Abstract
Heat treatment serves as a viable strategy to effectively mitigate the intense corrosion of biodegradable WE43 alloys. However, limited comprehension of the passivation mechanisms underlying heat treatment and the dilemma to quantitatively examine the evolution of hydrogen gas in vivo introduce uncertainties in designing heat treatments for developing clinically applicable WE43. This work aims to advance this knowledge by applying cutting-edge atom probe tomography to provide atomic-scale insights into the passivation roles of rare earth (RE)-rich β1 (Mg3(Y, Nd)) and β' (Mg12NdY) nanophases induced by T6 heat treatment at 250 °C, and employing machine learning-based image analysis techniques to quantitatively unveil WE43’s in vivo gas evolution during a 12-week implantation. It was found that nanosized β1 and β' phases can effectively improve WE43′s corrosion resistance by inducing an accelerated passivation effect on the surface and confining the distribution of hydrogen ions in the matrix. Female rats presented slightly higher corrosion rates than male rats in weeks 1 and 4 but lower hydrogen gas volumes in vivo, while male rats possessed a superior ability to metabolise hydrogen gas in vivo. Notably, latent gas evolution against the corrosion rates was found which peaked at week 4 and subsided at week 12 despite the gradually decreased corrosion rates from week 1 to 12. This study offers insights for engineering heat treatments to develop clinically applicable WE43 with acceptable corrosion rates and in vivo gas generation at various implantation stages. Statement of SignificanceThe study aimed to reveal the role of β1 and β' nanophases on the good corrosion resistance of WE43. The influence of these nanophases on WE43′s corrosion performance has not been totally understood. Similarly, the understanding of hydrogen gas evolution as it relates to the magnesium implant's corrosion rate lacks clarity. Atom probe tomography (APT) indicates β1 and β' nanophases trap hydrogen, removing H2 from the lattice and disabling its catalytic role in Mg oxidation. Machine learning-aided analyses of computed tomography (CT) scan images indicate latent gas evolution, contradicting the monotonic in vivo H2 evolution that is widely accepted.
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