Electro-Discharge Machining of Zr<sub>67</sub>Cu<sub>11</sub>Ni<sub>10</sub>Ti<sub>9</sub>Be<sub>3</sub>: An Investigation on Hydroxyapatite Deposition and Surface Roughness

This study attempts to simultaneously machine and synthesize a biomimetic nanoporous hydroxyapatite coating on the Zr<sub>67</sub>Cu<sub>11</sub>Ni<sub>10</sub>Ti<sub>9</sub>Be<sub>3</sub> bulk metallic glass (BMG) surface. The aim is to in...

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Bibliographic Details
Main Authors: Abdul’Azeez Abdu Aliyu, Ahmad Majdi Abdul-Rani, Saeed Rubaiee, Mohd Danish, Michael Bryant, Sri Hastuty, Muhammad Al’Hapis Razak, Sadaqat Ali
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Processes
Subjects:
Online Access:https://www.mdpi.com/2227-9717/8/6/635
Description
Summary:This study attempts to simultaneously machine and synthesize a biomimetic nanoporous hydroxyapatite coating on the Zr<sub>67</sub>Cu<sub>11</sub>Ni<sub>10</sub>Ti<sub>9</sub>Be<sub>3</sub> bulk metallic glass (BMG) surface. The aim is to investigate and optimize the hydroxyapatite deposition rate and the surface roughness during the electro-discharge coating of Zr<sub>67</sub>Cu<sub>11</sub>Ni<sub>10</sub>Ti<sub>9</sub>Be<sub>3</sub><b> </b>BMG. Scanning Electron Microscopy (SEM), X-ray powder Diffraction (XRD) and Energy-dispersive X-ray Spectroscopy (EDS) were employed to characterize and analyze the results. Response Surface Methodology using D-optimum custom design approach was utilized to generate the models and optimize the input parameters. A globule nanostructured and nanoporous coating of about 25.2 µm thick, containing mainly Ca, O, and K were ascertained. Further XRD analysis confirmed the deposition of biocompatible oxides (HA, CaZrO<sub>3</sub>, and ZrO<sub>2</sub>) and hard ZrC coating on the Zr<sub>67</sub>Cu<sub>11</sub>Ni<sub>10</sub>Ti<sub>9</sub>Be<sub>3</sub> BMG surface. A significant improvement in cell viability was observed in the HA electro-discharge coated BMG specimens. The numerical models for the Hydroxyapatite Deposition Rate (HDR) and Surface Roughness (SR) were developed and experimentally validated using the optimized parameters setting suggested by the software. The achieved average predicted error of 4.94 and 5.09% for the HDR and SR respectively confirmed the excellent reproducibility of the developed models.
ISSN:2227-9717