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The recent developments of inovative compact NMR spectrometers are therefore remarkable due to their possible application in process analytical technology (PAT) in an industrial environment without high maintenance requirements. spectroscopic methods, NMR spectroscopy offers some unique features for online reaction monitoring. However, those benefits have not been exploited for PAT applications so far. Within the CONSENS Project, the challenge to adapt a commercially available benchtop NMR spectrometer to the full requirements of an automated chemical production environment was tackled successfully. was provided in an explosion proof housing and involves a compact NMR spectrometer together with an automated data acquisition and evaluation unit, flow control, as well as data communication.
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which are calibration intensive. NMR spectroscopy has a high potential for direct loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and harsh environments for advanced process monitoring and control.
Within the European Union’s Research Project CONSENS (Integrated CONtrol and SENsing by development and integration of a smart NMR module for process monitoring was designed and delivers online spectra of various reactions. The presented NMR module is provided in an explosion proof housing of 57 x 57 x 85 cm module size and involves a compact spectrometer together with an acquisition unit and a programmable logic controller for automated data preparation (phasing, baseline correction), and evaluation.
For reaction monitoring and process control using NMR instruments after acquisition of the FID the data needs to be corrected in real-time for common effects using fast interfaces and automated methods.
When it comes to NMR data evaluation under industrial process conditions, the shape of signals can change drastically due to nonlinear effects. Additionally, the multiplet structure becomes more dominant because of the comparably low-field strengths which results in overlapping of multiple signals. However, the structural and quantitative information is still present but needs to be extracted by applying predictive models.
We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations). By using the benefits of traditional qNMR experiments data analysis models can meet the demands of the PAT community (Process Analytical Technology) regarding low calibration effort/calibration free methods, fast adaptions for new reactants, or derivatives and robust automation schemes.