Choi, Wonjae
Permanent URI for this collectionhttps://hdl.handle.net/10735.1/3944
Wonjae Choi is an Assistant Professor of Mechanical Engineering his research interests are interdisciplinary and include:
- Small scale fluid mechanics
- Wetting/non-wetting characteristics of nano-engineered surfaces
- Microfluidics
- Hemodynamics
Browse
Browsing Choi, Wonjae by Issue Date
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Influence of Textural Statistics on Drag Reduction by Scalable, Randomly Rough Superhydrophobic Surfaces in Turbulent Flow(American Institute of Physics Inc., 2019-04-22) Rajappan, A.; Golovin, K.; Tobelmann, B.; Pillutla, Venkata; Abhijeet; Choi, Wonjae; Tuteja, A.; Mckinley, G. H.; Pillutla, Venkata; Abhijeet; Choi, WonjaeWe investigate the influence of statistical measures of surface roughness on the turbulent drag reduction (DR) performance of four scalable, randomly rough superhydrophobic (SH) textures. Each surface was fabricated using readily scalable surface texturing processes to generate a random, self-affine height profile on the base substrate. The frictional drag on all four SH surfaces was measured when fully submerged in shear-driven turbulent flow inside a bespoke Taylor-Couette apparatus at Reynolds numbers in the range 1 × 10⁴ ≲ Re ≲ 1 × 10⁵. An "effective" slip length quantifying the overall drag-reducing ability for each surface was extracted from the resulting Prandtl-von Kármán friction plots. Reductions in the frictional drag of up to 26% were observed, with one of the hierarchically textured surfaces exceeding a wall shear stress of 26 Pa (corresponding to a Reynolds number Re ≈ 7 × 10⁴) before the onset of flow-induced plastron collapse. The surface morphology of each texture was characterized using noncontact optical profilometry, and the influence of various statistical measures of roughness on the effective slip length was explored. The lateral autocorrelation length was identified as the key textural parameter determining the drag-reducing ability for randomly rough SH textures, playing the role analogous to the spatial periodicity of regularly patterned SH surfaces. A large autocorrelation length, a small surface roughness, and the presence of hierarchical roughness features were observed to be the three important design requirements for scalable SH textures for optimal DR in turbulent flows. © 2019 Author(s).Item A Stacked Polymer Film for Robust Superhydrophobic FabricsYoo, Youngmin; You, Jae Bem; Choi, Wonjae; Im, Sung GapA robust superhydrophobic fabric was achieved by depositing a stacked polymer film composed of a poly(1,3,5,7-tetravinyl-1,3,5,7-tetramethylcyclotetrasiloxane) (p(V4D4)) layer and a poly(1H,1H,2H,2H-perfluorodecylacrylate) (p(PFDA)) layer. The polymer film was deposited by initiated chemical vapor deposition (iCVD), a solventless process that allows conformal coating of the stacked polymer film on various micro-structured substrates. The two polymeric layers most likely formed a covalent bonding at their interface, and thus the stacked polymer film was characterized by both strong hydrophobicity and enhanced mechanical robustness originated from highly cross-linked p(V4D4) and p(PFDA). The surface topography of superhydrophobic coating was systematically tunable by controlling the operating parameters of iCVD process and a hierarchical structure was obtained by a simple one-step iCVD process. The film was also highly transparent in the wavelength range from 380 nm to 780 nm. Fabrics coated with this stacked polymer film displayed chemical robustness even after exposure to different chemicals including acetone, toluene, H2SO4, and KOH. The fabric also maintained its water repellency even after 20 000 cycles of the abrasion test and after 75 cycles of the laundry test.