Particle size analysis

[3] Amongst its disadvantages is the fact that it does not properly resolve highly polydisperse samples, while the presence of large particles can affect size accuracy.

NTA also measures the hydrodynamic size of particles from the diffusion coefficient but is capable of overcoming some of the limitations posed by DLS.

In contrast to NTA, iNTA has a superior size resolution and gives access to the effective refractive index of the particles.

The light scattered by the particles in the forward direction is focused by a lens onto a large array of concentric photodetector rings.

Furthermore, their high price is mainly due to the use of expensive laser sources and a large number of detectors, i.e., one sensor for each scattering angle to be monitored.

An alternative method for PSD is cuvette-based SPR technique, that simultaneously measures the particle size ranging 10 nm-10 μm and concentration in a standard spectrophotometer.

To overcome this issue, LD PSAs require appropriate sampling and dilution systems, which increase capital investments and operational costs.

[12][13][14] However, these algorithms typically require implementing a complex correction, which increases the computation time and is often not suitable for online measurements.

[14] An alternative approach to compute the PSD without the use of optical models and complex correction factors is to apply machine learning (ML) techniques.

The method has found applications in proteomics and related fields where nano-sized particles may vary in size depending on their environment.

In the building industry, the particle size can directly affect the strength of the final material, as it observed for cement.

Furthermore, in the case of food emulsions, particle size analysis is relevant to predict stability and shelf-life, and optimize homogenization.

Sieving has long been the technique of choice for soil texture analysis, although laser diffraction instruments are increasingly used as they considerably speed up the analytical process, and provide highly reproducible results.

Wood particles used to make various types of products rely on particle-size analysis to maintain high quality standards.

DLS instruments are for instance part of the quality control process for mRNA vaccines formulated in lipid nanoparticle carriers.