CBET-EPSRC: Surfactant impact on drag reduction of superhydrophobic surfaces in turbulent flows

Superhydrophobic surfaces combine water repellency and microscale texture to yield several surprising and useful properties. When immersed in water, superhydrophobic surfaces can entrap an air layer inside microscopic cavities, potentially reducing friction drag between the liquid and the surface. Drag-reducing superhydrophobic surfaces could greatly reduce energy use, emissions, and cost for maritime transport, as well as in other applications.

However, superhydrophobic surfaces have shown inconsistent performance when tested in the laboratory or in the field in both laminar and turbulent flow conditions. Recent work has revealed that trace amounts of surfactants can significantly impair the drag-reduction performance in laminar flows. This observation has vast practical implications, since surfactants are naturally present in the environment and in engineering systems, often at large concentrations.

This project will investigate whether surfactant can also affect the performance of superhydrophobic surfaces in turbulent flows, explaining inconsistencies found in experimental tests, as well as the mismatch with existing models, which currently all ignore surfactant. The project will also develop public awareness about drag-reduction technology and its benefits through outreach programs with local communities.

The goal of this project is to uncover the impact of surfactant in realistic conditions, in order to identify practical mitigation strategies and unlock the drag-reduction potential of superhydrophobic surfaces for real-world applications. This will be pursued through the first-ever fundamental modelling investigation of superhydrophobic drag reduction in turbulent flow with surfactant, through a collaboration between the University of California, Santa Barbara (US) and the University of Manchester (UK).

A fully-resolved numerical simulation approach will be implemented, capable of representing surfactant-inclusive turbulent flow over superhydrophobic surfaces. The simulation approach will use advanced mesh refinement techniques, and will run on parallel supercomputers in order to reach flow regimes relevant to realistic conditions for maritime applications.

In addition, simpler theoretical models will be developed to identify and predict key phenomena. The theoretical models will also enable searching for likely regimes where drag reduction can be maximized, whereas the numerical simulations will provide a wealth of detailed information about the flow dynamics and the effect of surfactants, and will be used to validate the theoretical models.

The simulation results will also be made available online to other researchers seeking to advance the performance of superhydrophobic surfaces in the presence of surfactants.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.