Colloidal fat crystal network

A relatively new method to determine the fractal dimension is by using oil permeability measurements. In this method, the permeability coefficient, B, is measured for fat samples containing different SFC. This physical fractal dimension, the permeability fractal dimension. Dp, links the volumetric flow rate of liquid oil penetrating a colloidal fat crystal network with its SFC as (Bremer et al. 1989) ... 

Figure 17.24. General scheme used to measure the microscopy fractal dimension of a colloidal fat crystal network.

In addition two-dimensional imaging of polarized light micrographs of fat samples may be employed to determine the fractal dimension. The general scheme to measure the microscopy fractal dimension of a colloidal fat crystal network is shown in Figure 17.24. 

Tang, D., and Marangoni, A.G. (2006). Quantitative study on the mierostrueture of colloid fat crystal networks and fractal dimensions. Advanees in Colloid and Interface Science. 

In the case of fat crystal networks, fractal scaling is found between the size of a primary colloidal particle and a floe of primary particles (Marangoni 2005). 

This theory was first developed for colloidal aggregate networks and was later adapted to fat crystal networks (52-54). In colloidal systems (with a disordered distribution of mass and statistical self-similar patterns), the mass of a fractal aggregate (or the distribution of mass within a network), M, is related to the size of the object or region of interest (R) in a power-law fashion ... 

Vreeker, R., L.L. Hoekstra, D.C. den Boer, and W.G.M. Agterof, The Fractal Nature of Fat Crystal Networks, in Food Colloids and Polymers Stability and Mechanical Properties, edited by E. Dickinson and P. Walstra, The Royal Society of Chemistry, Cambrige, 1993, pp. 16-30. 

Now that all levels of the structural hierarchy within a fat crystal network are quantifiable (to various extents), as well as the amounts of solid fat within the network (by use mainly of pulsed nuclear magnetic resonance), it is important to relate these quantifiable parameters to rheological indicators such as the shear elastic modulus. One model to relate the microstructure to the shear elastic modulus was developed in colloidal physics by Shih et al. [57]. A brief chronology of the adaptation of this theory to the study of fat networks follows. 

Awad, T.S., Rogers, M.A., Marangoni, A.G. 2004. Scaling behavior of the elastic modulus in colloidal networks of fat crystals. J. Phys. Chem.B. 108, 171-179. 

According to W/O emulsion work by Lucassen-Reynders [34] droplet coverage is achieved only if the number of particles is much higher than the number of droplets. In her study, the number of tristearate crystals was 1000 times the number of droplets, indicating that half of the fat crystals flocculated in 1 s compared with 1000 s for the water droplets. Hence, the fat crystals were able to cover the droplets and form a network before any real droplet coalescence could occur, thereby stabilizing the emulsion. The network formation, however, also hindered the free diffusion of crystals to the interface. Without the presence of surfactants in the initial emulsion mix, no stabilization was observed. With added surfactant, however, crystal flocculation was reduced as the interparticle bond energy was lowered. Results showed that partial flocculation was best for W/O emulsion stabilization by tristearin. Lagaly et al. [114] also observed that surfactants aided the colloidal stabilization of emulsions. 

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