Abstract

Many surfaces in nature possessing superhydrophobicity have hierarchical (nano- and micro- scale) structures. A three-dimensional (3-D) model of cylindrical hierarchical nanostructured is established to describe the superhydrophobicity of solid surface. Based on thermodynamic analysis, the expressions of free energy (FE) and free energy barrier (FEB) for four precisely different wetting states are established and theoretically discussed. This approach provides theoretical guidance for predicting the dynamic contact angle (CA), static CA and CA hysteresis (CAH). Additionally, the actual three-phase contact line with droplet motion has been simulated, and the process of droplet advancing and receding is closely linked with the movement of contact line. To a great extent, the transition between different wetting states go hand in hand with that of the cylinder height and base spacing of nanostructure. Under the existing geometric parameters, when the nano-cylinders height reaches 1.5 × 10 −7 m, 2.36 × 10 −7 m, 2.56 × 10 −7 m, or when the nano-cylinders base spacing reaches 2.4 × 10 −7 m, 2.65 × 10 −7 m, 3.2 × 10 −7 m, the system will have a transition between different wetting states. Combined with the existing literature data and our experimental results support the correctness of the theoretical research, which are helpful for designing dual-scale hierarchical structure surfaces for researching the wetting behavior of advanced superhydrophobic materials. • A three-dimensional micro/nano model of hierarchical cylindrical structure is proposed and analyzed for the first time. • The single and synergistic effects of the uniform geometric parameters of micron and nanometer on the wettability of the system are discussed. • The critical expressions (Nanometer cylinder height and base spacing) of transition between any two wetting states (existence) are given. • The final stable wetting state of the system can be accurately predicted. • By controlling the micro/nano parameters, the stable wetting state of the hierarchical structure system can be predicted.

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