Thermodynamic feasibility of the four-stage chloride-induced depassivation mechanism of iron

Abstract

The atomistic mechanism of chloride-induced depassivation of iron is still debated. A recent study suggests a four-stage depassivation mechanism, in general agreement with the point defect model. The proposed four-stage mechanism is based on reactive force field molecular dynamics simulations and is rather complex but here we use density functional theory to confirm the thermodynamic feasibility of the proposed mechanism. We find that the four surface species, formed in the four stages, have decreasing surface stability, which is consistent with the order of species formed in the depassivation process proposed in the reactive force field molecular dynamics study. The Fe vacancy formation energy, that is the energy needed to form a surface Fe vacancy by removing different surface species, indicates that surface species with more chlorides dissolve more easily from the surface, suggesting that chloride acts as catalyst in the iron dissolution process. The results are consistent with the suggested fourstage reaction mechanism and the point defect model.

Density Functional Theory Study of Influence of Oxide Thickness and Surface Alloying on Cl Migration within α-Al2O3

“…13 On the other hand, DFT calculations have made some progress towards clarifying the atomic process involved in the oxide breakdown caused by Cl − . [14][15][16][17][18] However, how the oxide film thickness and alloy doping affect the Cl − ingress into Al oxide is still missing in theoretical simulations.…”

Revisiting Cl-Induced Degradation of MnS Inclusions Using DFT

“…We consider the fully Cl-adsorbed surface, i.e., eight Cl on the surface. Note that unlike Cl adsorption on the oxide surface such as Fe 2 O 3 , ,, where Fe can coordinate with more than one Cl, we found that Mn is energetically unfavorable to coordinate with more than one Cl on the MnS slab (see Figure S7 in the Supporting Information for details). It is shown that Cl interacts vigorously with the surface, especially on the top layer, showing that significant thermodynamic instability is induced.…”

Beyond the chloride threshold concept for predicting corrosion of steel in concrete

“…In recent years, atomistic/molecular modeling techniques have been used to study passivity and chloride-induced depassivation of iron in alkaline electrolytes to develop a fundamental understanding of how chlorides interact with passive films at the molecular level in idealized systems. [109][110][111][112][113][114] Although these techniques have the potential to help future development of new corrosion inhibitors and corrosionresistant steels, they are not very useful or practical in improving forecasts of safety and sustainability of reinforced concrete structures experiencing corrosion. Machine learning is a field that has received increased attention from researchers studying steel corrosion in concrete and has been shown to be a promising approach for predicting damage in reinforced concrete structures experiencing corrosion.…”