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Updated: Mar 22, 2026

Fabrication of Superhydrophobic Metal Surfaces for Anti-Icing Applications
Published on: August 15, 2018
Development of hydrophobic surface substrates enabling reproducible drop-and-dry spectroscopic measurements
Jinah Lee1, Pham Khac Duy1, Seok Chan Park2
1Department of Chemistry and Research Institute for Convergence of Basic Sciences, Hanyang University, Seoul 133-791, Republic of Korea.
Abstract:
We investigated several spectroscopic substrates with hydrophobic surfaces that were able to form reproducible droplets of aqueous samples for reliable high throughput drop-and-dry measurements. An amine-coated substrate, a polytetrafluoroethylene (PTFE) disk, and a perfluorooctyltrichlorosilane (FTS) coated substrate were prepared and initially evaluated for use in the determination of fat concentrations in milks using near-infrared (NIR) spectroscopy. Since the dried milk spots were not compositionally uniform due to the localization of components during sample drying, NIR spectra were collected by fully covering each spot to ensure a correct compositional representation of the sample. The amine-coated substrate yielded more reproducible dried milk patterns because its hydrophobicity was optimal for loading an appropriate amount of milk with decreased component localization after drying. The relative standard deviation (RSD) of the absorbance at 4330cm(-1) was 1.0%, thereby resulting in the more accurate determination of fat concentration. In addition, infrared (IR) spectroscopic discrimination between wild and transgenic tobaccos using their extracts was attempted. The extracted metabolites had a low concentration, so an FTS-coated CaF2 substrate that maximized sample loading was used to improve measurement sensitivity and produce reproducible droplets. The RSD of the absorbance at 1070cm(-1) was only 0.8%. Our strategy produced droplets that had consistent sizes and provided reproducible IR spectral features, which enabled the differentiation between wild and transgenic tobacco groups in the principal component (PC) score domain.

