Stabilizer-Free Dispersion Copolymerization Monitoring by In-Line NIR Spectroscopy

Abstract

Stabilizer-free dispersion copolymerization is a one-step technique to produce uniform polymer particles. Due to its fast kinetics and nucleation, assessing polymer conversion and particle size via off-line sampling can be a challenge. In addition, off-line analyses, e.g., gravimetry and dynamic light scattering, are time-consuming and can be sample-dependent. Near-infrared (NIR) spectroscopy is a fast and non-destructive technique to monitor polymerization reactions in-line. Stabilizer-free dispersion copolymerization between styrene and maleic anhydride was carried out via free-radical polymerization using isobutyl acetate and isopentyl acetate as solvents. Spectra data were collected in parallel with off-line analysis. Multivariate partial least squares calibration models were constructed to predict global conversion and particle size over time. The external validation shows good agreement between the models and experimental data. NIR can be extended to monitor systems with fast kinetics and to avoid destructive and time-consuming analytical methods.

Polymer Colloids: Current Challenges, Emerging Applications, and New Developments

“…The average particle size (dp) can in principle be monitored by in situ NIR spectroscopy and Raman spectroscopy . However, despite some successful examples, ,− the prediction of particle size by NIR spectroscopy is known to be poor due to the large difference between typical size of particles in emulsion polymerization and the wavelength of the NIR radiation. Raman spectroscopy typically gives good predictions of the average particle size, even at high solids content (up to 48%); however, for that, one needs to overcome the chemometric challenges of the measurement of dp by Raman using multivariate linear or nonlinear calibration models.…”

Real-time monitoring of the column chromatographic process of Phellodendri Chinensis Cortex part I: end-point determination based on near-infrared spectroscopy combined with machine learning

“…Furthermore, the detection modes of NIR spectroscopy include off-line, at-line, on-line, in-line, and non-invasive, which can be selected to match the equipment and exhibit flexibility. [8][9][10][11][12] Developing a quantitative calibration model requires the ''hidden'' information in a spectrum. In order to achieve this goal, a widely applied method is to use partial least squares (PLS) regression, a linear regression algorithm, to conduct multivariate data analysis.…”

“…Furthermore, the detection modes of NIR spectroscopy include off-line, at-line, on-line, in-line, and non-invasive, which can be selected to match the equipment and exhibit flexibility. 8–12…”

Online Monitoring of the Particle Size in Semibatch Emulsion Copolymerization Using Spatially Resolved Spectroscopy and Raman Spectroscopy

“…Some studies have also employed near-infrared spectroscopy (NIR) to predict the particle size, for instance, in the emulsion polymerization of methyl methacrylate, copolymerization of styrene/butyl acrylate , or copolymerization of vinyl acetate/butyl acrylate, butyl acrylate/styrene miniemulsion copolymerization, dispersion polymerization, styrene suspension polymerization, and vinyl chloride suspension polymerization, where the particle size varies between tens of nanometers to a few millimeters between these systems. These studies demonstrated that the NIR spectrum is affected by the particle size distribution.…”