Hydroxyapatite coating for control degradation and parametric optimization of pure magnesium: an electrophoretic deposition technique for biodegradable implants

JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T(2023)

引用 0|浏览2
暂无评分
摘要
Design of orthopedic implants is a challenging task to cope with desired properties, therefore, numerous metal-alloy and coating were utilized in the fabrication of implants as alternative options. Magnesium (Mg)-based alloys are among the unique materials owing to their promising properties to avoid cytotoxicity, genotoxicity, and carcinogenicity; however, the fast degradation of Mg limits its clinical applications. In this study, hydroxyapatite (HA) nano-powder was coated on pure Mg as the compositions of both materials are promising biodegradable bone-compatible materials. The electrophoretic deposition (EPD) technique was used to produce a bioactive coating on pure Mg. The research novelty highlighted for the first time, the EPD parameters were optimized via the full Design of Experiment (DoF) approach during HA coating of Mg, while the weight loss of pure Mg and HA coated Mg were investigated in SBF for 7, 14, 21, and 28 days. The surface morphologies of both materials were investigated before and after coating. The bioactivity of the coated samples was examined in Simulated Body Fluid (SBF) and investigated using SEM. Surface roughness, contact angle measurement, scratch test, wear test, an in-vitro study in SBF, electrochemical corrosion, and cellular studies were conducted according to the standard approaches. The results show that HA coated Mg samples are compatible for orthopedic implants in terms of surface roughness, wettability, adhesion, wear sustainability, HA growth, corrosion rate, and cell viability. Thus, the biological, mechanical, and cellular properties of HA-coated implants are suitable and recommended as alternatives to biodegradable implants.
更多
查看译文
关键词
DoE optimization,Electrophoretic deposition,Hydroxyapatite,Invitro study,Pure magnesium,Weight loss in SBF
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要