The shape of particulates affects the performance of abrasives, pharmaceutical powders, agglomerate materials, chemical powders
including polymers and catalysts, industrial materials including Portland cement, such minerals as graphite or garnet, pigments, food
powders and many other common materials. Generally, size data is insufficient to predict behavior.
A few examples may be cited. In the pharmaceutical and other industries, the rate at which a substance dissolves is crucial.
Researchers have found that both particle size and shape, and the relation between size and shape, affect dissolution rates. Rates are
affected by such shape factors as aspect ratio, degree of flakiness, and smoothness of the surface. These factors have different
effects at different particle sizes.
Granular flow is critical in many industries, and particle shape plays a large role in granular processes. The settling
behavior of sediments and other materials in a liquid is important in civil engineering and in the manufacture of substrates, for
example. Settling velocities are greatly affected by shape and size.
Packing of irregular particles is another area where a particle shape analyzer can provide data that predict behavior.
How are particles analyzed for shape?
Granular particles may be spherical, more or less round but not spherical, elliptical in a general way, flat or flaky, fibrous, rod-
like, or irregular without fitting into any particular shape category. A shape analyzer should allow for all these different classes
of particle shape.
With generally round or elliptical particles, circularity, aspect ratio and smoothness are important. With straight rods or needles
the widths, lengths, and aspect ratios are what we need to know. With fibers, we want the straightened width and length, and the
degree of curl. Thin flakes can be analyzed with different shape models, depending on their general shape. With crystals and flakes,
where sides are faceted, software can fit irregular polygons to particles and quantize the polygon parameters.
A particle shape analyzer can accumulate histogram-type data on many shape parameters. The Particle Insight allows for six shape categories or models and
several measurement parameters within each model. The six shape models are
Circle model (7 size and shape measures)
Ellipse model (6 measures)
Rectangle model (4 measures)
Polygon model (3 measures)
Fiber model (4 measures)
Irregular model (4 measures)
What are the industry-standard methods of reporting size and shape data?
All particle measurement systems divide the size (or shape measure) axis into small classes, and counts in each class are accumulated. The result is
histogram data, which gives a good indication of the actual size or shape measure distribution. The larger the number of divisions, the better the
accuracy of results will be. From the histogram data, the standard measures of the distribution center and spread can be calculated. These include Mean, Standard deviation,
and Mode. The Particle Insight also determines Harmonic Mean, Coefficent of variance, and Skewness.
Another standard way of quantizing a distribution is to report cumulative percentiles. For example the 50th percentile is the value such that half
of the sample has size (or other measure) below that value. It is typical to report the 10%, 50% and 90% percentiles. The PI can report five percentiles
that are user-settable.
Instruments that can only determine numerical counts in the size classes, on the basis of a single size measure, report "number" data. These systems
must assume that particles are spheres in order to convert number data into surface area or volume data. Such results can be highly inaccurate if
particles are non-spherical. An image analyzer that has the ability to fit particles to shape patterns can determine area and volume data much more
accurately. An analyzer that accumulates data on every particle can compute mean, standard deviation etc. directly from that data without the need
for histograms, resulting in the highest possible accuracy of all measurement methods.
Ability to save data and a thumbnail image for every particle, as an option. This allows for several post-run processing operations including:
Reanalyze the sample using different limits on measures
View individual particle thumbnails
Define several classes of particles using limits on the measures, and generate separate statistics for those classes
Statistically correlate any two measures (scatter chart)
What technology does the Particle Insight use?
The instrument uses a closed-loop recirculating stream of particles in liquid suspension. Images of back-lit particles are strobed and captured
by a high-resolution CMOS monochrome camera. Image size is 5 megapixels, with a darkness digitization resolution of 256 gray levels. Telecentric
lenses are used for good depth of field. Lens powers available are 1X (for particles larger than 100 microns, nominally) and 5X (particles less
than 100 microns). Instrument control features include Fill, Drain, Rinse and Debubble.
Images are analyzed in real time as they come from the camera.
Software analyzes images using a variable gray level threshold, focus discrmination, pixel area limits, rejection based on shape settings, and
other parameters that can be optimized for the particular kind of particles present.
How do you analyze a sample using the Particle Insight?
Prepare a 30 mL or more sample of particles in liquid suspension. Particle density should be between 105 and 107 particles/mL for most acccurate results.
Start the Particle Insight application. Create a new sample file using New. Check and adjust settings:
Analysis Conditions control how images are analyzed.
Run Conditions determine run length and operations during and after the run, such as image saving or individual particle data saving.
Report and Display Options relate to the user interface and data reporting; they do not affect the results and can be modified later if needed.
Pour the sample into the sample well and activate the pump. Use Single, Continuous, and single image Analyze to check image quality and particle density.
Open any desired measure windows, so as to monitor those measures as the run proceeds.
Open System Performance Data to monitor run control parameters such as image and particle counts.
Click Clear and Start to begin the run. The run will end at the preset limits, and will be auto-saved if that option is on. A typical run of
20,000 particles will take 15 to 45 seconds depending on particle density.
Use Print to output run results to a printer or PDF file. Set report options in Report and Display Options.