Hydroxyapatite-containing PEO-coating design for biodegradable Mg-0.8Ca alloy: Formation and corrosion behaviour
Source abstract
Abstract
In this study, the biocompatible protective coating was formed using plasma electrolytic oxidation (PEO) on bioresorbable Mg-0.8Ca alloy. The composition of the formed coating was studied using XRD, SEM-EDX analysis, and micro-Raman spectroscopy. The uniform distribution of hydroxyapatite over the thickness of protective PEO-layer was established. Using traditional (EIS, PDP, OCP) and local scanning electrochemical methods (SVET, SIET with H+-selective microelectrode), the level of protective properties of PEO-layer in a biological environment (mammalian cell culture medium, MEM) was determined. It was established that modification of Mg-0.8Ca alloy surface by PEO contributes to a significant increase in the corrosion resistance of the surface layer, making it possible to control the process of material`s biodegradation. The maximum local electrochemical activity was recorded after 72 h of testing, while for the uncoated sample, intense corrosion degradation was recorded in the first 12 min of exposure to the cell culture medium. Formation of the PEO-coating results in a twofold decrease in the corrosion current density (2.8ˑ10−6 A cm−2) and an increase in the impedance modulus measured at a low frequency (1.7ˑ104 Ω cm2) in comparison with the uncoated material (9.5ˑ10−6 A cm−2; 8.1ˑ103 Ω cm2). The mechanism of material bioresorption was established and a model for biodegradation process of Mg-0.8Ca alloy with hydroxyapatite-containing PEO-coating in MEM was proposed. Analysis of these results and comparing with others obtained by various scientific groups indicate the prospects for application of biocompatible PEO-coating on Mg-Ca alloy in implant surgery.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Magnesium Alloys: Properties and Applications · Hydrogen Storage and Materials · Surface Treatment and Coatings
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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