Estimation of particle size distribution and aspect ratio of non-spherical particles from chord length distribution

• Published in: Chemical engineering science Vol. 123; pp. 629 - 640
• Main Authors: Agimelen, Okpeafoh S., Hamilton, Peter, Haley, Ian, Nordon, Alison, Vasile, Massimiliano, Sefcik, Jan, Mulholland, Anthony J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 17.02.2015
• Subjects: Algorithms; Aspect ratio; Chord length distribution; Crystallization; Cylinders; Estimates; Focused beam reflectance measurement; Inverse problems; Particle shape; Particle size; Particle size distribution; Chord length distribution; Particle size distribution; Particle shape; Focused beam reflectance measurement
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2014.11.014

Information about size and shape of particles produced in various manufacturing processes is very important for process and product development because design of downstream processes as well as final product properties strongly depend on these geometrical particle attributes. However, recovery of particle size and shape information in situ during crystallisation processes has been a major challenge. The focused beam reflectance measurement (FBRM) provides the chord length distribution (CLD) of a population of particles in a suspension flowing close to the sensor window. Recovery of size and shape information from the CLD requires a model relating particle size and shape to its CLD as well as solving the corresponding inverse problem. This paper presents a comprehensive algorithm which produces estimates of particle size distribution and particle aspect ratio from measured CLD data. While the algorithm searches for a global best solution to the inverse problem without requiring further a priori information on the range of particle sizes present in the population or aspect ratio of particles, suitable regularisation techniques based on relevant additional information can be implemented as required to obtain physically reasonable size distributions. We used the algorithm to analyse CLD data for samples of needle-like crystalline particles of various lengths using two previously published CLD models for ellipsoids and for thin cylinders to estimate particle size distribution and shape. We found that the thin cylinder model yielded significantly better agreement with experimental data, while estimated particle size distributions and aspect ratios were in good agreement with those obtained from imaging. •An algorithm to get particle size and shape from chord length distribution is given.•It does not require any additional information about particle size range and shape.•It can be used with any optical or geometrical model for particle detection.