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Bio-inspired Superhydrophobic Self-healing Surfaces with Synergistic Anticorrosion Performance
- Source :
- Journal of Bionic Engineering. 17:1196-1208
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- The past decade has witnessed significant efforts in addressing the global metallic corrosion challenge, with a focus on avoiding or mitigating huge economic losses incurred by corrosion and on the development of protective coatings on metals. Herein, a synergistic anticorrosion coating with both superhydrophobicity and self-healing properties was reported, through a facile replica molding method by mixing the polyvinylidene fluoride (PVDF) matrix with nano-sized SiO2 particles and 2-mercaptobenzothiazole (MBT) loaded halloysites (HNTs). The surface exhibits robust self-cleaning behavior under harsh conditions and high liquid repellence to withstand the osmosis of corrosive ions. The self-healing performance of the coating, due to the introduction of MBT-loaded HNTs, enhances the anticorrosion capability, which is still valid once the protective layer is damaged. Potentiodynamic polarization (PDP) and Electrochemical Impedance Spectroscopy (EIS) measurements demonstrate that the synergetic effects in anticorrosion performances significantly enhance the long-term corrosion protection of metals. Hence, this type of dual-action coating may find unique applications in metal corrosion resistance where both super-repellency and self-healing properties are desired.
- Subjects :
- Materials science
0206 medical engineering
Biophysics
Bioengineering
Nanotechnology
02 engineering and technology
engineering.material
021001 nanoscience & nanotechnology
020601 biomedical engineering
Polyvinylidene fluoride
Corrosion
Dielectric spectroscopy
Metal
Replica molding
chemistry.chemical_compound
Coating
chemistry
Self-healing
visual_art
engineering
visual_art.visual_art_medium
0210 nano-technology
Layer (electronics)
Biotechnology
Subjects
Details
- ISSN :
- 25432141 and 16726529
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Journal of Bionic Engineering
- Accession number :
- edsair.doi...........4270e4024b8dd0cb8b9c5539a7ee1c1b
- Full Text :
- https://doi.org/10.1007/s42235-020-0094-4