Analytische Chemie
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The Royal Society of Chemistry NMR Discussion Group and Molecular Spectroscopy Group would like to invite you to the 2017 Spring Meeting, which will be held at GlaxoSmithKline (GSK), Stevenage. The theme for the meeting is “Low level detection and quantification by NMR” and different NMR technologies, including solution state NMR, solid state NMR and benchtop/low field NMR will be discussed. The presentations will cover a range of NMR related disciplines, including conventional low level detection and quantification, the use of cryoprobes, quantification of polymorphism using ssNMR and also methods for spectral simplification. Recent developments and applications of hyperpolarisation techniques, within both solution state and solid state NMR, will be presented in conjunction with the effect these sensitivity enhancements have with respect to quantification and limits of detection.
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short down-times between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. The advances of a fully automated NMR sensor were exploited, using a given pharmaceutical lithiation reaction as an example process within a modular pilot plant. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as , e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. NMR appeared as preeminent online analytical tool and allowed using a modular data analysis tool, which even served as reliable reference method for further PAT applications.
Recently, AI procedures have also been successfully used for NMR data evaluation. In order to overcome the typical limitation of too small data sets from process developments, a new method was tested, which allows a physically motivated multiplication of the available reference data together with context information in order to obtain a sufficiently large data set for the training of machine learning algorithms.
In future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.