A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems

Comprehensive review of the interfacial behavior of water/oil/surfactant systems using dissipative particle dynamics simulation

A comprehensive understanding of interfacial behavior in water/oil/surfactant systems is critical to evaluating the performance of emulsions in various industries, specifically in the oil and gas industry. To gain fundamental knowledge regarding this interfacial behavior, atomistic methods, e.g., molecular dynamics (MD) simulation, can be employed; however, MD simulation cannot handle phenomena that require more than a million atoms. The coarse-grained mesoscale methods were introduced to resolve this issue. One of the most effective mesoscale coarse-grained approaches for simulating colloidal systems is dissipative particle dynamics (DPD), which bridges the gap between macroscopic time and length scales and molecular-scale simulation. This work reviews the fundamentals of DPD simulation and its progress on colloids and interface systems, especially surfactant/water/oil mixtures. The effects of temperature, salt content, a water/oil ratio, a shear rate, and a type of surfactant on the interfacial behavior in water/oil/surfactant systems using DPD simulation are evaluated. In addition, the obtained results are also investigated through the lens of the chemistry of surfactants and emulsions. The outcome of this comprehensive review demonstrates the importance of DPD simulation in various processes with a focus on the colloidal and interfacial behavior of surfactants at water-oil interfaces.

Using reactive dissipative particle dynamics to understand local shape manipulation of polymer vesicles

Biological cells have long been of interest to researchers due to their capacity to actively control their shape. Accordingly, there is significant interest in generating simplified synthetic protocells that can alter their shape based on an externally or internally generated stimulus. To date, most progress has been made towards controlling the global shape of a protocell, whereas less is known about generating a local shape change. Here, we seek to better understand the possible mechanisms for producing local morphological changes in a popular protocell system, the block copolymer vesicle. Accordingly, we have combined Dissipative Particle Dynamics (DPD) and the Split Reactive Brownian Dynamics algorithm (SRBD) to produce a simulation tool that is capable of modeling the dynamics of self-assembled polymer structures as they undergo chemical reactions. Using this Reactive DPD or RDPD method, we investigate local morphological change driven by either the microinjection of a stimulus or an enzymatically-produced stimulus. We find that sub-vesicle-scale morphological change can be induced by either a solvent stimulus that swells the vesicle membrane, or by a reactant stimulus that alters the chemistry of the block polymer in the membrane corona. Notably, the latter method results in a more persistent local deformation than the former, which we attribute to the slower diffusion of polymer chains relative to the solvent. We quantify this deformation and show that it can be modulated by altering the interaction parameter of the parts of the polymer chain that are affected by the stimulus.

Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method

We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication "A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems" (Drawert et al., 2019). We validate 1D diffusion, and 2D diffusion cases against their analytical solutions. We present graphs and tables of data showing the error in the simulation method.