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Laser diffraction is a widely used particle sizing technique for materials ranging from hundreds of nanometers up to several millimeters in size. The main reasons for its success are:
Laser diffraction measures particle size distributions by measuring the angular variation in intensity of light scattered as a laser beam passes through a dispersed particulate sample. Large particles scatter light at small angles relative to the laser beam and small particles scatter light at large angles, as illustrated below. The angular scattering intensity data is then analyzed to calculate the size of the particles responsible for creating the scattering pattern, using the Mie theory of light scattering. The particle size is reported as a volume equivalent sphere diameter.
Laser diffraction uses Mie theory of light scattering to calculate the particle size distribution, assuming a volume equivalent sphere model.
Mie theory requires knowledge of the optical properties (refractive index and imaginary component) of both the sample being measured, along with the refractive index of the dispersant. Usually the optical properties of the dispersant are relatively easy to find from published data, and many modern instruments will have in-built databases that include common dispersants. For samples where the optical properties are not known, the user can either measure them or estimate them using an iterative approach based upon the goodness of fit between the modeled data and the actual data collected for the sample.
A simplified approach is to use the Fraunhofer approximation, which does not require knowledge of the optical properties of the sample. This can provide accurate results for large particles. However it should be used with caution whenever working with samples which might have particles below 50µm or where the particles are relatively transparent.
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Este webinario cubrirá el desarrollo de métodos para muestras dispersas en líquidos. Se hará un análisis de los factores que afectan la medición, como el muestreo y la dispersión, y la importancia relativa de estos factores en diferentes rangos de ta...
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(Webinar - Recorded)
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