Skip to content Skip to navigation

Particle-laden Droplet Removal from Superhydrophobic Surfaces: A Computational Study

Event Type: 
Date and Time: 
Friday, April 29, 2016 - 16:00
CTR Conference Room 103
Event Sponsor: 
Parviz Moin, Director of Center for Turbulence Research
Samaneh Farokhirad, Postdoctoral Research Associate and Adjunct Lecturer, CCNY


Interface-driven fluid dynamics is one of the recent interesting and challenging phenomena in fluid dynamics problems. Self-propulsion of droplets on superhydrophobic surfaces is one example of such phenomena, in which the fluid has a tendency to flow towards regions of higher surface energy, and subsequently a net flow results in the droplet motion. Rapid removal of self-propelled droplets from the surface is an essential factor in terms of expense and efficiency for many applications, including self-cleaning and enhanced heat and mass transfer to save energy and natural resources. Self-cleaning surfaces found in nature show great potential for application in many fields, ranging from industry to medicine. A potential mechanism for self-cleaning of natural surfaces in places with no precipitation is coalescence-induced self-propelled jumping of droplets, which was first reported in Phys. Rev. Lett. 103, 184501 (2009).  The micro- and nanostructures of natural surfaces help the dew droplets to coalesce, become bigger, and finally jump several millimeters into the air to carry unwanted particles, such as microbial and virus particles off the surface. This process requires neither gravity nor wind and provides a fundamentally different self-cleaning mechanism than the conventional lotus effect. This talk focuses on the influences of the ambient environment and particle presence on the development of a rapid self-cleaning mechanism using a three-dimensional Lattice Boltzmann Method (LBM). As a diffuse interface method, LBM links microscopic phenomena with the continuum macroscopic equations, and is suitable for simulations of complex fluid flow problems, including single-phase and multiphase flows, particle-laden flows, turbulent flows, and free surface problems. The fact that the nonlinear flow physics is fully contained in the local collision process makes LBM method readily parallelizable.

Samaneh Farokhirad graduated with a Bachelor of Science in Mechanical Engineering from Sharif University of Technology in 2006, and received her Master of Science in Mechanical Engineering from Iran University of Science and Technology in 2009. Then, she joined the Computational Multiphase Fluid Dynamics Group at the City College of New York, where she has collaborated with researchers from different fields including engineering, physics, and applied mathematics. After concluding her PhD in 2015, she has been working as a postdoctoral research associate and adjunct lecturer at CCNY. Samaneh Farokhirad’s main research interests are particle-laden multiphase flow and high performance computing.