TY - CONF A1 - Kern, Simon A1 - Guhl, Svetlana A1 - Meyer, Klas A1 - Wander, Lukas A1 - Paul, Andrea A1 - Maiwald, Michael T1 - Mathematical and statistical tools for online NMR spectroscopy in chemical processes T2 - Tagungsband 13. Dresdner Sensor-Symposium N2 - 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. PB - AMA Service GmbH CY - Berlin T2 - 13. Dresdner Sensor Symposium CY - Dresden, Germany DA - 04.12.2017 KW - Online NMR spectroscopy KW - Process control KW - Partial least squares regression KW - Indirect hard modeling KW - Quantum mechanics KW - First principles PY - 2017 UR - https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/43254 AN - OPUS4-43254 UR - https://www.ama-science.org/proceedings/details/2748 SN - 978-3-9816876-5-1 SP - P2, 209 EP - 212 AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany