材料科学
缝隙腐蚀
腐蚀
微观结构
合金
冶金
针状的
钛合金
马氏体
作者
Maria Herbster,Karsten Harnisch,Paulina Kriegel,A. Heyn,Manja Krüger,Christoph H. Lohmann,Jessica Bertrand,Thorsten Halle
出处
期刊:Materials
[Multidisciplinary Digital Publishing Institute]
日期:2022-08-19
卷期号:15 (16): 5733-5733
被引量:8
摘要
TiAl6V4 wrought alloy is a standard material used for endoprostheses due to its ideal characteristics in terms of osseointegration. However, the insufficient wear and crevice corrosion resistance of TiAl6V4 are limiting factors that can cause clinical problems. Therefore, the objective of this study was to analyze and identify suitable phases and microstructural states of TiAl6V4 alloy with advantageous implant properties by thermal treatments. By varying the temperature and cooling rate, four heat treatment strategies were derived that produced different microstructural states that differed in morphology, arrangement and proportions of phases present. All TiAl6V4 modifications were characterized regarding their microstructure, mechanical, corrosive and tribological properties, as well as cell adhesion. The acicular, martensitic microstructure achieves a significant hardness increase by up to 63% and exhibits improved corrosion and wear resistance compared to the forged condition. Whereas the modified microstructures showed similar electrochemical properties in polarization tests using different electrolytes (PBS with H2O2 and HCl additives), selective α or β phase dissolution occurred under severe inflammatory crevice conditions after four weeks of exposure at 37 °C. The microstructurally selective corrosion processes resemble the damage patterns of retrieved Ti-based implants and provide a better understanding of clinically relevant in vivo crevice corrosion mechanisms. Furthermore, a microstructural effect on cell attachment was determined and is correlated to the size of the vanadium-rich β phase. These key findings highlight the relevance of an adapted processing of TiAl6V4 alloy to increase the longevity of implants.
科研通智能强力驱动
Strongly Powered by AbleSci AI