4.7 Article

Computational modelling of magnesium degradation in simulated body fluid under physiological conditions

Journal

JOURNAL OF MAGNESIUM AND ALLOYS
Volume 10, Issue 4, Pages 965-978

Publisher

KEAI PUBLISHING LTD
DOI: 10.1016/j.jma.2021.11.014

Keywords

Biodegradation; Magnesium; Computational modelling; Corrosion; Uncertainty quantification; Kriging

Funding

  1. Helmholtz-Incubator project Uncertainty Quantification

Ask authors/readers for more resources

This paper presents a generalized model for simulating the degradation process of pure magnesium in simulated body fluid, considering uncertainty aspects. The model shows good agreement with experimental data in terms of average degradation depth, but the accuracy of determining elemental weight percentage of degradation products varies. The sensitivity analysis reveals correlations between model parameters, which is related to the complexity and computational costs of the model.
Magnesium alloys are highly attractive for the use as temporary implant materials, due to their high biocompatibility and biodegradability. However, the prediction of the degradation rate of the implants is difficult, therefore, a large number of experiments are required. Computational modelling can aid in enabling the predictability, if sufficiently accurate models can be established. This work presents a generalized model of the degradation of pure magnesium in simulated body fluid over the course of 28 days considering uncertainty aspects. The model includes the computation of the metallic material thinning and is calibrated using the mean degradation depth of several experimental datasets simultaneously. Additionally, the formation and precipitation of relevant degradation products on the sample surface is modelled, based on the ionic composition of simulated body fluid. The computed mean degradation depth is in good agreement with the experimental data (NRMSE= 0.07). However, the quality of the depth profile curves of the determined elemental weight percentage of the degradation products differs between elements (such as NRMSE = 0.40 for phosphorus vs. NRMSE = 1.03 for magnesium). This indicates that the implementation of precipitate formation may need further developments. The sensitivity analysis showed that the model parameters are correlated and which is related to the complexity and the high computational costs of the model. Overall, the model provides a correlating fit to the experimental data of pure Mg samples of different geometries degrading in simulated body fluid with reliable error estimation. (C) 2021 Chongqing University. Publishing services provided by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available