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Tuning the Superhydrophobic Properties of Hierarchical Nano-microstructural Silica Biomorph Arrays Grown at Triphasic Interfaces
The three-dimensional hierarchical morphology of surfaces greatly affects the wettability, absorption and microfabrication properties of their hybrid materials, however few scalable methods exist that controls simultaneously complex geometric shape and spatial scattered location and their physical p...
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Published in: | Scientific reports 2020-03, Vol.10 (1), p.4596-4596, Article 4596 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The three-dimensional hierarchical morphology of surfaces greatly affects the wettability, absorption and microfabrication properties of their hybrid materials, however few scalable methods exist that controls simultaneously complex geometric shape and spatial scattered location and their physical properties tuned. Consequently, this report describes a synthetic strategy that enables the position of well-ordered biomorph nano-microstructures on hydrophobic surfaces to be precisely controlled. The hierarchical architecture can be accurately positioned on polydimethylsiloxane (PDMS) surfaces in an unprecedented level by leveraging a solid/liquid/gas triphase dynamic reaction diffusion system strategy. The effect of salt concentrations, pH, CO
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levels, temperature and substrate patterning on this self-assembly process has been investigated, enabling protocols to be devised that enables the hydrophobic properties of the hierarchically assembled multiscale microstructures to be tuned as required. This combined top-down/bottom-up approach can be used to produce composites with outstanding hydrophobicity properties, affording superhydrophobic materials that are capable of retaining water droplets on their surfaces, even when the material is inverted by 180°, with a wide range of potential applications in oil/water separation technology and for selective cell recognition in biological systems. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-020-61530-0 |