2000
DOI: 10.1002/1097-4628(20010118)79:3<426::aid-app50>3.0.co;2-v
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Measurement of partial conversions during the solution copolymerization of styrene and butyl acrylate using on-line raman spectroscopy

Abstract: The copolymerization of styrene and n‐butyl acrylate in dioxane was monitored by on‐line Raman spectroscopy. The calculation of the individual monomer concentrations on the basis of the individual vinyl peaks is not straightforward for this system, as these bands are overlapping in the Raman spectrum. To tackle this problem, univariate and multivariate approaches were followed to obtain monomer concentrations and the results were validated by reference gas chromatography data. In the univariate analysis, linea… Show more

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Cited by 34 publications
(1 citation statement)
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“…Within a single Raman spectrum, we specifically monitored the area under the curve (AUC) of the Raman active vibrational modes of the styrene vinyl CC stretch (∼1630 cm –1 ) and the p -xylene ring breathing mode (∼830 cm –1 ) . Since Raman spectroscopy involves light scattering and absolute intensities cannot be used to quantify conversion, we normalized the vinyl AUC against the p -xylene AUC within a Raman spectrum to allow for the subsequent quantification of conversion across residence times. To allow for rapid data extraction from a large number of Raman spectra collected during the experiments, we automated baseline subtraction, peak fitting, and AUC calculation using Python scripts.…”
Section: High-throughput Raman Spectra Data Extractionmentioning
confidence: 99%
“…Within a single Raman spectrum, we specifically monitored the area under the curve (AUC) of the Raman active vibrational modes of the styrene vinyl CC stretch (∼1630 cm –1 ) and the p -xylene ring breathing mode (∼830 cm –1 ) . Since Raman spectroscopy involves light scattering and absolute intensities cannot be used to quantify conversion, we normalized the vinyl AUC against the p -xylene AUC within a Raman spectrum to allow for the subsequent quantification of conversion across residence times. To allow for rapid data extraction from a large number of Raman spectra collected during the experiments, we automated baseline subtraction, peak fitting, and AUC calculation using Python scripts.…”
Section: High-throughput Raman Spectra Data Extractionmentioning
confidence: 99%