Mcb (Mass and Charge Balance) Model Simulation of Corrosion of Co-Cr Alloy Stellite-6
Authors: Momeni Mojtaba , Behazin Mehran , Wren Jungsook Clara 
Published: February 2020

Understanding of oxide formation and growth on an alloy is very important in predicting its corrosion behaviour. Several models for oxide growth as well as metal dissolution kinetics in the presence of an oxide layer have been developed. These models focus on describing the transport of charged species through the oxide film and the electrochemical reactions at the metal/oxide and oxide/solution interfaces, although the detailed description and formulation of these processes vary. However, these models do not consider the type of oxide that can form. Consequently, the models have limited capability of predicting changes in the corrosion rate with time as corrosion progresses, or the dependence of corrosion kinetics on the solution redox conditions.
Recently, we have developed a corrosion model that can predict the rates of metal oxidation, oxide growth and dissolution simultaneously as a function of time. The model imposes reaction thermodynamics constraints, and mass and charge balance (MCB) requirements on corrosion reaction rates and hence is labelled the MCB model [1]. The mass and charge balance requirements dictate that the flux of metal cations created by oxidation of metal atoms at the m|ox interface (the oxidation flux) must be equal to the sum of the fluxes of the metal cations forming an oxide at the oxide/solution interface (the oxide formation flux) and the flux of metal cations dissolving into solution (the dissolution flux). The oxidation flux is calculated by using a modified Butler-Volmer equation with an effective overpotential that is defined as a function of the equilibrium potential of the metal oxidation and the potential drop across the oxide layer that is growing. Both the oxide formation dissolution fluxes have a first-order dependence on the oxidation flux. The first-order rate constant for the oxide formation follows an Arrhenius dependence with an activation energy that increases linearly with oxide thickness. The dissolution rate constant depends on surface hydration and the solution environment (pH and temperature), but is independent of the oxide thickness. Consequently, under constant solution conditions the rate constant for the oxide formation, kMO(t), changes with time as the oxide grows but the rate constant of dissolution, kdiss, is constant with time. Due to a mass balance constraint and competition between the two processes for the metal ions, the oxide formation and dissolution fluxes cannot vary independently. The fraction of the oxidation flux that leads to oxide formation or dissolution depends on their rate constants; fk-MO(t) = kMO(t)/(kMO(t) + kdiss) and fk-diss(t) = 1 - fk-MO(t), respectively.
In this paper, we present MCB model simulation results of potentiostatic polarization experiments performed on Co-Cr alloy Stellite-6 [2]. The simulations results are compared with the experimental measurements of the corrosion current as a function of time and the final composition and structure of the oxide(s) that formed. In these simulations, the parameters such as rate constants, exchange current density and field strength (or specific potential drop) across an oxide layer were kept constant for a specific pH and temperature. The main rate parameter that varies with pH and temperature was . This rate constant ratio is higher under conditions which promote oxide formation over dissolution, such as high pHs where the solubility of metal cations is low. The MCB model with the same model parameters was then applied to different sets of experimental data which include measurements of corrosion potential as a function of time and determination of the amounts of dissolved metals in coupon corrosion tests conducted in sealed quartz vials. The excellent agreement between the model results and experimental data over a range of polarization potential, pH and temperature indicates that the MCB model is a valuable method for simulating time-dependent corrosion behaviour while an oxide film is changing.

References

[1] M. Momeni, J.C. Wren, Faraday Discussions (2015) DOI 10.1039/C4FD00244J.
[2] M. Behazin et al. Electrochimica Acta 134 (2014) 399–410.