Glucose contents of simulated body fluid may both inhibit and accelerate corrosion of magnesium alloys. The nature of the influence may depend on the type and content of glucose and the characteristics of simulated body fluid. Hence in this study, the corrosion of a Mg-Zn-Zr alloy (i.e., ZK60) in modified-simulated body fluid (m-SBF) was investigated with and without added glucose (i.e., 0, 1, 2, 3 g L−1: representing various physiological glycemic conditions), employing potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS). The morphology and chemical characteristics of the corrosion product layer were investigated by scanning electron microscopy (SEM), grazing-incidence X-ray diffraction (GI-XRD), and X-ray photoelectron spectroscopy (XPS), which enabled a mechanistic understanding of the role of glucose addition in corrosion of the alloy. Further, a complementary analytical framework combining principal component analysis (PCA) and Bayesian uncertainty quantification was implemented in order to substantiate electrochemical findings from PDP and EIS. The quantitative electrochemical parameters derived from PDP tests revealed a distinct non-monotonic trend in corrosion current density (icorr) relative to the glucose-free m-SBF: at glucose levels of 1 g l−1 and 2 g l−1 a 24% reduction, while at 3 g l−1 a 12% increase in icorr is recorded. EIS further revealed that the 2 g l−1 glucose condition exhibited the highest corrosion resistance, primarily associated with the enhanced film resistance. The combined analysis validates a non-monotonic corrosion response with respect to glucose dependence, i.e., at physiological glucose levels (1 g l−1 and 2 g l−1), surface passivation enhances, contributing to decreased corrosion current densities. Further, the surface analysis corroborates that the lower corrosion resistance at 3 g l−1 is due to film destabilization caused by excessive hydration and organic adsorption. This work provides a statistically rigorous and quantitative assessment of the electrochemical data beyond conventional mean-comparison.
