Using Dissipative Particle Dynamics to Model Sheared Edible Oils as Complex Fluids

Abstract

This thesis summarises the use of the computational algorithm Dissipative Particle Dynamics (DPD) to investigate structure formation at the nanoscale in sheared edible oils. Pure edible oils at room temperature are typically a mixture of solid and liquid triglycerides. The solid elements interact via weak van der Waals interactions which drive the formation of a fat crystal network. This network is fractal and traps liquid oil, which is fundamental for the sensory characteristics and stability of many fatty food products. There is a need to link structure of fats to functionality in order to engineer healthier products. Shear is ubiquitous in the food processing industry and has been shown to greatly affect structure formation during crystallisation. The mesoscopic fluid model DPD was selected to simulate the aggregation of solid fats under laminar shear. The results have yielded predictions that could be investigated via Rheometry and Ultra Small Angle X-ray Scattering.