How statistical physics can help to predict mass transport properties in complex food products

This work illustrates how principles of statistical physics including random walks, micro-reversibility and partition functions can be used to derive effective transport properties in complex materials such as food materials. A general formulation based on continuous Langevin Dynamics is proposed to calculate effective diffusivities in emulsions up to the percolation threshold. Interface conditions assuming either reflections or transmissions are used to account for possible partitioning between phases and could be extended to the interactions with macromolecules. The effective properties simulated in 2D emulsions for a wide range of conditions are compared with the analytical core-shell model proposed by Kalnin and Kotomin (1998) for low dense emulsions. The effects were classified in decreasing importance order as follows: ratio of diffusion coefficients, r(D) = [10(-2),10(2)], partition coefficients between the continuous and disperse phases, K = [10(-2),+infinity], globule densities, d = [0.1,0.4], and morphologies. The effects of r(D), K and d were nonlinearly coupled in a way that depended on the morphology of the emulsion: heterogeneity in the size of globules, packing of globules, quasi-continuity between globules.