ANTICORROSION PERFORMANCE OF SELF-HEALING POLYMERIC COATINGS ON LOW CARBON STEEL SUBSTRATES

التفاصيل البيبلوغرافية
العنوان: ANTICORROSION PERFORMANCE OF SELF-HEALING POLYMERIC COATINGS ON LOW CARBON STEEL SUBSTRATES
المؤلفون: Esah Hamzah, Mohd Fauzi Mamat, Muhammad Ashraff Ahmad Seri, Abdelsalam Ahdash
المصدر: Jurnal Teknologi. 79
بيانات النشر: Penerbit UTM Press, 2017.
سنة النشر: 2017
مصطلحات موضوعية: Materials science, Carbon steel, General Engineering, Epoxy, engineering.material, Corrosion, Coating, visual_art, Self-healing, engineering, Immersion (virtual reality), visual_art.visual_art_medium, Salt spray test, Composite material, Zeolite
الوصف: Recently, self-healing coating is classified as one of the smart coatings which has the ability to heal or repair damage of the coating to prevent further corrosion. The aim of this study is to synthesize the self-healing coatings from polymeric material and evaluate the performance and their corrosion behavior when coated on steel substrates. The corrosion tests were performed using immersion test and salt spray test method at room temperature. The immersion test shows that self-healing coating gives lower corrosion rate compared to pure epoxy paint, with a value of 0.02 and 0.05 mm/year respectively. Also, salt spray test shows similar trend as the immersion test, which is 0.11 and 0.19 mm/year for self-healing coating and pure epoxy paint respectively. While uncoated samples without any protection corroded at 0.89 mm/year. It was also found that the damage on self-healing coating was covered with zeolite from the microcapsules indicating that the self-healing agent was successfully synthesized and could function well. In other words, self-healing coating shows better corrosion resistance compared to the pure epoxy coating on steel substrate.
تدمد: 2180-3722
0127-9696
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::a5732e0e8624825fcd96b25550d3cf29Test
https://doi.org/10.11113/jt.v79.12268Test
رقم الانضمام: edsair.doi...........a5732e0e8624825fcd96b25550d3cf29
قاعدة البيانات: OpenAIRE