Highlights

In brief

Simulations capturing how water droplets interact with surfaces could lead to the design of better water-repelling materials.

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Simulating a water droplet

2 Apr 2021

An integrated simulation model provides a clearer picture of what happens when a water droplet comes in contact with a hydrophobic surface.

Most of us can recall the anguish of accidentally hitting over a cup of coffee and wetting the table. From a layman’s perspective, this is a classic example of the wetting phenomena. But it belies the significance of wetting in industrial applications—the behavior of a liquid while maintaining contact with a solid surface is crucial in the design of coatings and surfactants, such as those used in shampoos or paints.

“In general, surfaces can be simplified as either hydrophobic or hydrophilic. The process of wetting, however, is much more complicated. The texture of the surface, for example, as well as its contact angle with an incoming droplet of water, are important factors to consider,” explained Shuai Chen, a Research Scientist at A*STAR’s Institute of High Performance Computing (IHPC) and the first author on a study that describes an integrated model of wetting.

Although computational scientists have long relied on a simulation method called molecular dynamics (MD) to predict the water contact angle of surfaces, MD is restricted to atoms and molecules at the nanoscale and fails to take into account the micro- and macrostructures of a surface. “Also, MD simulations can only be performed for short time scales and thus cannot be used to predict sliding and bouncing of water on surfaces,” Chen added.

To overcome the limitations of MD simulations, Chen and colleagues employed a multiscale modeling strategy combining MD with computational flow dynamics (CFD), which effectively expands the model’s field of view across space and time.

In MD simulations, they showed that the water contact angle of a water droplet on smooth polydimethylsiloxane (PDMS) surface could be widened by adding fluorocarbon chains on the surface. These simulation results were validated in experiments with C8F17-functionalized PDMS surfaces.

Experimental measurements also showed that altering the surface microstructure of PDMS by adding silica filler particles could maximize its hydrophobicity, obtaining the highest hydrophobicity with an optimum concentration of around 7.5 weight percent of silica.

To complete the picture of wetting at the microscale, the researchers used CFD simulations to show how a drop of water slides along an inclined surface. For the case of a surface with a small slope, the droplet slides along the surface, but when surface hydrophobicity is enhanced, the droplet bounces after it hits the surface. These findings were confirmed experimentally with PDMS surfaces.

“Fine-tuning the surface energy of coatings through experimental trial-and-error is tedious and time-consuming,” Chen said. “Theoretical models provide useful guidelines for the virtual testing of an experimental formulation, and thus can accelerate the design of an optimal hydrophobic surface.”

The A*STAR-affiliated researchers contributing to this research are from the Institute of High Performance Computing (IHPC) and the Singapore Institute of Manufacturing Technology (SIMTech).

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References

Chen, S., Yune, J.H.R., Zhang, Z., Liu, Z., Sridhar, N., et al. Multiscale Modeling to Predict the Hydrophobicity of an Experimentally Designed Coating, The Journal of Physical Chemistry 124, 9866-9874 (2020) | article

About the Researcher

Shuai Chen is a Research Scientist at A*STAR’s Institute of High Performance Computing (IHPC). He obtained his PhD degree in mechanical engineering from Tsinghua University, China, and subsequently joined IHPC in 2016. Chen’s research interests are focused on using multiscale computational tools to investigate the growth, structure and property of materials, including 2D materials, high-entropy alloys and polymers.

This article was made for A*STAR Research by Wildtype Media Group