reproducibility. Pelletizing ZIF-8 increases the packing density close to the corresponding value for a single crystal without loss of porosity, resulting in an improved volumetric hydrogen storage capacity close to the upper limit for a single crystal. The high volumetric uptake combined with a low and constant heat of adsorption provides ca. 31 g of usable hydrogen per liter of pellet assuming a temperature−pressure swing adsorption process between 77 K − 100 bar and 117 K − 5 bar. Cycling experiments do not indicate any degradation in storage capacity. The excellent stability during preparation, handling, and operation of ZIF-8 pellets demonstrates its potential as a robust adsorbent material for technical application in pilot- and full-scale adsorption vessel prototypes.
Ratiometric green–red fluorescent nanosensors for fluorometrically monitoring pH in the acidic range were designed from 80 nm-sized polystyrene (PS) and silica (SiO2) nanoparticles (NPs), red emissive reference dyes, and a green emissive naphthalimide pH probe, analytically and spectroscopically characterized, and compared regarding their sensing performance in aqueous dispersion and in cellular uptake studies. Preparation of these optical probes, which are excitable by 405 nm laser or LED light sources, involved the encapsulation of the pH-inert red-fuorescent dye Nile Red (NR) in the core of self-made carboxylated PSNPs by a simple swelling procedure and the fabrication of rhodamine B (RhB)-stained SiO2-NPs from a silane derivative of pH-insensitive RhB. Subsequently, the custom-made naphthalimide pH probe, that utilizes a protonation-controlled photoinduced electron transfer process, was covalently attached to the carboxylic acid groups at the surface of both types of NPs. Fluorescence microscopy studies with the molecular and nanoscale optical probes and A549 lung cancer cells confirmed the cellular uptake of all probes and their penetration into acidic cell compartments, i.e., the lysosomes, indicated by the switching ON of the green naphthalimide fluorescence. This underlines their suitability for intracellular pH sensing, with the SiO2-based nanosensor revealing the best performance regarding uptake speed and stability.
Process analytical technology (PAT) is a cross-sectional technology and thus essential for future smart production. While in the past decades, the focus of process optimization strategies was on increasing efficiency, in the future, the focus will be on the sustainability of a production and its products. In addition, products will be increasingly personalized in order to match the property profile exactly to the intended use. PAT is able to provide context-sensitive information at the molecular level for process control. Spectroscopic sensors can determine inline and simultaneously both the chemical composition and its sub-microscopic morphology. The article will focus on the optical spectroscopy and therefore starts with a brief introduction on the basic concepts of molecular spectroscopy. In addition, the particularities of measuring liquids, surfaces, or particulate systems in PAT applications are described. This should enable the reader to select the appropriate method for the specific problem. Many examples from everyday industrial practice illustrate the applications. The areas covered are the manufacturing industry, process and pharmaceutical industry, food industry, as well as biotechnology and medical technology. Future will show that PAT is especially important for applications in the field of medicine (point of care) circular economy (recycling, water–wastewater, etc.). It is important to emphasize that sustainability in industrial production can only be successful with an inter- and transdisciplinary close exchange between the different disciplines.
EN 16516 sets specifications for the determination of emissions into indoor air from construction products. Reliable, accurate and International System of Unit (SI)-traceable measurement results of the emissions are the key to consumer protection. Such measurement results can be obtained by using metrologically traceable reference materials. Gas-phase standards of volatile organic compounds (VOCs) in air can be prepared by a variety of dynamic methods according to the ISO 6145 series. However, these methods are not always applicable for semi-VOCs (SVOCs) due to their high boiling point and low vapour pressure. Therefore, a novel dynamic gas mixture generation system has been developed. With this system gas-phase standards with trace level VOCs and SVOCs in air can be prepared between 10 nmol mol−1 and 1000 nmol mol−1. The VOCs and SVOCs in this study have normal boiling points ranging from 146 °C to 343 °C. Metrologically traceable reference materials of the gas-phase standard were obtained by sampling of the VOC gas-phase standard into Tenax TA® sorbent material in SilcoNert® coated stainless steel tubes. Accurately known masses between 10 ng and 1000 ng per VOC were sampled. These reference materials were used to validate the dynamic system. Furthermore, the storage and stability periods of the VOCs in the reference materials were determined as these are crucial characteristics to obtain accurate and SI-traceable reference materials. In a round robin test (RRT), the reference materials were used with the aim of demonstrating the feasibility of providing SI-traceable standard reference values for SVOCs for interlaboratory comparison purposes. Based on the results from the validation, the storage and stability studies and the RRT, gas-phase standards and reference materials of VOCs and SVOCs with relative expanded uncertainties between 5% and 12% (k = 2) have been developed. These reference standards can be used as calibrants, reference materials or quality control materials for the analysis of VOC emissions.
Climate change and related energy policies, exacerbated by unforeseen geopolitical developments, pose new challenges for gas analytics, such as the use of hydrogen, hydrogen-containing alternative gaseous fuels (NH3, etc.), the use of alternative methane-based energy gases (LNG, LPG, etc.) or decarbonisation via CCSU. In all topics, the quality, i.e. the actual chemical composition of the gases, naturally plays a decisive role. BAM is meeting this strategic importance with the further development of hydrogen analytics and is continuing to develop the methods used in order to support the German economy and research landscape with traceability, reference materials and analytical procedures as quickly as possible.
Mass spectrometry plays an important role for trace analysis in hydrogen matrix. The presentation shows first experimental results from the application of PTR-TOF-MS (Proton Transfer Reaction Time-of-Flight Mass Spectrometry).
Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification
(2022)
qNMR is a valuable technique for metrological studies due to the uniformity of its signal response for all chemical species of an isotope of interest, which enables compound-independent calibration. However, protein quantification remained challenging as large molecules produce wide, low-intensity signals that reduce the already low sensitivity. Combining qNMR with the hydrolysis of protein samples into amino acids circumvents many of these issues and facilitates the use of NMR spectroscopy for absolute protein and peptide quantification.In this work, different conditions have been tested for quantifying aromatic amino acids and proteins. First, we examined the pH-based signal shifts in the aromatic region. The preferable pH depends on the selection of the amino acids for quantification and which internal standard substance should be used to avoid peak overlap. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, have been applied as internal standards. The quantification of amino acids from an amino acid standard, as well as from a certified reference material (bovine serum albumin), was performed. Using the first two suggested internal standards, recovery was ~ 97 % for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98 ± 2 and 88 ± 4 %, respectively, at a protein concentration of 16 g/L or 250 µM.
Im Rahmen von der BAM und anderen Partnern ins Leben gerufene Initiative „Digitale Qualitätsinfrastruktur“ ist der Fokus auf die Entwicklung von neuen Regelwerken und Zertifizierungsworkflows ausgerichtet. Dabei ist eine besondere Bedeutung dem Zusammenführen von Operational Technology (OT) und Informationstechnik (IT) beizumessen, wenn aktuelle Prozess- und Parameterdaten
zuverlässig zur Verfügung gestellt werden sollen. In dem Use Case Wasserstofftankstelle werden digitale Abbilder erprobt, die u.a. der Kalibrierung von Sensoren, dem Nachweis über die Wasserstoffreinheit und der vorausschauenden Wartung dienen sollen.
Großenteils der verfahrenstechnischen Bestandsanlagen, die sogenannten Brownfield-Anlagen, sind nach einem konservativen und hierarchischen Automatisierungskonzept ausgelegt. Hierbei können sämtliche Prozessdaten,
besonders aus der Feldebene, einer oberen informationstechnische Ebene
unzugänglich bleiben. Eine Brückentechnologie nach der NAMUR Open Architecture (NOA) soll möglichst viele Informationen und Daten aus der vorgegebenen Brownfield-Automatisierung sicher und rückwirkungsfrei zur
Verfügung stellen. Zusätzliche Sensorik soll ebenso zu der Datenerweiterung beitragen und letztendlich den digitalen Zwilling, bzw. das digitale Abbild des verfahrenstechnischen Prozesses, ergänzen.
Die Herausforderungen einer solchen Infrastruktur gelten vor allem einer universellen
Kommunikationsschnittstelle und der Sicherheit. Darüber hinaus werden vorgeschlagene Normen und Empfehlungen untersucht und erprobt.
Unternehmen der Prozessindustrie müssen neue Wege finden, um in einem sich wandelnden Umfeld erfolgreich zu überleben, und gleichzeitig flexiblere Wege der Produkt- und Prozessentwicklung finden, um ihre Produkte schneller auf den Markt zu bringen – insbesondere hochwertige, hochwertige Produkte wie Feinchemikalien oder Arzneimittel. Dies wird zukünftig durch Veränderungen in den Wertschöpfungsketten entlang einer potenziellen Kreislaufwirtschaft erschwert.
Anhand von Beispielen wird in diesem Vortrag ein möglicher ganzheitlicher Ansatz zur Digitalisierung und zum Einsatz maschineller Verfahren in der Produktion von Spezialchemikalien durch die Einführung integrierter und vernetzter Systeme und Prozesse skizziert.
Es wird auch auf die aktuelle Technologie-Roadmap „Prozess-Sensoren 2027+“ eingegangen, die Ende 2021 erschienen ist. Im Zentrum dieser Roadmaps stehen Sensoren zur Erfassung von physikalischen und chemischen Messgrößen mittels spezifischer und unspezifischer Messverfahren, die zur Steuerung und dem besseren Verständnis von Prozessen dienen. Die Roadmap fasst die gemeinsame Technologie- und Marktsicht von Anwendern, Herstellern und Forschungs¬einrichtungen im Bereich Prozess-Sensorik in der verfahrenstechnischen Industrie zusammen. Digitalisierung und Nachhaltigkeit sind übergreifende Kernthemen der künftigen Entwicklung.
Die BAM setzt in ihren analytischen Labors zunehmend Labor-Robotik ein, um gefähliche oder zeitraubende Routineaufgaben zu automatisieren. Durch Automation kann auch die Reproduzierbarkeit solcher Anwendungen erhöht werden.
Im Beitrag werden einige aktuelle Beispiele aus den Analytiklabors diskutiert, wie z. B. die Anwendung für die Herstellung und RFA-Analytik von Gläsern, eine Feinwäge-Robotik für 10-L-Gaszylinder im Rahmen der Herstellung von Primärnormalen oder die Automatisierung von Probenpräsentationen für optische Spektroskopie und chemical Imaging. Auch wird kurz auf den Einsatz von Speicherprogrammierbaren Steuerungen in der modularen Laborautomation und die Virtualisierung von analytischen Laborrechnern eingengangen.
Integrierte und vernetzte Systeme und Prozesse – Eine Perspektive für die smarte Laborinfrastruktur
(2022)
Chemie- und Pharmaunternehmen müssen neue Wege gehen, um in einem sich wandelnden Umfeld erfolgreich zu überleben, und gleichzeitig flexiblere Wege der Produkt- und Prozessentwicklung finden, um ihre Produkte schneller auf den Markt zu bringen - vor allem hochwertige High-End-Produkte wie Feinchemikalien oder Arzneimittel. Dazu gehört auch das Potenzial der digitalen Technologien, um ein umfassenderes Wissensmanagement zu ermöglichen.
Eine wichtige Wissensquelle sind analytische Labors, die Unternehmensweit aktiv sind – von F&E bis zur Produktion. Die ganzheitliche Einbindung von analytischen Labors und ein unternehmensweites Daten- und Wissensmanagement sind wichtige Bausteine zur Integration und Vernetzung aller Systeme und Prozesse. Das Potenzial von Daten aus der Produktion mit ihren Kontextinformationen wird heute oft noch nicht konsequent für ein umfassendes Verständnis der Produktion genutzt.
Dieser Beitrag skizziert anhand von Beispielen einen möglichen ganzheitlicheren Ansatz zur Digitalisierung und zum Einsatz maschineller Verfahren in der Produktion von Spezialchemikalien und Pharmazeutika durch die Einführung integrierter und vernetzter Systeme und Prozesse.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Companies of chemical industry find themselves more often in a rapidly changing environment, e.g., due to variability of raw material quality or energy costs and efficiency. Process optimization and new process concepts become more and more important. For example, flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds like exothermic reactions with high heat dissipation.
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. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis approach, which can even serve as reliable reference method for further calibration-dependent PAT applications (e.g., NIR spectroscopy). Based on experiences from these field studies an improved analyzer enclosure setup was developed and built, including the option of a secondary method besides NMR spectroscopy. Integrated control systems allow for a flexible implementation based on the available automation infrastructure at the chemical plant or pilot plant setup. In the future, fully integrated and intelligently interconnecting “smart” PAT systems and processes have the potential speed up the setup of production equipment for chemicals and pharmaceuticals and therefore help to reduce the time-to-market.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
At the end of the article, ideas for solutions are discussed in order to speed up the implementation of new special products from the point of view of process analytics and to network the existing process chains more closely.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further Process Analytical Technology (PAT) applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated. Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
Modular production involving benchtop NMR Current Application Examples Driven by Digitalization
(2022)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
Modular production involving benchtop NMR Current Application Examples Driven by Digitalization
(2022)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI, ENPRO, or MTP naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Chemical companies must find new paths to successfully survive in a changing environment, especially by utilizing the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products.
Therefore, fully automated process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. It was used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plants show promising results gaining process knowledge. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, fully integrated and interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Compact NMR Spectroscopy in the field: A Versatile PAT Tool for Production of Specialty Chemicals
(2022)
Chemical companies must find new paths to successfully survive in a changing environment, especially by utilizing the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products.
Therefore, fully automated process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of chemical production environment such as explosion safety, field communication, and robust evaluation of sensor data. It was used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plants show promising results gaining process knowledge. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, fully integrated and interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Chemical and pharmaceutical companies need to find new ways to survive successfully in a changing environment, while finding more flexible ways of product and process development to bring their products to market faster - especially high-value, high-end products such as fine chemicals or pharmaceuticals. This is complicated by changes in value chains along a potential circular economy.
One current approach is flexible and modular chemical production units that use multi-purpose equipment to produce various high-value products with short downtimes between campaigns and can shorten time-to-market for new products. Online NMR spectroscopy will play an important role for plant automation and quality control, as the method brings very high linearity, matrix independence and thus works almost calibration-free. Moreover, these properties ideally enable automated and machine-aided data analysis for the above-mentioned applications.
Using examples, this presentation will outline a possible more holistic approach to digitalization and the use of machine-based processes in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
Das europäische Projekt MefHySto befasst sich mit dem Bedarf an großmaßstäblichen Energiespeichern, die für eine Umstellung der Energieversorgung auf erneuerbare Energien erforderlich sind. Eine solche Speicherung ist entscheidend, um Energie zu Spitzenzeiten zu liefern, wenn die erneuerbaren Energiequellen schwanken. Eine mögliche Lösung für die Energiespeicherung ist der großtechnische Einsatz von Wasserstoff. Die messtechnische Rückführbarkeit in der Energieinfrastruktur für die Wasserstoffspeicherung ist dann von entscheidender Bedeutung und eine bessere Kenntnis der chemischen und physikalischen Eigenschaften von Wasserstoff sowie rückführbare Messungen und validierte Techniken unverzichtbar.
Im Rahmen des EU-Projekts „CONSENS – Integrated Control and Sensing“ wurde ein vollautomatisiertes, gemäß Atmosphère-Explosibles(ATEX)-Regeln zertifiziertes Analysatormodul auf Basis eines kommerziellen Benchtop-Kernspinresonanzspektrometers (Engl. nuclear magnetic resonance, NMR) entwickelt und im Umfeld einer modularen containerbasierten Produktionsanlage validiert. Auf Basis der gewonnenen Daten konnten sowohl eine iterative Optimierung der Prozessparameter erfolgen als auch Referenzdaten für die Kalibrierung eines Nahinfrarot-Spektrometers gewonnen werden.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and highthroughput mass quantification of microplastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermoanalytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg.
The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most
compact NIR spectrometers available.
Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous-Flow Production
(2022)
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 downtimes 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. 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. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
For more than 110 years, BAM has been producing reference materials for a wide range of application fields. With the development of new analytical methods and new applications as well as continuously emerging more stringent requirements of laboratory accreditation with regard to quality control and metrological traceability, the demand and requirements for reference materials are increasing. This trend article gives an overview of general developments in the field of reference materials as well as developments in selected fields of application in which BAM is active. This includes inorganic and metal analysis, gas analysis, food and consumer products, and geological samples. In addition to these more traditional fields of application, developments in the areas of optical spectroscopy, particulary fluorescence methods, and nanomaterials are considered.
Changes in the global bulk and local structures, of three different barium compounds (BaZrO3, BaF2, and BaFCl),were induced by mechanical milling and followed using X-ray powder diffraction (PXRD), subsequent microstructure analysis, and 137Ba solid state NMR spectroscopy. Harder materials like BaZrO3 experience significantly higher structural changes upon milling than softer materials like BaF2. Moreover, soft materials with layered structures, like BaFCl, show a pronounced structural change during the milling process. By combining PXRD and solid state NMR, detailed information on the changes to the global and local structures were obtained, which are of interest for mechanochemical synthesis, mechanically treated catalysts or ionic conductors.
Formation Mechanism of a Nano-Ring of Bismuth Cations and Mono-Lacunary Keggin-Type Phosphomolybdate
(2022)
A new hetero-bimetallic polyoxometalate (POM) nano-ring was synthesized in a one-pot procedure. The structure consists of tetrameric units containing four bismuth-substituted monolacunary Keggin anions including distorted [BiO8] cubes. The nano-ring is formed via self-assembly from metal precursors in aqueous acidic medium. The compound (NH4)16[(BiPMo11O39)4] ⋅ 22 H2O; (P4Bi4Mo44) was characterized by single-crystal X-ray diffraction, extended X-ray absorption fine structure spectroscopy (EXAFS), Raman spectroscopy, matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI-TOF), and thermogravimetry/differential scanning calorimetry mass spectrometry (TG-DSC-MS). The formation of the nano-ring in solution was studied by time-resolved in situ small- and wide-angle X-ray scattering (SAXS/WAXS) and in situ EXAFS measurements at the Mo−K and the Bi−L3 edge indicating a two-step process consisting of condensation of Mo-anions and formation of Bi−Mo-units followed by a rapid self-assembly to yield the final tetrameric ring structure.
Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and high-throughput mass quantification of micro¬plastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermo-analytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg. The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most compact NIR spectrometers available.
The prerequisites for a successful energy transition and the economic use of hydrogen as a clean green energy carrier and for H2 readiness are a rapid market ramp-up and the establishment of the required value chains. Reliable quality and safety standards for innovative technologies are the prerequisite for ensuring supply security, for environmental compatibility and sustainable climate protection, for building trust in these technologies and thus enable product and process innovations.
With the Competence Centre "H2Safety@BAM", BAM is creating the safety-related prere-quisites for the successful implementation of hydrogen technologies at national as well as European level. BAM uses decades of experience in dealing with hydrogen technologies to develop the necessary quality and safety standards.
The presentation will draw a bow from the typical basic tasks of BAM in the field of competence "Sensors, analytics and certified reference materials", such as maintenance and dissemination of the national gas composition standards for calorific value determination as Designated Institute for Metrology in Chemistry within the framework of the Metre Convention, to the further development of measurement and sensor technology for these tasks. For the certification of reference materials, a mostly slow and time-consuming but solid reference analysis is common. With hydrogen and its special properties, completely new requirements are added. In addition, fast and simple online analysis is required for process control, for example to register quality changes, e.g., during load changes or refuelling processes.
Der AK 3.7 ist ein "erweiterter" AK und je zur Hälfte mit NAMUR-Vertretern und Vertretern der Geräte- und Softwarehersteller besetzt. Er wurde ins Leben gerufen, um Begrifflichkeiten der digitalen Transformation aufzugreifen, wie etwa Smarte Sensorik, Sensordatenfusion, Schwarmsensorik oder Softsensorik. Eine erste Aufgabe bestand darin, einige exemplarische Anwendungsfälle der Nutzung smarter Eigenschaften von Feldgeräten sowie deren zukünftige Kommunikationsmöglichkeiten sowohl mit Bezug auf Bestandsanlagen als auch mit Blick auf einen potentiellen Technologiewechsel zu betrachten. Neuer Scope des AK 3.7 ist eine "Next Generation Automation" um einen potentiellen Technologiewechsel rechtzeitig vorauszudenken. Dieses erfolgt unter vollständiger gedanklicher Trennung von heutiger Automatisierung und auch vom NOA-Konzept.
Ebenso wird ein Technologiewechsel in der Produktion der Prozessindustrie (wahrscheinlich modulbasiert) postuliert. Ziel des AK 3.7 wird es in Zukunft sein, diese Anforderungen an smarte Feldgeräte aufzugreifen und gemeinsam mit den thematisch überlappenden Interessenskreisen in Standards zu übersetzen.
Storage is still limiting the implementation of hydrogen as an energy carrier to integrate the intermittent operation of renewable energy sources. Among different solutions to the currently used compressed or liquified hydrogen systems, physical adsorption at cryogenic temperature in porous materials is an attractive alternative due to its fast and reversible operation and the resulting reduction in storage pressure. The feasibility of cryoadsorption for hydrogen storage depends mainly on the performance of the used materials for the specific application, where metal-organic frameworks or MOFs are remarkable candidates. In this work, gravimetric and volumetric hydrogen uptakes at 77 K and up to 100 bar of commercially available MOFs were measured since these materials are made from relatively cheap and accessible building blocks. These materials also show relatively high porous properties and are currently near to large-scale production. The measuring device was calibrated at different room temperatures to calculate an average correction factor and standard deviation so that the correction deviation is included in the measurement error for better comparability with different measurements. The influence of measurement conditions was also studied, concluding that the available adsorbing area of material and the occupied volume of the sample are the most critical factors for a reproducible measurement, apart from the samples’ preparation before measurement. Finally, the actual volumetric storage density of the used powders was calculated by directly measuring their volume in the analysis cell, comparing that value with the maximum volumetric uptake considering the measured density of crystals. From this selection of commercial MOFs, the materials HKUST-1, PCN-250(Fe), MOF-177, and MOF-5 show true potential to fulfill a volumetric requirement of 40 g·L−1 on a material basis for hydrogen storage systems without further packing of the powders.
The CCQM-K148.a comparison was coordinated by the BIPM on behalf of the CCQM Organic Analysis Working Group for NMIs and DIs which provide measurement services in organic analysis under the CIPM MRA. It was undertaken as a "Track A" comparison within the OAWG strategic plan. CCQM-K148.a demonstrates capabilities for assigning the mass fraction content of a solid organic compound having moderate molecular complexity, where the compound has a molar mass in the range (75 - 500) g/mol and is non-polar (pKow < −2), when present as the primary organic component in a neat organic solid and where the mass fraction content of the primary component in the material is in excess of 950 mg/g.
Participants were required to report the mass fraction of Bisphenol A present in one supplied unit of the comparison material. Participants using a mass balance method for the assignment were also required to report their assignments of the impurity components present in the material. Methods used by the seventeen participating NMIs or DIs were predominantly based on either stand-alone mass balance (summation of impurities) or qNMR approaches, or the combination of data obtained using both methods. The results obtained using thermal methods based on freezing-point depression methods were also reported by a limited number of participants. There was excellent agreement between assignments obtained using all three approaches to assign the BPA content.
The assignment of the values for the mass fraction content of BPA consistent with the KCRV was achieved by most of the comparison participants with an associated relative standard uncertainty in the assigned value in the range (0.1 - 0.5)%.
Intelligent sensor systems, certified reference materials and instrumental analytical-chemical methods contribute to safety and functionality in hydrogen technologies.
This article gives a brief overview of SensRef activities in the Competence Centre H2Safety@BAM on the issues: Analytical methods for the determination of hydrogen purity, certified reference materials as measurement standards with regard to gas quality (primary calibrators) of BAM, test methods for gas sensor systems to detect hydrogen in air as well as the application of fibre-optic sensor systems to monitor the expansion and ageing behaviour of composite containers in hydrogen technologies.
Der Vortrag zum Mess- und Prüfverfahren mit verschiedenen Sensortechnologien und Ultraschallwellen beinhaltet die Themen:
Metrologie zur Wasserstoffspeicherung - Euramet-Vorhaben "MefHySto",
Erkennung von freigesetztem Wasserstoff sowie die Bestimmung des Wasserstoff-Luftverhälntisses mit Gassensoren, zerstörungsfreie Fehlstellenerkennung mit integriertem Zustandsüberwachungssystem basierend auf geführten Ultraschallwellen zur Lebensdauerüberwachung von Composite-Behältern (Wasserstoffspeicher) sowie faseroptische Sensorik zur Schadenfrüherkennung von Wasserstoffspeichern aufgrund erkennbarer Dehnungsänderungen an Druckbehältern.
Rückgebaute Mineralwolledämmstoffe und Baustellenverschnitte werden in der Regel deponiert und damit als Rohstoffe dem Markt entzogen. Ziel dieses Projektes ist es darzulegen, dass das Recycling von Glas- und Steinwolle im großmaßstäblich volumenrelevanten Umfang für das Schmelzwannenverfahren technisch umsetzbar und ökonomisch und ökologisch vorteilhaft ist. Neben verfahrenstechnischen Herausforderungen, gilt es die wirtschaftliche in-situ-Identifikation unbekannter Mineralwolle zu ermöglichen. Dazu wird auf erste erfolgversprechende Tastversuche mit spektroskopischen Methoden weiter aufgebaut.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are valuable analytical and quality control methods for most industrial chemical processes as they provide information on the concentrations of individual compounds and by-products. These processes are traditionally carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been realized to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra, to train an ANN with better prediction performance and speed than state-of-the-art analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
The demand for increasing product diversity in the chemical process industry calls for new production processes that enable greater flexibility. Therefore, plants are needed that produce significant quantities for market supply that can be scaled up to several tons per year. Compared to traditional batch processes, intensified continuous production enables not only flexibility but also the production of compounds that are difficult to produce. Custom-designed small-scale reactors significantly improve heat and mass transfer through micro mixing and can improve safety, e.g. in the case of high grade exothermic or high-pressure reactions, and might play an important role for customized, modular production facilities.1 Combined with optimally designed flow cells, compact NMR instruments currently present promising analytical tools for use in flow chemistry applications.2,3 In recent process monitoring applications, the flow cell and the mixing unit are usually separated parts leading to a severe time delay between mixing and first data acquisition.
In this work, we present a comprehensive workflow for the design of a flow cell−mixer combination based on CFD simulation and other design principles.4 Due to the increasing opportunities in additive manufacturing of ceramics, it was possible to realize an optimized SMX-type mixer with a fully integrated NMR flow cell (cf. Fig. 1).
Validation studies exhibited 1H NMR spectra with a quality comparable to common NMR glass tubes. So far, the mixing performance of the system has been evaluated for different mass flow rates within the intended working range of 5–120 seconds region and compared to ideally mixed samples. Thus, the integrated flow cell−static mixer combination can be used for different purposes such as evaluation of fluid properties, equilibration studies, or reaction monitoring of two instantaneously mixed samples.
The ceramic flow cell was additively manufactured and analyzed through x-ray microtomography revealing surface characteristics due to the manufacturing process (cf. Fig. 2). Furthermore, the working range of the whole system was characterized leading to an operational specification for further applications.
In summary, the role of custom-designed components for modular, chemical production, amongst other essential factors like fast development of reliable evaluation models is discussed.
References
[1] Bornemann-Pfeiffer et al., Chem. Ing. Tech. (2021), 93: 1–10
[2] Kern et al., Anal. Bioanal. Chem. (2018) 410: 3349–3360
[3] Kern et al., Anal. Bioanal. Chem. (2019) 411: 3037–3046
[4] Bornemann et al., Ind. Eng. Chem. Res. (2019), 58: 19562−19570
Modular production involving Benchtop NMR: Current application examples driven by digitalization
(2021)
The demand for increasing product diversity in the chemical and pharmaceutical industry calls for new production processes that enable greater flexibility. Therefore, plants are needed which can be adapted to new processes in a fast manner and be scaled up and down easily to volatile market demands. Modular production techniques in combination with advanced process analytical technology (PAT) are considered as a promising solution able to fulfil these requirements.
The success and acceptance of modular concepts in both new and existing plants is dependent of its reliability, easy applicability, and standardization. In recent past, enormous efforts were made to overcome existing barriers in a superordinate level, e.g. DEXPI [1], ENPRO [2], or MTP [3] naming just a few. Here, we’d like to present a few, more hands-on, application examples which are shown in Figure 1 aiming to increase process flexibility and applicability.
This includes:
a) The development of an additively manufactured mixer—flow reactor combination for the application inside of NMR instruments. [4]
b) The application of automated, model-based approaches for model development and spectra evaluation.
c) The application of machine-assisted spectral model building as a genuine alternative to classical model-based approaches [5]
d) Improvement of NIR calibration through online available NMR reference data. [6]
These examples represent miscellaneous use cases but result of the same fact: the increased use and availability of data through advanced PAT and therefore new opportunities utilizing them.
Industrial Applications of Low-Field NMR Spectroscopy for Process and Quality Control of Silanes
(2021)
The combination of different silanes as starting materials and as a product of hydrolysis by several alcohols or water creates a range of hundreds of technical products for a wide range of applications. In recent years, functional trialkoxysilanes have proven to be multi-purpose organosilanes. Applications range from weather protection of buildings to bonding-imparting properties in the glass fiber industry, for sealants and adhesives, for coatings and paints to the modification of polymer materials.
Commercial benchtop NMR spectrometers have the potential to be used in silane chemistry as an online method for reaction monitoring and quality control [1]. Interesting NMR nuclei for the above-mentioned products are 1H and 29Si. In a joint research cooperation between EVONIK and BAM, the applicability of low-field NMR spectroscopy for the chemical analysis of silanes was evaluated based on various case studies. In the course of the case studies it was shown how low-field NMR spectroscopy extends the application range of chemical analysis to new applications where existing technologies such as NIR, Raman, UV/VIS, etc. cannot be used quantitatively due to lack of reference data.
Chemical companies must find new paths to stay productive in a rapidly changing environment. One of these is the potential of digital technologies. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market. Process safety is improved due to smaller amounts processed and the abilities of efficient heat-transfer allow for otherwise difficult-to-produce compounds.
To exploit these advantages, a fully automated process control along with real-time quality control is mandatory and should be based on “chemical” information. The advances of a fully automated NMR analyzer were demonstrated, using a given pharmaceutical reaction step operated within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the requirements of an automated chemical production environment such as explosion safety, field communication, and robust data evaluation. Obtained results were used for direct loop advanced process control and real-time optimization of the process.
NMR spectroscopy appeared as excellent online analytical tool and allowed a modular data analysis approach, which even served as reliable reference method for further PAT applications. Using the available datasets, a second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously. In future, such fully integrated and interconnecting “smart” systems and processes can increase the efficiency of the production of specialty chemicals and pharmaceuticals.
Raman spectroscopy for online monitoring of a homogeneous hydroformylation process in microemulsion
(2021)
An important industrial reaction is hydro¬formylation for the production of aldehydes from alkenes and syngas on the basis of homogeneous catalysis. The main cost factors of the processes currently used are product selectivity and the loss of the catalysts used. Therefore, various concepts for the hydroformylation of long-chain olefins have been developed, including hydroformylation in microemulsions, which is being investigated on a mini-plant scale at the Technical University of Berlin [1]. In this study, online Raman spectroscopy of the reaction of 1-dodecene to 1-tri¬decanal in a microemulsion was performed [2]. First, an experimental design was used to obtain a good representation of the operating range in the mini plant with respect to the concentrations of five reactants in a laboratory setup [3]. Based on the Raman spectra, Partial Least Squares (PLS) models for the prediction of 1-dodecene and 1-tride-decanal were calibrated and with these the reactions were predicted on a laboratory scale. In the next step, the PLS models were applied to online spectra from a mini-plant. This resulted in promising estimates of 1-tridecanal and acceptable predictions of 1-dodecene mass fractions. The predictive power of PLS models in this particular case was limited by unexpected by-product formation which, however, can easily be compensated by an extended calibration. Hence, Raman spectroscopy is a promising technique for process analysis in microemulsions.
Companies in the chemical industry have to tread new paths in order to survive successfully in a changed environment. This includes, in particular, the potential of digital technologies. The full integration and intelligent networking of systems and processes is making slow progress.
This talk is a tribute to the field level. It wants to encourage a more holistic approach to the digitalisation of the process industry based on smart sensors, actuators and communication and provides information on current technical perspectives, such as the "one-network paradigm", ad-hoc networking, edge computing, FPGAs, virtual machines or blockchain. These give smart sensors, actuators and communication a completely new perspective.
Die Technologie-Roadmap „Prozess-Sensoren 2027+“ ist eine Weiterentwicklung vorgängiger Technologie-Roadmaps. Im Zentrum dieser Roadmaps stehen Sensoren zur Erfassung von physikalischen und chemischen Messgrößen mittels spezifischer und unspezifischer Messverfahren, die zur Steuerung und dem besseren Verständnis von Prozessen dienen.
Die Roadmap fasst die gemeinsame Technologie- und Marktsicht von Anwendern, Herstellern und Forschungseinrichtungen im Bereich Prozess-Sensorik in der verfahrenstechnischen Industrie zusammen. Sie beschreibt die wesentlichen Trends im Bereich Prozess-Sensorik und künftige Handlungsbedarfe für Hersteller, Anwender sowie für Einrichtungen der Forschung und Lehre.
Für die aktuellen und zukünftigen Anforderungen an Prozess-Sensoren werden 19 Thesen formuliert. Die Thesen basieren auf den Thesen der vorangegangenen Roadmaps, wobei die aus heutiger Sicht erforderlichen Anpassungen, Ergänzungen und teilweise auch Streichungen vorgenommen wurden. Die Thesen sind in 5 Themencluster eingeordnet. Digitalisierung und Nachhaltigkeit sind übergreifende Kernthemen der künftigen Entwicklung.
OPC-UA für Prozessindustrie und Laborwelt - Offener Standard für die störungsfreie Kommuniktaion
(2021)
Im privaten Umfeld machen wir uns keine Gedanken mehr über die Einbindung von elektronischen Geräten in Netzwerke, sei es bei der Verbindung des Mobiltelephons mit dem W-Lan-Netzwerk des Hotels oder von Freunden oder des drahtlosen Kopfhörers mit dem Notebook: Wir erwarten, dass es auf Anhieb funktioniert. Dahinter stecken offene Standards für die Konnektivität.
Dafür braucht man immer zwei Dinge: Einen physischen Kommunikationskanal, auf dem die Datenpakete zwischen den Komponenten und Geräten hin- und herwandern und eine einheitliche Kommunikationssprache, so dass sich die Komponenten und Geräte auch untereinander verstehen, weil sie dieselbe Sprache sprechen und automatisch wissen, was sie miteinander zu besprechen haben. Wenn man eine sichere Konnektivität bevorzugt, werden weitere Informationen benötigt, wie etwa ein Passwort.
Auch für die störungsfreie Kommunikation aller Automatisierungskomponenten der Prozessindustrie untereinander oder etwa für die Kommunikation von Geräten in einem analytischen Labor wird ein einheitliches Protokoll (Kommunikationssprache) und ein einheitlicher Feldbus (Kommunikationskanal) benötigt. Mittlerweile gilt der Standard OPC Unified Architecture (OPC-UA) für das Erstere als gesetzt und kann als ein kleiner Triumph von Industrie 4.0 betrachtet werden. OPC-UA kann auf verschiedenen Kommunikationskanälen laufen – am liebsten solchen, die eine angemessene Bandbreite oder Datenrate haben. Was den dazu notwendigen physischen Kommunikationskanal betrifft, findet man aus verschiedenen Gründen einen sehr spezialisierten und historisch über Jahrzehnte gewachsenen Lebensraum vor, der Operational Technology (OT) genannt wird. Zumeist findet man Zwei- und Vierdraht-Techniken mit Strom- und Spannungs-Signalübertragung, zum Beispiel mit 4–20 mA. Kommunikationsstandards wie eingangs erwähnt, wie Ethernet oder W-Lan sind absolut die Seltenheit. Dieses wird für die sogenannte Informationstechnik (Information Technology, IT) eingesetzt und ist aus Sicherheitsgründen heute komplett von der OT getrennt.
Auch wenn es der OT nicht gefällt, wachsen die beiden Welten IT und OT aber stetig weiter zusammen, da die IT bereits viele funktionierende und preislich attraktive Lösungen bereithält. Die vermeintliche Sicherheit, Verfügbarkeit und Echtzeitfähigkeit der klassischen OT, aber auch ihre Komplexität müssen im Zuge der Digitalen Transformation nun sorgfältig abgewogen werden.
Gas adsorption is based on physical properties between gases and solid materials, enriching the surface with packed gas molecules with a higher density than in the bulk phase. For using this mechanism as a gas storage strategy, highly porous materials are necessary since large surfaces in small volumes can provide the storage system with a higher density than the gas phase. In the case of hydrogen gas, the interaction forces with solid surfaces are generally low at room temperature but can increase considerably at low operating temperatures. As a counterpart, the storage pressure is considerably lower than that necessary by traditional gas compression.
Amongst ultra-porous adsorbent materials for hydrogen cryoadsorption, metal-organic frameworks (MOFs) are a group of remarkable solids made from metallic nodes linked by organic molecules exhibiting a wide variety of composition, geometry, porous properties, and chemical functionality. The scientific community focused in the last years on enhancing both the specific area of materials and the interaction energy to extend the storage properties of cryoadsorption to ambient-temperature and use it as hydrogen storage mechanisms in vehicles. However, the found difficulty in achieving ultra-porous structures with high-enough interaction energies decreased this research interest in the last years.
However, for a stationary application like hydrogen refueling stations, where space and weight are not such limits as in vehicles, cryoadsorption can still be considered a feasible candidate for hydrogen storage. Cryoadsorption is the only fast and fully reversible approach to store hydrogen at similar density values as compressed gas. Cryogenic operation is a technological challenge, but first, liquid nitrogen is cheap, and second, it is less energy-demanding than hydrogen liquefaction, which is indeed considered as feasible for transportation and storage. Cryoadsorption involves lower pressure
than compressed gas, increasing safety in the storage facilities, but additional research on the construction materials properties is necessary to better understand their behavior in contact with hydrogen at cryogenic temperatures. However, the knowledge of all these mechanisms is important to identify the improvement opportunities based on, probably, the interphase between different solutions.
To achieve the set project goals, this internal research report describes the work packages realised within the framework of the project.
Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous- Flow Production
(2021)
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 downtimes 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. 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. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
ISO/IEC 17025 is the worldwide quality standard for testing and calibration laboratories. It is the basis for accreditation by an accreditation body. The current version was published in 2018.
Implementing ISO/IEC 17025 as part of laboratory quality initiatives offers both laboratory and business benefits, such as expanding the potential customer base for testing and/or calibration, increasing the reputation and image of the laboratory at national and international level, continuous improvement of the data quality and the effectiveness of the laboratory or creation of a good basis for most other quality systems in the laboratory sector, such as GxP. The main difference between a proper approach to analysis and a formal accreditation is shown in a targeted documentation, especially on the qualification of the personnel, the test equipment and the validation of the analytical methods.
Using quantitative NMR spectroscopy as an example, it is shown how accreditation can be carried out and what documentation is required. In our case, we have described the procedure in an SOP ("Determination of the quantitative composition of simple mixtures of structurally known compounds with 1H-NMR spectroscopy") and supported it with a modular system of organizational and equipment SOPs. The special feature is that the accredited method is independent for the choice of the analyte and the matrix and therefore it is possible to operate with a single validated method. In our case, we have proposed three quality levels ("leagues") with different levels of analytical effort, which differ in their measurement uncertainty, in order to simplify the workflow and analysis design.
Chemical and pharmaceutical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these.
A current approach uses flexible and modular chemical production units, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. At the same time, we need to move towards knowledge-based production that takes into account all essential equipment, process and control data from plants and laboratories and makes valuable expertise available and transferable. The potential of data from production together with its contextual information is often not yet consistently used today for a comprehensive understanding of production.
By giving examples this paper outlines a possible more holistic approach to digitalisation and the use of machine-based methods in the production of specialty chemicals and pharmaceuticals through the introduction of integrated and networked systems and processes.
A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. “Chemputer” which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.
Electrochemical methods offer great promise in meeting the demand for user-friendly on-site devices for Monitoring important parameters. The food industry often runs own lab procedures, for example, for mycotoxin analysis, but it is a major goal to simplify analysis, linking analytical methods with smart technologies. Enzyme-linked immunosorbent assays, with photometric detection of 3,3’,5,5’-tetramethylbenzidine (TMB),form a good basis for sensitive detection. To provide a straightforward approach for the miniaturization of the detectionstep, we have studied the pitfalls of the electrochemical TMB detection. By cyclic voltammetry it was found that the TMB electrochemistry is strongly dependent on the pH and the electrode material. A stable electrode response to TMB could be achieved at pH 1 on gold electrodes. We created a smartphonebased, electrochemical, immunomagnetic assay for the detection of ochratoxin A in real samples, providing a solid basis forsensing of further analytes.
Der Sensorik kommt bei der Digitalisierung der Prozessindustrie eine Schlüsselrolle zu. Entsprechend ist sie ein zentraler Baustein der NAMUR Open Architecture Konzepts (NOA). M+O-Sensoren (Monitoring + Optimization) - stellen eine neue Geräteklasse für die zusätzliche Überwachung und Optimierung von Anlagen der Prozessindustrie dar. Diese deckt klassische und alternative Messprinzipien bis hin zur Nachbildung der menschlichen Sinne ab. Hier werden die Anforderungen an M+O-Sensoren als Bestandteile der NOA beschrieben.
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 downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Ergot alkaloids are mycotoxins formed by fungi of the Claviceps genus, which are some of the most common contaminants of food and feed worldwide. These toxins are a structurally heterogeneous group of compounds, sharing an ergoline backbone. Six structures and their corresponding stereoisomers are typically quantified by either HPLC-FLD or HPLC-MS/MS and the values subsequently summed up to determine the total ergot alkaloid content. For the development of a screening method targeting all ergot alkaloids simultaneously, the alkaloids need to be transferred to one homogeneous structure: a lysergic acid derivative. In this study, two promising cleaving methods—acidic esterification and hydrazinolysis—are compared, using dihydroergocristine as a model compound. While the acidic esterification proved to be unsuitable, due to long reaction times and oxidation sensitivity, hydrazinolysis reached a quantitative yield in 40-60 min. Parallel workup of several samples is possible. An increasing effect on the reaction rate by the addition of ammonium iodide was demonstrated. Application of hydrazinolysis to a major ergot alkaloid mix solution showed that all ergopeptines were cleaved, but ergometrine/-inine was barely affected. Still, hydrazinolysis is a suitable tool for the development of a sum parameter screening method for ergot alkaloids in food and feed.
The combination of different silanes as starting materials and as a product of hydrolysis by several alcohols or water creates a range of hundreds of technical products for a wide range of applications. In recent years, functional trialkoxysilanes have proven to be multi-purpose organosilanes. Applications range from weather protection of buildings to additives for glass fiber industry, sealants, adhesives, coatings and paints to the modification of polymers.
Commercial benchtop NMR spectrometers have the potential to be used in silane chemistry as an online method for reaction monitoring and quality control. NMR nuclei of interest for silane products are 1H and 29Si. In a joint research cooperation between EVONIK and BAM, the applicability of low-field NMR spectroscopy for the chemical analysis of silanes was evaluated. It was shown how it can extend the application range where existing technologies like NIR, Raman, UV/VIS, etc. cannot be used quantitatively due to a lack of reference data.
In a first case study the process of hydrolysis and condensation was observed using online NMR analysis. For this purpose, the substituents of a trialkoxysilane are first hydrolyzed by adding water and corresponding silanols are formed, which can then bind to materials via SiOH functions and crosslink to form siloxane units. Another case study was dealing with the kinetics of the cleavage of a cyclic silane compound. Online NMR analysis was used both in the laboratory and in the manufacturing plant. For this purpose, a fully automated containment system was used, which enables the use of a commercial NMR spectrometer in ATEX-environments. In the third case study presented, quantitative 1H-NMR spectra were acquired on product mixtures of a trialkoxysilane and other components such as organic stabilizers, organotin compounds, an aromatic amine and organic peroxides. An automatic evaluation method based on Indirect Hard Modeling (IHM) was developed.
The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties.
The competitiveness of the process industry is based on ensuring the required product quality while making optimum use of equipment, raw materials and energy. Chemical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these.
One way is knowledge-based production, taking into account all essential equipment, process and regulatory data of plants and laboratories. Today, the potential of this data is often not yet consistently used for a comprehensive understanding of production. Another approach uses flexible and modular chemical plants, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. Digital transformation is enabling completely new production concepts that are being used increasingly. Intensified continuous production plants also allow for difficult to produce compounds.
This contribution aims to encourage a more holistic approach to the digitalization and use of machine-assisted methods in (bio) process engineering by introduction of integrated and networked systems and processes, which have the potential to speed up the high-quality production of specialty chemicals and pharmaceuticals.
Industrielle Anwendungen der Niederfeld-NMR-Spektroskopie für die Qualitätskontrolle von Silanen
(2021)
Aus der Kombination verschiedener Silane als Ausgangsstoffe und als Produkt der Hydrolyse durch eine Reihe von Alkoholen oder Wasser ergibt sich eine Palette von hunderten technischen Produkten für verschiedenste Anwendungen. Funktionelle Trialkoxysilane haben sich in den vergangenen Jahren als vielseitig einsetzbare Organosilane erwiesen. Die Einsatzgebiete erstrecken sich vom Witterungsschutz von Bauwerken über haftvermittelnde Eigenschaften in der Glasfaserindustrie, bei Dicht- und Klebstoffen, in Farben und Lacken bis hin zur Modifizierung von polymeren Werkstoffen.
Kommerzielle Benchtop-NMR-Spektrometer haben das Potential auch im Bereich der Silanchemie als Online-Methode zur Reaktionsüberwachung und für die Qualitätskontrolle eingesetzt zu werden. Interessante NMR-Kerne für die oben genanntem Produkte sind 1H und 29Si. In einer gemeinsamen Forschungskooperation zwischen EVONIK und BAM wurde anhand verschiedener Fallstudien die Anwendbarkeit der Niederfeld-NMR-Spektroskopie zur chemischen Analyse von Silanen evaluiert. Die Möglichkeiten der Konzentrationsbestimmung erweitern die Anwendungsgebiete, in denen bestehende Technologien wie z. B. NIR, Raman, UV/VIS, etc. mangels Referenzdaten nicht quantitativ eingesetzt werden können.
Eine Fallstudie setzte dazu an, den Hydrolyse- und Kondensationsverlauf mit geeigneter Online-NMR-Analytik zu beobachten, den Reaktionsfortschritt der Hydrolyse und Kondensation auf dieser Basis besser zu verstehen und zu optimieren. Zu diesem Zweck werden durch Zugabe von Wasser zunächst die Alkoxysubstituenten eines Trialkoxysilans hydrolysiert und entsprechende Silanole gebildet. Diese können dann über eine SiOH-Funktion an den zu modifizierenden Werkstoff anbinden und über weitere Silanolgruppen unter Ausbildung von Siloxaneinheiten vernetzen. In einer weiteren Fallstudie wurde die Kinetik der Aufspaltungen einer cyclischen Silanverbindung untersucht. Die Online-NMR-Analytik kam hierbei sowohl im Labor als auch in der industriellen Produktionsanlage zum Einsatz. Hierfür wurde eine automatisierte Einhausung verwendet, welche den Einsatz eines kommerziellen NMR-Spektrometers in explosionsgeschützten Bereichen ermöglicht.
Der Artikel ist ein Editorial, der für die Herstellung eines grundlegenden Vertrauens in medizinische Produkte - insbesondere Impfstoffe - wirbt, um Skeptiker zu Unterstützern zu machen. Er wirbt nicht nur für die Impfstoffe, sondern auch für die Kultur der Pharmazie und Chemie und die Wissenschaft ganz allgemein und regt an, mehr erklärende Formate wie z. B. im Stil der Sendung mit der Maus für diese Dinge zu werben. Der Artikel geht auch auf den ungeheuren Reiz der seit gut zwanzig Jahren diskutierten risikobasierten Ansätze für pharmazeutische Entwicklung und Herstellung von Arzneimitteln auf Basis der Quality Guidelines ein.
In den letzten Jahrzehnten ist die Nachfrage nach kostengünstigen und flächendeckenden Kartierungsmöglichkeiten im Hinblick auf eine ertragssteigernde und umweltfreundlichere Bewirtschaftung von landwirtschaftlichen Nutzflächen stark gestiegen. Hierfür eignen sich spektroskopische Methoden wie die Röntgenfluoreszenzanalyse (RFA), Raman- und Gammaspektroskopie sowie die laserinduzierte Plasmaspektroskopie (LIBS). In Abhängigkeit von der Funktionsweise der jeweiligen Methoden werden Informationen zu verschiedensten Bodeneigenschaften wie Nährelementgehalt, Textur und pH-Wert erhalten.
Ziel dieser Arbeit ist die Entwicklung eines Online-LIBS-Verfahrens zur Nährelementbestimmmung und Kartierung von Ackerflächen. Die LIBS ist eine schnelle und simultane Multielementanalyse bei der durch das Fokussieren eines hochenergetischen Laserpulses Probenmaterial von der Probenoberfläche ablatiert wird und in ein Plasma überführt wird. Beim Abkühlen des Plasmas wird Strahlung emittiert, welche Rückschlüsse über die elementare Zusammensetzung der Probe gibt. Diese Arbeit ist im Teilprojekt I4S (Intelligenz für Böden) im Forschungsprogramm BonaRes (Boden als nachhaltige Ressource für die Bioökonomie) des Bundesministerium für Bildung und Forschung (BMBF) entstanden. Es wurden insgesamt 651 Bodenproben von verschiedenen Test-Agrarflächen unterschiedlichster Standorte Deutschlands gemessen, ausgewertet und zu Validierungszwecken mit entsprechender Referenzanalytik wie die Optische Emissionsspektroskopie mittels induktiv gekoppeltem Plasma (ICP-OES) und die wellenlängendispersive Röntgenfluoreszenzanalyse (WDRFA) charakterisiert.
Für die Quantifizierung wurden zunächst die Messparameter des LIBS-Systems auf die Bodenmatrix optimiert und für die Elemente geeignete Linien ausgewählt sowie deren Nachweisgrenzen bestimmt. Es hat sich gezeigt, dass eine absolute Quantifizierung basierend auf einem univariaten Ansatz aufgrund der starken Matrixeffekte und der schlechten Reproduzierbarkeit des Plasmas nur eingeschränkt möglich ist. Bei Verwendung eines multivariaten Ansatz wie der Partial Least Squares Regression (PLSR) für die Kalibrierung konnten für die Nährelemente im Vergleich zur univariaten Variante Analyseergebnisse mit höherer Güte und geringeren Messunsicherheiten ermittelt werden. Die Untersuchungen haben gezeigt, dass das multivariate Modell weiter verbessert werden kann, indem mit einer Vielzahl von gut analysierten Böden verschiedener Standorte, Bodenarten und einem breiten Gehaltsbereich kalibriert wird. Mithilfe der Hauptkomponentenanalyse (PCA) wurde eine Klassifizierung der Böden nach der Textur realisiert. Weiterhin wurde auch eine Kalibrierung mit losem Bodenmaterial erstellt. Trotz der Signalabnahme konnten für die verschiedenen Nährelemente Kalibriergeraden mit ausreichender, analytischer Güte erstellt werden.
Für den Einsatz auf dem Acker wurde außerdem der Einfluss von Korngröße und Feuchtigkeit auf das LIBS-Signal untersucht. Die unterschiedlichen Korngrößen haben nur einen geringen Einfluss auf das LIBS-Signal und das Kalibriermodell lässt sich durch entsprechende Proben leicht anpassen. Dagegen ist der Einfluss der Feuchtigkeit deutlich stärker und hängt stark von der Bodenart ab, sodass für jede Bodenart ein separates Kalibriermodell für verschiedene Feuchtigkeitsgehalte erstellt werden muss. Mithilfe der PCA kann der Feuchtigkeitsgehalt im Boden grob abgeschätzt werden und die entsprechende Kalibrierung ausgewählt werden.
Diese Arbeit liefert essentielle Informationen für eine Echtzeit-Analyse von Nährelementen auf dem Acker mittels LIBS und leistet einen wichtigen Beitrag zu einer fortschrittlichen und zukunftsfähigen Nutzung von Ackerflächen.
Im Rahmen der vom Bundesministerium für Bildung und -forschung geförderten Forschungsinitiative „BonaRes – Boden als nachhaltige Ressource der Bioökonomie“ soll sich das Teilprojekt „I4S – integrated system for site-specific soil fertility management“ der Entwicklung eines integrierten Systems zum ortsspezifischen Management der Bodenfruchtbarkeit widmen. Hierfür ist eine Messplattform zur Bestimmung relevanter Bodeneigenschaften und der quantitativen Analyse ausgewählter Makro- und Mikronährstoffe geplant. In der ersten Phase dieses Projekts liegt das Hauptaugenmerk auf der Kalibrierung und Validierung der verschiedenen Sensoren auf die Matrix Boden, der Probennahme auf dem Acker und der Planung sowie dem Aufbau der Messplattform. Auf dieser Plattform sollen in der zweiten Phase des Projektes die verschiedenen Bodensensoren installiert, sowie Modelle und Entscheidungsalgorithmen zur Steuerung der Düngung und dementsprechend Verbesserung der Bodenfunktionen erstellt werden.
Ziel der vorliegenden Arbeit ist die Grundlagenuntersuchung und Entwicklung einer robusten Online-Analyse mittels Energie-dispersiver Röntgenfluoreszenzspektroskopie (EDRFA) zur Quantifizierung ausgewählter Makro- und Mikronährstoffe in Böden für eine kostengünstige und flächendeckende Kartierung von Ackerflächen. Für die Entwicklung eines Online-Verfahrens wurde ein dem Stand der Technik entsprechender Röntgenfluoreszenzmesskopf in Betrieb genommen und die dazugehörigen Geräteparameter auf die Matrix Boden optimiert. Die Bestimmung der analytischen Qualitäts-merkmale wie Präzision und Nachweisgrenzen fand für eine Auswahl an Nährelementen von Aluminium bis Zink statt. Um eine möglichst Matrix-angepasste Kalibrierung zu erhalten, wurde sowohl mit zertifizierten Referenzmaterialien (CRM), als auch mit Ackerböden kalibriert. Da einer der größten Nachteile der Röntgenfluoreszenzanalyse die Beeinflussung durch Matrixeffekte ist, wurde neben der klassischen univariaten Datenauswertung auch die chemometrische multivariate Methode der Partial Least Squares Regression (PLSR) eingesetzt. Die PLSR bietet dabei den Vorteil, Matrixeffekte auszugleichen, wodurch robustere Kalibriermodelle erhalten werden können. Zusätzlich wurde eine Hauptkomponentenanalyse (PCA) durchgeführt, um Gemeinsamkeiten und Ausreißer innerhalb des Probensets zu identifizieren. Es zeigte sich, dass eine Klassifizierung der Böden anhand ihrer Textur Sand, Schluff, Lehm und Ton möglich ist.
Aufbauend auf den Ergebnissen idealer Bodenproben (zu Tabletten gepresste luftgetrocknete Proben mit Korngrößen < 0,5 mm) wurde im Verlauf dieser Arbeit die Probenvorbereitung immer weiter reduziert und der Einfluss verschiedener Kenngrößen untersucht. Diese Einflussfaktoren können die Dichte und die Homogenität der Probe, sowie Korngrößeneffekte und die Feuchtigkeit sein. Anhand des RMSE (Wurzel der mittleren Fehlerquadratsumme) und unter Berücksichtigung der Residuen werden die jeweils erstellten Kalibriermodelle miteinander verglichen. Um die Güte der Modelle zu bewerten, wurden diese mit einem Testset validiert. Hierfür standen 662 Bodenproben von 15 verschiedenen Standorten in Deutschland zur Verfügung. Da die Ergebnisse an gepressten Tabletten für die Elemente Al, Si, K, Ca, Ti, Mn, Fe und Zn den Anforderungen für eine spätere Online-Analyse entsprechen, wurden im weiteren Verlauf dieser Arbeit Kalibriermodelle mit losen Bodenproben erstellt. Auch hier konnten gute Ergebnisse durch ausreichende Nachweisgrenzen und eine niedrige gemittelte Messabweichung bei der Vorhersage unbekannter Testproben erzielt werden. Es zeigte sich, dass die Vorhersagefähigkeit mit der multivariaten PLSR besser ist als mit der univariaten Datenauswertung, insbesondere für die Elemente Mn und Zn.
Der untersuchte Einfluss der Feuchtigkeit und der Korngrößen auf die Quantifizierung der Elementgehalte war vor allem bei leichteren Elementen deutlich zu sehen. Es konnte schließlich eine multivariate Kalibrierung unter Berücksichtigung dieser Faktoren für die Elemente Al bis Zn erstellt werden, so dass ein Einsatz an Böden auf dem Acker möglich sein sollte. Eine höhere Messunsicherheit muss dabei einkalkuliert werden. Für eine spätere Probennahme auf dem Feld wurde zudem der Unterschied zwischen statischen und dynamischen Messungen betrachtet, wobei sich zeigte, dass beide Varianten genutzt werden können. Zum Abschluss wurde der hier eingesetzte Sensor mit einem kommerziell erhältlichen Hand-Gerät auf sein Quantifizierungspotential hin verglichen. Der Sensor weist anhand seiner Ergebnisse ein großes Potential als Online-Sensor für die Messplattform auf. Die Ergebnisse unter Laborbedingungen zeigen, dass eine robuste Analyse Ackerböden unter Berücksichtigung der Einflussfaktoren möglich ist.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Dear Colleagues,
Raman spectroscopy provides vibrational fingerprints of chemical compounds, enabling their identification via a comparison with reference spectra. This analytical tool has high potential not only in the identification of minerals from natural sources but also for studying the complex microstructure and mineral distribution of both ancient and modern man-made materials, ranging from, e.g., historical ceramics and mortars to modern solar cell materials. In addition to the chemical identity of minerals, Raman spectra are affected by crystal orientations, substoichiometric to stoichiometric compositional changes (e.g., in solid solution series), traces of foreign ions, stress, strain, and crystallinity, enabling a comprehensive physicochemical characterisation of minerals. This Special Issue includes method developments and applications in the field of modern Raman spectroscopy of minerals in a broad sense, from natural mineral deposits to inorganic phases in materials; covers both spectroscopic and imaging studies; and provides a platform for discussing the possibilities and limits of the technique in the context of the existing analytical arsenal.
Thomas Schmid
Petra Dariz
Künstliche Mineralfasern (KMF) werden weltweit in vielfältiger Weise als Dämmstoffe verwendet. Jährlich fallen in Deutschland ungefähr 20 Millionen Tonnen KMF an, die nach dem Abriss auf Deponien entsorgt werden müssen. Grundsätzlich besteht jedoch die Möglichkeit der Rückführung dieser Materialien in den Produktionsprozess. Dafür ist es notwendig, anfallende KMF sowohl nach Material (Glaswolle, Steinwolle) als auch nach Alter zu sortieren.
Auf der Suche nach einer Methode, die es grundsätzlich gestattet eine schnelle Untersuchung vor Ort auf einer Baustelle durchzuführen, wurde die Nah-Infrarot (NIR) Spektroskopie unter Verwendung eines Prozessspektrometers mit Reflexionssonde getestet. Anhand von Laboruntersuchungen an 70 KMF Proben, die entweder betriebsneu waren oder bundesweit auf Baustellen gesammelt wurden, konnte eine NIR-basierte Methode zur Unterscheidung in Glas- und Steinwolle entwickelt werden. Mittels Partial Least Square Diskriminanzanalyse (PLS-DA) der NIR Spektren wurde basierend auf 40 zufällig ausgewählten Proben ein chemometrisches Modell kalibriert, das erfolgreich zur Klassifizierung der verbleibenden 30 Proben eingesetzt werden konnte. Unabhängig von Farbe, Dichte oder Alter der untersuchten KMF Proben war es möglich, eine 100% korrekte Zuordnung des Materials zu erzielen. Die nötigen Referenzwerte wurden unter Nutzung eines Röntgenfluoreszenzspektroskopischen Verfahrens über den Elementgehalt nach VDI 3492 ermittelt.
Insgesamt ist der experimentelle Aufwand für die Durchführung und Auswertung der NIR Messungen gering und manifestiert sich vor allem in der Kalibrierphase, die in diesem Fall die Untersuchung von 8-fach aliquotierten Probestücken der 70 KMF umfasste. Nur bei deutlich feuchtem Material muss ein zusätzlicher Trocknungs-schritt berücksichtigt werden. Das vorgestellte Verfahren wurde nachfolgend zu einem Patent angemeldet. Untersuchungen zu einer weiteren Unterscheidung der KMF nach Alter sind geplant.
Calibration-Free Chemical Process and Quality Control Units as Enablers for Modular Production
(2021)
Modular chemical production is a tangible translation of the digital transformation of the process industry for specialty chemicals. In particular, it enables the speeding-up of process development and thus a quicker time to market by flexibly connecting and orchestrating standardised physical modules and bringing them to life (i.e., parameterising them) with digitally accumulated process knowledge.
We focus on the specific challenges of chemical process and quality control, which in its current form is not well suited for modular production and provide possible approaches and examples of the change towards direct analytical methods, analytical model transfer or machine-supported processes.
Chemische Prozesskontrolle für modulare Produktionskonzepte mit direkten analytischen Methoden
(2020)
Flexible Produktionskonzepte werden oft mit modularen, schnell rekonfigurierbaren Einheiten verbunden. Um die Vorteile dieser flexiblen Produktion tatsächlich nutzen zu können ist neben einer geeigneten Infrastruktur auch eine ebenso anpassungsfähige Qualitätskontrolle unverzichtbar. Analysengeräte und Sensoren werden heutzutage immer kompakter und kostengünstiger in ihrer Anschaffung. Dadurch wird es möglich eine große Anzahl von Messstellen innerhalb einer Anlage zu realisieren. Die erfassten Datenmengen erfordern zuverlässige und robuste Auswerteverfahren, die sich in das Gesamtkonzept der Automatisierung einer derart flexiblen Produktion nahtlos integrieren. Referenzdaten aus direkten Methoden wie der NMR-Spektroskopie können hier einen wertvollen Beitrag zur Generierung von Prozesswissen für die Entwicklung neuer Modelle für kostengünstigere Analysenverfahren leisten.
Bei Industry 4.0 dreht sich alles um Interkonnektivität, sensorgestützte Prozesssteuerung und datengesteuerte Systeme. Prozessanalysentechnik (PAT) wie die Online-Kernresonanzspektroskopie (NMR) gewinnt zunehmend an Bedeutung, da sie zur Automatisierung und Digitalisierung in der Produktion beiträgt. Eine klassische Auswertung von Prozessdaten und deren Umsetzung in Wissen ist jedoch bisher in vielen Fällen aufgrund der unzureichend großen verfügbaren Datensätze nicht möglich oder nicht wirtschaftlich. Bei der Entwicklung eines automatisierten Verfahrens für die Prozesskontrolle stehen manchmal nur die Basisdaten einer begrenzten Anzahl von Batch-Versuchen aus typischen Produkt- und Prozessentwicklungskampagnen zur Verfügung. Diese Datensätze sind jedoch nicht groß genug, um maschinengestützte Verfahren zu trainieren.
Um diese Einschränkung zu überwinden, wurde ein neues Verfahren entwickelt, das eine physikalisch motivierte Multiplikation der verfügbaren Referenzdaten erlaubt, um einen ausreichend großen Datensatz für das Training von maschinellen Lernalgorithmen zu erhalten. Das zugrundeliegende Beispiel einer chemischen Synthese wurde spektroskopisch verfolgt und mit der neuen Methode sowie mit einem physikalisch basierten Modell analysiert, wobei sowohl eine anwendungsrelevante Niederfeld-NMR als auch eine Hochfeld-NMR-Spektroskopie als Referenzmethode verwendet wurde.
Künstliche neuronale Netze (ANNs) haben das Potenzial, bereits aus relativ begrenzten Eingabedaten wertvolle Prozessinformationen abzuleiten. Um jedoch die Konzentration unter komplexen Bedingungen (viele Edukte und weite Konzentrationsbereiche) vorherzusagen, sind größere ANNs und damit ein größerer Trainingsdatensatz erforderlich. Wir zeigen, dass ein mäßig komplexes Problem mit vier Edukten unter Verwendung von ANNs in Kombination mit der vorgestellten PAT-Methode (Niederfeld-NMR-Spektroskopie) und mit dem vorgeschlagenen Ansatz zur Erzeugung aussagekräftiger Trainingsdaten bewältigt werden kann.
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 downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications. In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
Due to its advantages of being a direct comparison method, quantitative NMR spectroscopy (qNMR) becomes more and more popular in industry. While conventional high-field NMR systems are often associated with high investment and operational costs, the upcoming market of permanent-magnet based benchtop NMR systems show a considerable option for a lot of applications. The mobility of these systems allows to bring them more closely to the real production environment, e.g. for at-line quality control.
In this work we present an interlaboratory comparison study investigating the qNMR performance of state-of-the-art benchtop NMR spectrometers. Therefore, BAM prepared two samples of a mixture of NMR reference standards tetramethylbenzene (TMB) and tetrachloronitrobenzene (TCNB) at concentration levels of 200 mM and 10 mM. These “ready-to-use” samples were sent to participant laboratories, which performed analysis on their benchtop NMR equipment of different vendors and fields from 43 to 80 MHz. Raw data was reported back and further investigated by using different data analysis methods at BAM.
After this very first qNMR comparison study of benchtop NMR spectrometers show promising results, following studies are planned to cover more parts of the qNMR process, e.g. sample preparation and weighing, but also data analysis, as commonly done in similar studies for high-field NMR spectroscopy in industry and metrology.
The increasing enrichment of water bodies and soils with plastic waste leads to the accumulation of microscopic plastic particles, so-called microplastics (MP). There is an urgent need for analytical methods that help to identify and quantify MP. At present, mainly thermo-analytical and microscopic methods such as micro-infrared spectroscopy or micro-Raman are used for this purpose. The latter are usually tied to time-consuming sample enrichment and preparation, only small sample quantities (micrograms) can be examined and the evaluation of the obtained spectra can be demanding. In the context of this presentation, two approaches are presented which, via the multi-variate analysis of spectroscopic data, allow i) a new methodological approach to screening MP in contaminated soils and ii) an alternative evaluation of large (micro)-spectroscopic data sets.
First, a NIR spectroscopic method is presented which allows MP consisting of polyethylene, polyethylene terephthalate, polypropylene and polystyrene to be detected in the range of up to 0.5 mass percent. Due to short measurement times and robust technology, this approach has the potential, in contrast to thermo-analytical and micro-spectroscopic methods, to examine larger sample quantities with minimal pre-treatment.
The second approach deals with the evaluation of large data sets, as typically obtained as a result of micro-FTIR using modern FPA detectors. The micro-FTIR technique is based on the spectral recording, imaging and subsequent identification of vibration bands typical of synthetic polymers. The image data sets are large and contain spectra of numerous particles of natural and synthetic origin. Exploratory multivariate data analysis has been tested to complement existing approaches based on e.g. spectrum library searches. The core concept used was dimensionality reduction. The results not only represent an orthogonal method for checking the results obtained by an automated library search, but also revealed a group of spectra that were not recorded in the existing spectrum libraries.