Edible oil structures at low and intermediate concentrations. I. Modeling, computer simulation, and predictions for X ray scattering

Abstract

Triacylglycerols (TAGs) are biologically important molecules which form the recently discovered highly anisotropic crystalline nanoplatelets (CNPs) and, ultimately, the large-scale fat crystal networks in edible oils. Identifying the hierarchies of these networks and how they spontaneously self-assemble is important to understanding their functionality and oil binding capacity. We have modelled CNPs and studied how they aggregate under the assumption that all CNPs are present before aggregation begins and that their solubility in the liquid oil is very low. We represented CNPs as rigid planar arrays of spheres with diameter ≈50 nm and defined the interaction between spheres in terms of a Hamaker coefficient, A, and a binding energy, VB. We studied three cases: weak binding, |VB|/kBT ≪ 1, physically realistic binding, VB = Vd(R, Δ), so that |VB|/kBT ≈ 1, and Strong binding with |VB|/kBT ≫ 1. We divided the concentration of CNPs, ϕ, with 0≤ϕ= 10−2 (solid fat content) ≤1, into two regions: Low and intermediate concentrations with 0<ϕ<0.25 and high concentrations with 0.25 < ϕ and considered only the first case. We employed Monte Carlo computer simulation to model CNP aggregation and analyzed them using static structure functions, S(q). We found that strong binding cases formed aggregates with fractal dimension, D, 1.7≤D≤1.8, in accord with diffusion limited cluster-cluster aggregation (DLCA) and weak binding formed aggregates with D=3, indicating a random distribution of CNPs. We found that models with physically realistic intermediate binding energies formed linear multilayer stacks of CNPs (TAGwoods) with fractal dimension D=1 for ϕ=0.06,0.13, and 0.22. TAGwood lengths were greater at lower ϕ than at higher ϕ, where some of the aggregates appeared as thick CNPs. We increased the spatial scale and modelled the TAGwoods as rigid linear arrays of spheres of diameter ≈500 nm, interacting via the attractive van der Waals interaction. We found that TAGwoods aggregated via DLCA into clusters with fractal dimension D=1.7−1.8. As the simulations were run further, TAGwoods relaxed their positions in order to maximize the attractive interaction making the process look like reaction limited cluster-cluster aggregation with the fractal dimension increasing to D=2.0−2.1. For higher concentrations of CNPs, many TAGwood clusters were formed and, because of their weak interactions, were distributed randomly with D=3.0. We summarize the hierarchy of structures and make predictions for X-ray scattering.