Predicting the Biodegradation of Magnesium Alloy Implants: Modeling, Parameter Identification, and Validation.

Area of Science:

• Biomaterials Science
• Materials Engineering
• Computational Mechanics

Background:

• Magnesium (Mg) and its alloys offer biodegradable properties suitable for bone implants.
• Accurate modeling of Mg alloy degradation (corrosion) in physiological environments is essential for clinical application.
• Pitting corrosion is a significant factor influencing the in vivo performance of Mg-based implants.

Purpose of the Study:

• To develop a predictive model for the in vitro corrosion behavior of Mg-based alloys.
• To incorporate the effects of pitting corrosion into the degradation model.
• To validate the model's accuracy using experimental data.

Main Methods:

• Development of a customized FORTRAN user material subroutine (VUMAT) for the Abaqus/Explicit finite element (FE) solver.
• Implementation of a continuum damage mechanics (CDM) FE model to estimate corrosion rates.
• Conducting mass loss immersion tests in simulated body fluid (SBF) at 37°C and pH 7.4.
• Utilizing response surface methodology (RSM) to calibrate FE model parameters (γ, ψ, β, K_u).

Main Results:

• The developed VUMAT subroutine and CDM FE model successfully estimated the corrosion rate of a Mg-Zn-Ca alloy.
• Optimized model parameters were determined: γ = 2.74898, ψ = 2.60477, β = 5.1, and K_u = 0.1005.
• FE predictions showed a strong agreement with experimental mass loss data.

Conclusions:

• The numerical framework accurately captures the corrosion behavior and mass loss of Mg-based alloys over time.
• The developed model provides a precise tool for predicting the degradation of Mg alloys in physiological conditions.
• This research advances the development of reliable Mg-based biomaterials for orthopedic applications.