Jacob Wagner with João Maia, Dept. of Macromolecular Science and Engneering
Simulation of Droplet Breakup by dissipative particle dynamics (DPD)
Coarse grained (CG) simulation methods, such as CG molecular dynamics and Stokesian dynamics, are normally used to gain a better understanding of mesoscopic phenomena. Hoogerbrugge and Koelman proposed a new simulation method called Dissipative Particle Dynamics (DPD) in 1992, which has a variety of applications, including Newtonian fluids, colloidal suspensions, emulsion, polymer solutions, polymer melts, polymer blend, diblock copolymer, polymer nano-composites, and so on. Recently, shear thickening of dense colloidal suspension have been reported by resorting to core-potential. As to polymeric systems, phase separation of polymer blend and diblock copolymer is reasonably reproduced, whereas the dynamics of polymer chains of polymer melts cannot be reproduced well due to soft potential used in DPD. Entanglement forces have been considered for entanglement effect, which should be the key for dynamics. Lahmar et al. recently proposed a simulation DPD method coupled with Monte Carlo (MC) method that provides Gaussian statistics and 3.2-power law on viscosity, which are reasonable, but shows unphysical properties such as non-Gaussian bond length distribution and no sign of entangled structures in the radius of gyration. This thesis will apply a new DPD simulation method recently developed by the Maia group [1], whose coarse-grained level is tunable, to capture the Physics of droplet break-up in micro- and nano-emulsions. We will focus on the interplay between droplet size and the stress level in shear and extensional flows to determine the break-up dynamics and will try, in particular, to correctly predict computationally the well-known Grace plot.