Analytische Chemie
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Zusätzlich zu Methodenentwicklung, Miniaturisierung und Kopplungsverfahren zeigen sich die Hyperspektroskopie zusammen mit Imaging‐Verfahren, der Einzelmolekülnachweis und der Einsatz von 3‐D‐Druckern als neue Schwerpunkte. Hinzu kommen künstliche Intelligenz bei Sensoren, Bildgebungsverfahren und Prozesssteuerung sowie die Vernetzung von Analyse‐ und Laborgeräten. Trends und Forschungsthemen aus der analytischen Chemie, zusammengestellt von elf Autoren, koordiniert von Günter Gauglitz.
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.
Mechanochemistry is increasingly used as a ‘green alternative’ for synthesizing various materials including pharmaceutical cocrystals. Herein, we present the mechanochemical synthesis of three new cocrystals containing the API carbamazepine (cocrystals CBZ:Indometacin 1:1, CBZ:Benzamide 1:1, and CBZ:Nifedipine 1:1). The mechanochemical reaction was investigated in situ documenting a fast and complete reaction within one minute. Online NMR spectroscopy proved the direct influence of the dissolution behaviour of the coformers to the dissolution behaviour of the API carbamazepine. The dissolution behaviour of the organic cocrystals is compared to the behaviour of the pure drug indicating a general applicability of this approach for detailed cocrystal dissolution studies.
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.
There have been an increasing number of publications on flow chemistry applications of compact NMR. Despite this, there is so far no comprehensive workflow for the technical design of flow cells. Here, we present an approach that is suitable for the design of an NMR flow cell with an integrated static mixing unit. This design moves the mixing of reactants to the active NMR detection region within the NMR instrument, presenting a feature that analyses chemical reactions faster (5–120 s region) than other common setups. During the design phase, the targeted mixing homogeneity of the components was evaluated for different types of mixing units based on CFD simulation. Subsequently, the flow cell was additively manufactured from ceramic material and metal tubing. Within the targeted working mass flow range, excellent mixing properties as well as narrow line widths were confirmed in validation experiments, comparable to common glass tubes.
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.
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.
The Tutzing Symposium "100 % digital: survival strategies for the process industry" (see 4.1) in April 2018 was characterized by a great momentum which has been taken up and continued until today. The aim was to implement the ideas from the Tutzing Symposium in a coordinated and targeted manner. For this purpose, development needs as well as the numerous currently planned or already started research and development activities in the context of digitalisation were first compiled and analysed. This resulted in the current research landscape for digitalization in the process industry. It now enables to identify open topics and to translate them into research funding programs as well as to define new projects in the dialogue between users, suppliers and research, which are to be meaningfully interlinked and consolidated with existing projects.
Due to the strong interest in digitalisation, activities are constantly being added, so that this paper can only provide a snapshot of the situation in the period 2019-2020.
Zur Onlineüberwachung von Fermentationsprozessen werden zunehmend schwingungsspektroskopische (Raman-, Mittel- und Nahinfrarotspektroskopie (NIRS) und UV-/VIS- Methoden(Absorptions- und Fluoreszenzspektroskopie) in Kombination mit multivariater Auswertung eingesetzt. Anliegen dieser Arbeit war es, zu testen, welche Verfahren für die spektroskopische On- und Offlineüberwachung des Fermentationsprozesses zur biotechnologischen Herstellung einer Malariavaccine grundlegend geeignet sind und welche Messbereiche und Genauigkeiten der Vorhersage im Idealfall bei der Abwesenheit von Hefezellen erzielt werden können.
Current and future requirements to industrial analytical infrastructure—part 2: smart sensors
(2020)
Complex processes meet and need Industry 4.0 capabilities. Shorter product cycles, flexible production needs, and direct assessment of product quality attributes and raw material attributes call for an increased need of new process analytical technologies (PAT) concepts. While individual PAT tools may be available since decades, we need holistic concepts to fulfill above industrial needs. In this series of two contributions, we want to present a combined view on the future of PAT (process analytical technology), which is projected in smart labs (Part 1) and smart sensors (Part 2). Part 2 of this feature article series describes the future functionality as well as the ingredients of a smart sensor aiming to eventually fuel full PAT functionality. The smart sensor consists of (i) chemical and process information in the physical twin by smart field devices, by measuring multiple components, and is fully connected in the IIoT 4.0 environment. In addition, (ii) it includes process intelligence in the digital twin, as to being able to generate knowledge from multi-sensor and multi-dimensional data. The cyber-physical system (CPS) combines both elements mentioned above and allows the smart sensor to be self-calibrating and self-optimizing. It maintains its operation autonomously. Furthermore, it allows—as central PAT enabler—a flexible but also target-oriented predictive control strategy and efficient process development and can compensate variations of the process and raw material attributes. Future cyber-physical production systems—like smart sensors—consist of the fusion of two main pillars, the physical and the digital twins. We discuss the individual elements of both pillars, such as connectivity, and chemical analytics on the one hand as well as hybrid models and knowledge workflows on the other. Finally, we discuss its integration needs in a CPS in order to allow is versatile deployment in efficient process development and advanced optimum predictive process control.