Spectroscopic determination of particle size distribution in turbide systems

The quality of emulsions and suspensions is not only depending on their chemical composition, but also the size of the colloidal particles is a crucial factor. The particle size distribution (PSD) has an impact on the stability and the technical properties, like viscosity, of the product. For many products for example in the food industry, not only the basis product is, but also the processing and derivatives are influenced by the PSD. For example in the case of milk, the ease of creaming and the moisture retention in cheese depend on the size of the milk fat globules. The PSD is also an important factor concerning health: the efficiency of nutrient uptake in the gastrointestinal tract depends on the particle size.
Given the impact of the particle size distribution on the quality of the product, the PSD should be accurately monitored during before, during and after the production process. A lot of the techniques currently used for particle size measurements require dilution of dense emulsions and suspensions that are characterised by high light scattering. Moreover, the particle size distribution is often measured on a sample that is assumed to be representative for the entire batch of the product. Replacing such off-line methods by accurate optical in-line PSD measurements, would allow a faster detection of deviation in produced particle size and thus a faster adjustment of the production process if needed.
The goal of this research  is to develop an accurate method for particle size distribution determination of emulsions and suspensions, by combining spectroscopic measurements with light transport models. The sensor design  will be optimised for so that even for dense systems an accurate PSD estimation can be given without the need for sample preparation.
To start, an inverse micro-scale light transport model will be constructed based on analytic approximations of Mie theory. The model describes the relationship between the light scattering properties of the medium and the particle size distribution. First, this invers model will be elaborated for samples with a low volume concentration of scattering particles, i.e. samples for which the assumption of independent light scattering is valid. Secondly, this model will be extended to a to an inverse model that takes into account dependent scattering. Such model allows PSD estimation for dense systems with a high volume concentration of scattering particles. This inverse model to estimate particle size distributions from optical properties will be used in the insilico optimisation of a sensor design. By means of light transport simulation, the configuration of a spatially resolved reflectance sensor will be optimised for PSD measurements.
For the validation of results, a model system with well-known optical properties is used: suspensions of silica particles in water. Once the models and algorithms are validated on this system, they will be applied to two case studies from the agro-food industry: milk and sauces. These two systems can be seen as models for large variety of emulsions and suspensions from different sectors such as the agro-food industry, pharmacy, paint production,...