Rafieerad A R, Bushroa A R, Nasiri-Tabrizi B, Kaboli S H A, Khanahmadi S, Amiri Ahmad, Vadivelu J, Yusof F, Basirun W J, Wasa K
Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia; Centre of Advanced Manufacturing and Material Processing (AMMP), University of Malaya, 50603 Kuala Lumpur, Malaysia.
Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia; Centre of Advanced Manufacturing and Material Processing (AMMP), University of Malaya, 50603 Kuala Lumpur, Malaysia; Department of Mechanical Engineering, Faculty of Engineering, University of UCLA, Los Angeles, CA 90032, United States; Department of Mechanical and Aerospace Engineering, University of California, CA 90095-1597, United States.
J Mech Behav Biomed Mater. 2017 May;69:1-18. doi: 10.1016/j.jmbbm.2016.11.019. Epub 2016 Dec 5.
Recently, the robust optimization and prediction models have been highly noticed in district of surface engineering and coating techniques to obtain the highest possible output values through least trial and error experiments. Besides, due to necessity of finding the optimum value of dependent variables, the multi-objective metaheuristic models have been proposed to optimize various processes. Herein, oriented mixed oxide nanotubular arrays were grown on Ti-6Al-7Nb (Ti67) implant using physical vapor deposition magnetron sputtering (PVDMS) designed by Taguchi and following electrochemical anodization. The obtained adhesion strength and hardness of Ti67/Nb were modeled by particle swarm optimization (PSO) to predict the outputs performance. According to developed models, multi-objective PSO (MOPSO) run aimed at finding PVDMS inputs to maximize current outputs simultaneously. The provided sputtering parameters were applied as validation experiment and resulted in higher adhesion strength and hardness of interfaced layer with Ti67. The as-deposited Nb layer before and after optimization were anodized in fluoride-base electrolyte for 300min. To crystallize the coatings, the anodically grown mixed oxide TiO-NbO-AlO nanotubes were annealed at 440°C for 30min. From the FESEM observations, the optimized adhesive Nb interlayer led to further homogeneity of mixed nanotube arrays. As a result of this surface modification, the anodized sample after annealing showed the highest mechanical, tribological, corrosion resistant and in-vitro bioactivity properties, where a thick bone-like apatite layer was formed on the mixed oxide nanotubes surface within 10 days immersion in simulated body fluid (SBF) after applied MOPSO. The novel results of this study can be effective in optimizing a variety of the surface properties of the nanostructured implants.
最近,稳健优化和预测模型在表面工程和涂层技术领域备受关注,旨在通过最少的反复试验实验获得尽可能高的输出值。此外,由于需要找到因变量的最优值,人们提出了多目标元启发式模型来优化各种工艺。在此,采用田口设计的物理气相沉积磁控溅射(PVDMS)并随后进行电化学阳极氧化,在Ti-6Al-7Nb(Ti67)植入物上生长定向混合氧化物纳米管阵列。通过粒子群优化(PSO)对Ti67/Nb的附着力和硬度进行建模,以预测输出性能。根据所开发的模型,运行多目标PSO(MOPSO)旨在找到PVDMS输入参数,以同时最大化电流输出。将提供的溅射参数应用于验证实验,结果表明与Ti67界面层的附着力和硬度更高。优化前后的沉积Nb层在氟化物基电解液中进行300分钟的阳极氧化。为了使涂层结晶,将阳极生长的混合氧化物TiO-NbO-AlO纳米管在440°C下退火30分钟。从场发射扫描电子显微镜(FESEM)观察结果来看,优化后的Nb粘结中间层使混合纳米管阵列更加均匀。这种表面改性的结果是,退火后的阳极氧化样品显示出最高的机械、摩擦学、耐腐蚀和体外生物活性性能,在应用MOPSO后,在模拟体液(SBF)中浸泡10天内,混合氧化物纳米管表面形成了一层厚厚的骨样磷灰石层。本研究的新结果可有效优化纳米结构植入物的各种表面性能。