Monitoring specific chemical properties is the key to chemical process control. Today, mainly optical online methods are applied, which require time- and cost-intensive calibration effort. NMR spectroscopy, with its advantage being a direct comparison method without need for calibration, has a high potential for enabling closed-loop process control while exhibiting short set-up times. Compact NMR instruments make NMR spectroscopy accessible in industrial and rough environments for process monitoring and advanced process control strategies. We present a fully automated data analysis approach which is completely based on physically motivated spectral models as first principles information (indirect hard modeling—IHM) and applied it to a given pharmaceutical lithiation reaction in the framework of the European Union’s Horizon 2020 project CONSENS. Online low-field NMR (LF NMR) data was analyzed by IHM with low calibration effort, compared to a multivariate PLS-R (partial least squares regression) approach, and both validated using online high-field NMR (HF NMR) spectroscopy. [Figure not available: see fulltext.].
CITATION STYLE
Kern, S., Meyer, K., Guhl, S., Gräßer, P., Paul, A., King, R., & Maiwald, M. (2018). Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis. Analytical and Bioanalytical Chemistry, 410(14), 3349–3360. https://doi.org/10.1007/s00216-018-1020-z
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