0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessSelf-healing coatings with capsules containing healing agents have been developed for the corrosion protection of metal. In this paper, polyurethane capsules were synthesized under different conditions to examine the size and shape of capsules, and self-healing ability of coatings with capsules dispersed was examined after damaging the coated layer by scratching with a cutter blade. The size and shape of capsules depended on the concentration of chlorobenzene in cyclohexanone used as a solvent of prepolymer solution. The capsule formed with 70 % of chlorobenzene gave a self-healing capability to the coated layer by releasing the healing agent after damaging. The amount of glycerol added for the formation of the polyurethane capsule shell affected the self-healing ability of the coated layer. The coating with the capsule formed with small amounts of glycerol showed a high healing ability, while, with large amounts of glycerol, the self-healing ability was relatively low.
Makoto Chiba, Kazuki Anetai, Chinami Yamada, Yuki Sato, Haruka Okuyama, Minori Sugiura, Sven Pletincx, Hilke Verbruggen, Atsushi Hyono, Iris De Graeve, Herman Terryn, Hideaki Takahashi (2017). Development of Self-Healing Coatings with Micro Capsules for Corrosion Protection of Metal. ECS Transactions, 75(27), pp. 89-99, DOI: 10.1149/07527.0089ecst.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2017
Authors
12
Datasets
0
Total Files
0
Language
English
Journal
ECS Transactions
DOI
10.1149/07527.0089ecst
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access