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- Online NMR Spectroscopy (3) (entfernen)
Online monitoring and process control requires fast and noninvasive analytical methods, which are able to monitor the concentration of reactants in multicomponent mixtures with parts-per-million resolution. Online NMR spectros-copy can meet these demands when flow probes are directly coupled to reactors, since this method features a high linearity between absolute signal area and sample concentration, which makes it an absolute analytical com-parison method being independent on the matrix. Due to improved magnet design and field shimming strategies portable and robust instruments have been introduced to the market by several manufacturers during the last few years. First studies with this technology showed promising results to monitor chemical reaction in the laboratory.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Smart sensors enable concepts like self-diagnostics, self-calibration, and self-configuration/parameterization whenever our current automation landscape allows it. Here we summarize the currently discussed general requirements for process sensors 4.0 and introduce a smart online NMR sensor module as example, which was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu).
The development of innovative medium resolution NMR spectrometers (MR-NMR) is remarkable due to their possible applications in quality control, education, or process monitoring.
The use of compact permanent magnets allows to employ NMR devices in an industrial environment without high maintenance requirements and without the need for cryogenic liquids.
A benchtop 43 MHz MR-NMR spectrometer was used for reaction monitoring. Quasi-simultaneous proton and fluorine NMR spectra were acquired. Automatic data pretreatment and evaluation methods were applied and compared to quantitative 500 MHz HR-NMR spectroscopy