Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis
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.
KeywordsOnline NMR spectroscopy Process analytical technology Partial least squares regression Indirect hard modeling Benchtop NMR spectroscopy Smart sensors
The authors thank Lukas Wander for his help plotting Fig. 3.
This study was supported by the funding of CONSENS by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 636942.
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Conflict of interest
The authors declare that they have no conflict of interest.
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