With the advent of automated imaging systems, it is now possible to obtain statistically significant size distributions using image analysis. This opens up a range of applications which can not be developed using more established techniques such as laser diffraction. The applications available to each technique are defined by their sensitivities to changes within the size distribution and the way the sample information is attached.
Laser diffraction represents a rapid, robust method for measuring the bulk properties of powders, emulsions and suspensions. It is an ensemble technique that measures millions of particles during any measurement and can make measurements over an extremely wide dynamic range. This makes the technique ideal for bulk sample measurements where materials may be polydisperse. As it is a volume-based technique, it is also very sensitive to the presence of over-sized material.
Image analysis offers a high-resolution technique for particle characterisation. Multiple size and shape parameters can be extracted for single particles, in contrast to ensemble techniques. This makes automated imaging systems ideal for detecting small differences in the morphology of materials that may affect powder-processing properties. As imaging is a number based technique, it is very sensitive to the presence of fine particles which are often presence in significant numbers, or small volumes, with a sample.
The table below contrasts laser diffraction and image analysis and provides some guidance as to which applications best suit each technique.
Imaging |
Laser Diffraction |
Produces Number Distributions
|
Produces Volume Distributions |
High Sensitivity to small particles |
High Sensitivity to over-sized material |
Specific Particle Properties |
Bulk Material Properties |
Resolves Precise Morphological Information |
Resolves Broad Size Distributions |
Presents Detailed Sample Information |
Provides Rapid Particle Characterisation |
Research and Diagnostic Tool |
Routine Sample Analysis Tool |
High Resolution and Sensitivity |
Robust, Reproducible Measurements |
Samples a Small Amount of Material |
Samples a Large amount of Material |