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Register a new userOptimization of Patterned Surfaces for Improved Superhydrophobicity Through Cost-Effective Large-Scale Computations
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The growing need for creating surfaces with specific wetting properties, such as superhyrdophobic behavior, asks for novel methods for their efficient design. In this work, a fast computational method for the evaluation of patterned superhyrdophobic surfaces is introduced. The hydrophobicity of a surface is quantified in energy terms through an objective function. The increased computational cost led to the parallelization of the method with the Message Passing Interface (MPI) communication protocol that enables calculations on distributed memory systems allowing for parametric investigations at acceptable time frames. The method is demonstrated for a surface consisting of an array of pillars with inverted conical (frustum) geometry. The parallel speedup achieved allows for low cost parametric investigations on the effect of the fine features (curvature and slopes) of the pillars on the superhydophobicity of the surface and consequently for the optimization of superhyrdophobic surfaces.
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A theory for wetting of structured solid surfaces is developed, based on the delta-comb periodic potential. It possesses two matching parameters: the effective line tension and the friction coefficient on the three-phase contact line at the surface. The theory is validated on the dynamics of spreading of liquid zinc droplets on morphologically patterned zinkophilic iron surface by means of square patterns of zinkophobic aluminum oxide. It is found that the effective line tension is negative and it has essential contribution to the dynamics of spreading. Thus, the theoretical analysis shows that the presence of lyophobic patterns situated on lyophilic surface makes the latter completely wettable, i.e. no equilibrium contact angle on such surface exists making the droplet spread completely in form of thin liquid layer on the patterned surface.
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Rough or textured hydrophobic surfaces are dubbed superhydrophobic due to their numerous desirable properties, such as water repellency and interfacial slip. Superhydrophobicity stems from an aversion for water to wet the surface texture, so that a water droplet in the superhydrophobic Cassie state, contacts only the tips of the rough hydrophobic surface. However, superhydrophobicity is remarkably fragile, and can break down due to the wetting of the surface texture to yield the Wenzel state under various conditions, such as elevated pressures or droplet impact. Moreover, due to large energetic barriers that impede the reverse (dewetting) transition, this breakdown in superhydrophobicity is widely believed to be irreversible. Using molecular simulations in conjunction with enhanced sampling techniques, here we show that on surfaces with nanoscale texture, water density fluctuations can lead to a reduction in the free energetic barriers to dewetting by circumventing the classical dewetting pathways. In particular, the fluctuation-mediated dewetting pathway involves a number of transitions between distinct dewetted morphologies, with each transition lowering the resistance to dewetting. Importantly, an understanding of the mechanistic pathways to dewetting and their dependence on pressure, allows us to augment the surface texture design, so that the barriers to dewetting are eliminated altogether and the Wenzel state becomes unstable at ambient conditions. Such robust surfaces, which defy classical expectations and can spontaneously recover their superhydrophobicity, could have widespread importance, from underwater operation to phase change heat transfer applications.
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