What is it about?
This study focused on using near-infrared hyperspectral imaging to assess the size of polymer particles in model fractions. The accuracy of particle size estimation based on hyperspectral imaging was compared with basic single-spot near-infrared measurements. Hyperspectral imaging provides additional information about the spatial distribution of sample components, which helps in gaining a better understanding of scattering phenomena and particle size distribution. It was also found that partial least-squares models constructed using hyperspectral images outperformed models built for mean spectra, regardless of the evaluated type of powdered polymer. This research was supported by the National Science Centre, Poland (research grant no. 2018/29/N/ST4/01547).
Photo by geissht on Unsplash
Why is it important?
Our findings demonstrate the potential of using hyperspectral imaging to estimate the size of polymer particles in model fractions. This is significant because characterizing the size of polymer particles is critical for various industries. Traditional methods for particle size analysis can be time-consuming and require expensive equipment, making them less accessible for many applications. The use of hyperspectral imaging provides a more efficient and cost-effective approach that can improve the accuracy of particle size estimation. Additionally, the study highlights the importance of considering the spatial distribution of sample components in particle size analysis, which can provide a more comprehensive understanding of particle size distribution and scattering phenomena.
Read the Original
This page is a summary of: Near-infrared hyperspectral imaging for polymer particle size estimation, Measurement, December 2021, Elsevier, DOI: 10.1016/j.measurement.2021.110201.
You can read the full text:
The following have contributed to this page