Journal of Bionic Engineering ›› 2023, Vol. 20 ›› Issue (5): 1967-1984.doi: 10.1007/s42235-023-00372-8
Laser Surface Texturing of Co–Cr–Mo Alloy for Biomedical Applications: A Case Study for the Effects of Process Parameters on Surface Properties
Şefka Kasman1; İbrahim Can Uçar1; Sertan Ozan2
- 1 Department of Mechanical Engineering, Dokuz Eylul University, Izmir 35397, Turkey 2 Department of Mechanical Engineering, Yozgat Bozok University, Yozgat 66100, Turkey
Laser Surface Texturing of Co–Cr–Mo Alloy for Biomedical Applications: A Case Study for the Effects of Process Parameters on Surface Properties
Şefka Kasman1; İbrahim Can Uçar1; Sertan Ozan2
- 1 Department of Mechanical Engineering, Dokuz Eylul University, Izmir 35397, Turkey 2 Department of Mechanical Engineering, Yozgat Bozok University, Yozgat 66100, Turkey
摘要： This study presents a comprehensive approach to applying texturing processes created by engraving on the surface of CoCr28Mo alloy workpieces using a 20 W pulsed nanosecond fiber laser. The hatch strategy and distance, frequency, and scan speed were control parameters for texturing applications. The effectiveness of the parameters in terms of roughness and contact angle of the texturized surface was investigated. Surface roughness and contact angle were analyzed using variance analysis to identify each variable's influence. It has been determined that the roughness of the texture defined by the hatch strategy plays a decisive role in the wettability behavior of the surface; however, the scan speed, frequency, and hatch distance which are among the laser surface texturing conditions are influential in the roughness and contact angle. Increasing scan speed and hatch distance while decreasing frequency resulted in smoother surfaces, increasing the contact angle. Textures having rough surfaces produced with different processing conditions exhibit a super hydrophilic behavior. The contact angle is most sensitive to the hatch distance; however, the frequency has the least influence on the contact angle. The most and least efficient surface roughness parameters are revealed to be scan speed and hatch distance, respectively.