Determination of Particle Size Distributions of Bulk Samples Using Micro-Computed Tomography and Artificial Intelligence
- Resource Type
- article
- Authors
- Stefan Höving; Laura Neuendorf; Timo Betting; Norbert Kockmann
- Source
- Materials, Vol 16, Iss 3, p 1002 (2023)
- Subject
- determination of particle size distributions
three dimensional particle analysis in bulk
micro-computed tomography
Mask–RCNN
Wadell sphericity
Technology
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Engineering (General). Civil engineering (General)
TA1-2040
Microscopy
QH201-278.5
Descriptive and experimental mechanics
QC120-168.85
- Language
- English
- ISSN
- 1996-1944
The knowledge of product particle size distribution (PSD) in crystallization processes is of high interest for the pharmaceutical and fine chemical industries, as well as in research and development. Not only can the efficiency of crystallization/production processes and product quality be increased but also new equipment can be qualitatively characterized. A large variety of analytical methods for PSDs is available, most of which have underlying assumptions and corresponding errors affecting the measurement of the volume of individual particles. In this work we present a method for the determination of particle volumes in a bulk sample via micro-computed tomography and the application of artificial intelligence. The particle size of bulk samples of sucrose were measured with this method and compared to classical indirect measurement methods. Advantages of the workflow are presented.