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Abstract
Manufacturing of particulate products across many industries relies on accurate measurements of particle size distributions in dispersions or powders. Laser diffraction (or small angle light scattering) is commonly used, usually off-line, for particle size measurements. The estimation of particle sizes by this method requires the solution of an inverse problem using a suitable scattering model that takes into account size, shape and optical properties of the particles. However, laser diffraction instruments are usually accompanied by software that employs a default scattering model for spherical particles, which is then used to solve the inverse problem even though a significant number of particulate products occur in strongly non-spherical shapes such as needles. In this work, we demonstrate that using the spherical model for the estimation of sizes of needle-like particles can lead to the appearance of artefacts in the form of multimodal populations of particles with size modes much smaller than those actually present in the sample.
This effect can result in a significant under-estimation of the mean particle size and in false modes in estimated particles size distributions.
This effect can result in a significant under-estimation of the mean particle size and in false modes in estimated particles size distributions.
Original language | English |
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Pages (from-to) | 445-452 |
Number of pages | 8 |
Journal | Chemical Engineering Science |
Volume | 158 |
Early online date | 18 Oct 2016 |
DOIs | |
Publication status | Published - 2 Feb 2017 |
Keywords
- particle size distribution
- particle shape
- particle sizing
- light scattering
- laser diffraction
- non-spherical particles
- needle-like particles
- spherical model
- particle size estimation
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Dive into the research topics of 'Modelling of artefacts in estimations of particle size of needle-like particles from laser diffraction measurements'. Together they form a unique fingerprint.Projects
- 1 Finished
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Intelligent Decision Support Technologies for Continuous Manufacture
Andonovic, I., Bititci, U., Florence, A., Gachagan, A., Johnston, B., Marshall, S., Michie, C., Mulholland, A., Nordon, A., Sefcik, J. & Vasile, M.
AstraZeneca UK Limited, Glaxo Smithkline (UK), EPSRC (Engineering and Physical Sciences Research Council), Bayer Healthcare AG, Novartis Pharma AG
1/02/13 → 31/07/18
Project: Research