4.7 Article

Near-infrared hyperspectral imaging for polymer particle size estimation

Journal

MEASUREMENT
Volume 186, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2021.110201

Keywords

Particle size distribution; Hyperspectral imaging; Polymer detection; Polymer processing; Chemometrics

Funding

  1. National Science Centre, Poland [2018/29/N/ST4/01547]

Ask authors/readers for more resources

This study explores the potential of near-infrared hyperspectral imaging for accurately assessing the size of polymer particles compared to traditional single point measurement methods. Hyperspectral imaging not only provides information about the spatial distribution of sample components, but also reveals changes in physical properties.
This study examines the potential of near-infrared hyperspectral imaging for assessing the size of polymer particles in model fractions based on the scattering phenomena. Different fractions of ground polymers, either polymethyl methacrylate or polypropylene, were characterized by near-infrared spectra collected between 900 and 1700 nm. The possibility to estimate the size of polymer particles using hyperspectral images was confronted with a basic single spot near-infrared measurement. Hyperspectral imaging, in addition to the standard spectral data dimension, provides information about the spatial distribution of sample components and reveals changes in physical properties. Therefore, one can gain a better insight into the scattering phenomena and study the physical inhomogeneity of a sample in terms of particle size distribution. The partial least-squares models constructed to estimate particle size of polymers that were characterized by hyperspectral images (a pixel-based approach) outperforms models built for mean spectra regardless of the considered powdered polymer.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available