College

Starch particle size was determined using laser diffraction by suspending the sample in air, sufficient to produce obscuration of 15%. The test showed that:

- 90% of particles have a size of 59.1 μm,
- 50% of particles have a size of 42.6 μm,
- 10% of particles have a size of 10.11 μm.

Find the particle size distribution. What is your comment?

Answer :

Final answer:

The particle size distribution of starch particles can be understood through values representing the cumulative frequencies of particle diameters, with 90%, 50%, and 10% of particles falling below 59.1, 42.6, and 10.11 micrometers respectively. The span value, derived from these measurements, provides insight into the uniformity of the particle sizes. The accuracy of these measurements may vary depending on the characteristics of the suspension and limitations of the DLS method.

Explanation:

Particle Size Distribution

The student has presented data from a laser diffraction test indicating the particle size distribution for starch particles suspended in air. The key values given are that 90% of particles are at or below 59.1 µm (D90), 50% are at or below 42.6 µm (D50), and 10% are at or below 10.11 µm (D10). These values represent the cumulative size distribution of the particles and can be plotted on a graph to visually understand the distribution.

To comment on the distribution, one widely used measure is the span, which is defined as (D90-D10)/D50. Using the data provided, (59.1 µm - 10.11 µm) / 42.6 µm gives a span value, which can indicate how broad or narrow the particle size distribution is. A smaller span suggests a more uniform particle size, whereas a larger span indicates a wider variance in size.

In terms of reliability and sample preparation mentioned in the context, it's important to note that the Dynamic Light Scattering (DLS) method used has strengths and weaknesses based on particle size and solution properties. DLS is generally reliable for monodisperse or stability-controlled polydisperse suspensions within certain size ranges but may not be as reliable for heterogeneous samples or those containing large aggregates.