Fabrication of superamphiphobic surfaces with controllable oil adhesion in air

Droplet impacting on pillared hydrophobic surfaces with different solid fractions

HYPOTHESIS

The solid fraction of the substrate is expected to influence the bouncing behavior of an impinging droplet, thereby affecting spreading and contact time. Hence, it should be possible to alter the velocity and pressure distribution of impacting droplet, and also affect the impact velocity for droplet penetration right upon impact.

SIMULATIONS

We systematically investigate the impact dynamics of water droplets on pillared hydrophobic surfaces with different solid fractions using phase-field simulations. The velocity and pressure distributions of impacting droplets on pillared hydrophobic surfaces with varied Weber numbers and solid fractions are studied. In addition, the influences of the solid fraction on the bouncing behaviors of the impinging droplet, such as the maximum wetting spreading, the maximum impacting depth, and the contact time, are also investigated to further understand the impact event.

FINDINGS

We show that a three-peak pressure profile appears on the top of the pillared hydrophobic surface during droplet impact by varying the solid fraction of the surface. The first peak is generated by the impact of the droplet itself, while the second peak arises from the droplet recoil impact associated with the dynamic properties of the jet. Moreover, we identify a hitherto unknown third pressure peak related to the hydrodynamic singularity that emerges due to the convergence of the fluid during the droplet rebound. This solid fraction-dependent impacting behavior reveals the intricate interplay between droplet dynamics and the underlying surface characteristics, providing valuable insights into the design and optimization of micro/nano structured hydrophobic surfaces for various applications.

Robust and durable liquid-repellent surfaces

This review provides a comprehensive summary of characterization, design, fabrication, and application of robust and durable liquid-repellent surfaces.

Modulation and Control of Wettability and Hardness of Zr-Based Metallic Glass via Facile Laser Surface Texturing

Bulk metallic glass (BMG) has received consistent attention from the research community owing to its superior physical and mechanical properties. Modulating and controlling the surface functionalities of BMG can be more interesting for the surface engineering community and will render more practical applications. In this work, a facile laser-based surface texturing technique is presented to modulate and control the surface functionalities (i.e., wettability and hardness) of Zr-based BMG. Laser surface texturing was first utilized to create periodic surface structures, and heat treatment was subsequently employed to control the surface chemistry. The experimental results indicate that the laser textured BMG surface became superhydrophilic immediately upon laser texturing, and it turned superhydrophobic after heat treatment. Through surface morphology and chemistry analyses, it was confirmed that the wettability transition could be ascribed to the combined effects of laser-induced periodic surface structure and controllable surface chemistry. In the meantime, the microhardness of the BMG surface has been remarkably increased as a result of laser surface texturing. The facile laser-based technique developed in this work has shown its effectiveness in modification and control of the surface functionalities for BMG, and it is expected to endow more useful applications.

Development of hydrophobic paper substrates using silane and sol-gel based processes and deriving the best coating technique using machine learning strategies

Low energy surface coatings have found wide range of applications for generating hydrophobic and superhydrophobic surfaces. Most of the studies have been related to use of a single coating material over a single substrate or using a single technique. The degree of hydrophobicity is highly dependent on fabrication processes as well as materials being coated and as such warrants a high-level study using experimental optimization leading to the evaluation of the parametric behavior of coatings and their application techniques. Also, a single platform or system which can predict the required set of parameters for generating hydrophobic surface of required nature for given substrate is of requirement. This work applies the powerful machine learning algorithms (Levenberg Marquardt using Gauss Newton and Gradient methods) to evaluate the various processes affecting the anti-wetting behavior of coated printable paper substrates with the capability to predict the most optimized method of coating and materials that may lead to a desirable surface contact angle. The major application techniques used for this study pertain to dip coating, spray coating, spin coating and inkjet printing and silane and sol-gel base coating materials.