P2.07 - Mathematical and Statistical Tools for Online NMR Spectroscopy in Chemical Processes
- Event
- 13. Dresdner Sensor-Symposium 2017
2017-12-04 - 2017-12-06
Hotel Elbflorenz, Dresden - Chapter
- P2. Prozessmesstechnik
- Author(s)
- S. Kern, S. Guhl, K. Meyer, L. Wander, A. Paul, M. Maiwald - Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin/D
- Pages
- 209 - 212
- DOI
- 10.5162/13dss2017/P2.07
- ISBN
- 978-3-9816876-5-1
- Price
- free
Abstract
Monitoring chemical reactions is the key to chemical process control. Today, mainly optical online methods are applied, which require excessive calibration effort. 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, as demonstrated within the European Union’s Horizon 2020 project CONSENS.
We present a range of approaches for the automated spectra analysis moving from conventional multivariate 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.