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High-speed Particle Image Velocimetry Near Surfaces

High-speed Particle Image Velocimetry Near Surfaces

Published on: June 24, 2013

Rapid particle size measurement using 3D surface imaging.

Ira Soppela¹, Sari Airaksinen, Juha Hatara

¹Division of Pharmaceutical Technology, Faculty of Pharmacy, University of Helsinki, Finland. ira.soppela@helsinki.fi

AAPS Pharmscitech

|April 12, 2011

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A new 3D surface imaging technique analyzes granule particle size and shape. This photometric approach offers rapid, visual characterization, aiding flowability screening.

Area of Science:

Materials Science
Analytical Chemistry
Chemical Engineering

Background:

Accurate characterization of granular materials is crucial for industrial processes.
Traditional methods for particle size distribution analysis can be time-consuming and lack detailed surface information.
Evaluating granule flowability requires understanding surface properties like roughness and shape.

Purpose of the Study:

To introduce and validate a novel three-dimensional (3D) surface image analysis technique for granular materials.
To compare the performance of the new 3D imaging method against established techniques like sieve analysis and spatial filtering.
To assess the utility of the 3D imaging approach for rapid flowability screening of granular samples.

Main Methods:

Utilized white light illumination from multiple incident angles to generate 3D surface models via a photometric approach.

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Applied the derived 3D surface features for the characterization of particle size distributions in granules.

Conducted comparative analysis using approximately 30 granule batches against sieve analysis and spatial filtering particle sizing methods.

Evaluated the technique's effectiveness in flowability screening of granular materials.

Main Results:

The new 3D imaging technique successfully characterized particle size distributions of granules.
Demonstrated comparable results to sieve analysis and spatial filtering methods across numerous granule batches.
The method provided valuable visual insights into granule surface characteristics, including roughness and particle shape.
The 3D imaging approach proved effective for rapid analysis and visual assessment.

Conclusions:

The developed 3D surface image analysis technique provides a rapid and visually informative method for granular material characterization.
This novel approach is suitable for determining particle size distributions and assessing surface properties.
The technique shows promise for efficient flowability screening, offering advantages in speed and data richness over traditional methods.