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Number or Volume-Based Reporting?

Which method of reporting is appropriate for your particle sizing/characterization application?

Angelo DePalma, PhD

Angelo DePalma is a freelance writer living in Newton, New Jersey. You can reach him at

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particle sizing

Because number-based imaging techniques are sensitive to the presence of fines, they are useful for detecting low levels of material that is finer than the bulk of the sample.

Volume reporting, on the other hand, as delivered by laser diffraction, is useful for determining the amount of sample lying within an optical size range and for detecting the presence of large particles, such as oversized primary particles or agglomerates within pharmaceutical powders or suspensions.

Only perfect spheres may be precisely characterized using a single parameter, but these rarely occur in industry. For all other particles, the reported size parameter is related to the measurement technique used.

“The reporting associated with a given technique is directly linked to that method, making certain techniques inherently more or less suitable for specific applications,” says Dr. Paul Kippax, product group manager at Malvern Instruments (Malvern, UK). “However, data for a given technique are routinely manipulated to present information in ways that optimize its relevance.”

Close scrutiny of laser diffraction and image analysis illustrates the practical implications of spherical equivalence, defined as the diameter of a spherical particle with volume equivalent to that of the irregularly shaped particle.

Laser diffraction is an ensemble sizing technique, meaning it generates a result for the whole sample through one measurement. The reported particle size metric is the diameter of a sphere of the same volume as the particle; size distributions are generated on the basis of the volume of the sample in each size fraction.

Related Article: In Particle Sizing, Static and Dynamic Imaging Provide Pros and Cons

Alternately, image analyzers capture thousands of images of individual particles and use the dimensions of each to create statistically relevant size and shape distributions. “Here the reported particle size metric is the diameter of a circle with the same 2D surface area as the particle. And because distributions are built up from data for individual particles, they are number-based; that is, the distributions quantify the number of particles in each size fraction,” Kippax says.

Converting particle size data from one format to another requires consideration of both the size parameter and the distribution basis. “If particles are close to spherical, then the equivalent volume and equivalent area metrics will typically be similar. However, for other particles, those that are needle-shaped, for example, these numbers will clearly be very different,” Kippax adds.

Imaging analysis

FlowCam® from Fluid Imaging Technologies (Scarborough, ME) is an example of imaging analysis. It works by capturing images of the sample as it passes through a flow cell, and storing digital representations of each particle in software. This allows measurement of more than 20 characteristics for each particle, generating both size frequency and volume data.

Historically, most particle analyses were volumetric, measuring some characteristic that is proportional to particle volumes. “But this requires a leap of faith,” says Fluid Imaging technical director Lew Brown. “You’re assuming that everything is spherical, so if it has a certain volume it must have a specific diameter.”

Related Article: Diverse, Complimentary Techniques

In real-life samples, number and volumetric distributions are very different. A sample containing one million tiny particles and a few very large particles will be skewed heavily toward the smaller particles if number or frequency analysis is desired, whereas volume reporting favors the larger particles.

Brown estimates that today’s particle analyzers work in volume mode about 90 percent of the time. “Historically, before all this technology emerged, the most common sizing technique was sieving, which by definition is volumetric.”

The question of volume versus frequency becomes complex for foods and drugs. The patent for a popular peanut butter brand is based on particle size frequency for the ground peanuts. For chocolate, sugar crystal volume might be one of the defining contributors to taste and texture. Particle shape is also critical for taste because the shape may influence how the particle interacts with taste buds or even chemical receptors on the tongue. Similarly, shape may affect how quickly and where in the digestive tract a drug dissolves.

For additional resources on particle sizing, including useful articles and a list of manufacturers, visit