Molecular dynamics simulations of surfactant adsorption at oil/water interface under shear flow
Source abstract
Abstract
Abstract Surfactants are extensively used in many chemical products to improve their stability, appearance, texture, and rheology. Precise control of the emulsion droplet size distribution, which depends on the characteristics of the surfactant used, is important for target-oriented product design. A complete understanding of the structures and dynamics of emulsion droplets at the reactor level requires coupling of two mesoscale physical constraints, that at the interfacial level, i.e., smaller than a single droplet (Mesoscale-1), and that at the device level, i.e., larger than a single droplet (Mesoscale-2). In this work, the structures and adsorption kinetics of Mesoscale-1 surfactant molecules were studied via coarse-grained molecular dynamics. A non-equilibrium model that could introduce stable shear flow into the simulation box was used to investigate the interfacial structures at the droplet interface under different shear rates. The configurations of the surfactant molecules and adsorption amounts were compared with those obtained without flow. The adsorption kinetics for different shear rates were compared to determine the effects of hydrodynamic interactions. The dominant mechanisms governing the dynamic structures can thus be summarized as maximization of the adsorption density at the interface and minimization of flow resistance in the bulk phase (water and/or oil molecules). A scheme for coupling between Mesoscale-1 and Mesoscale-2 is proposed. This method is promising for the incorporation of interfacial structure effects into the hydrodynamics at the reactor device level for the manipulation of chemical products.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Surfactants and Colloidal Systems · Pickering emulsions and particle stabilization · Innovative Microfluidic and Catalytic Techniques Innovation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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