| Title |
Online low-field NMR spectroscopy for process control of an industrial lithiation reaction—automated data analysis
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, April 2018
|
| DOI | 10.1007/s00216-018-1020-z |
| Pubmed ID | |
| Authors |
Simon Kern, Klas Meyer, Svetlana Guhl, Patrick Gräßer, Andrea Paul, Rudibert King, Michael Maiwald |
| Abstract |
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. Graphical abstract NMR sensor module for monitoring of the aromatic coupling of 1-fluoro-2-nitrobenzene (FNB) with aniline to 2-nitrodiphenylamine (NDPA) using lithium-bis(trimethylsilyl) amide (Li-HMDS) in continuous operation. Online 43.5 MHz low-field NMR (LF) was compared to 500 MHz high-field NMR spectroscopy (HF) as reference method. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 40% |
| Canada | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 29% |
| Researcher | 11 | 21% |
| Student > Bachelor | 6 | 12% |
| Student > Master | 5 | 10% |
| Other | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 9 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 22 | 42% |
| Engineering | 7 | 13% |
| Chemical Engineering | 4 | 8% |
| Agricultural and Biological Sciences | 2 | 4% |
| Business, Management and Accounting | 1 | 2% |
| Other | 5 | 10% |
| Unknown | 11 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 June 2020.
All research outputs
#3,063,181
of 25,382,440 outputs
Outputs from Analytical & Bioanalytical Chemistry
#292
of 9,619 outputs
Outputs of similar age
#61,094
of 342,873 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#9
of 181 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 342,873 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 181 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.