Abstract

In this poster, first principles density functional theory (DFT) implemented in the Vienna Ab Initio Simulation Package (VASP)1 is coupled with micro-kinetic model2 to simulate the electrochemical corrosion kinetics of some commonly identified intermetallic particles3 (IMPs) associated with precipitation hardened aluminum alloys such as AA7075. First principles DFT calculation is used to characterize the adsorption energies for the cathodic reaction intermediates on intermetallic surfaces. The species include atomic oxygen (O) and hydroxide (OH) as intermediates for the oxygen reduction reaction. We will show that when coupling the thermodynamic calculations with an appropriate micro-kinetic model, we can predict the corrosion kinetics of IMPs. One of the most desirable properties obtained from the simulated polarization curve is the corrosion potential of the IMPs. The corrosion potential can indicate the relative nobilities of IMPs with respect to the alloy matrix. Experimentally the corrosion potential of IMPs on the range of microns are measured via a micro-capillary cell technique. With the state of the art TEM, localized corrosion even down to the nm scale can be characterized4. On the simulation side, however, a method that can be directly compared to experimental data has not yet been fully realized. Attempts to estimate corrosion potentials from the surface work functions obtained by DFT calculations have been made in recent literature but the direct correlation of work function to the corrosion potential has a significant band of uncertainty associated with it. Rather than finding direct correlation, we incorporate work function into the kinetics equation as one of the input parameters. Our simulated for Al7FeCu2, one of the most commonly identified IMP in high strength aluminum alloy, is -337 mVNHE, which is in good agreement with experimental data (-307 mVNHE). We contend here that a first-principles model founded in electrode kinetics is a promising path forward for bridging first-principles simulation and experiment in corrosion science.Reference G. Kresse and J. Furthmüller, Comput. Mater. Sci., 6, 15–50 (1996).H. A. Hansen, V. Viswanathan, and J. K. Nørskov, J. Phys. Chem. C, 118, 6706–6718 (2014) http://pubs.acs.org/doi/abs/10.1021/jp4100608.N. Birbilis and R. G. Buchheit, J. Electrochem. Soc., 152, B140 (2005) http://jes.ecsdl.org/cgi/doi/10.1149/1.1869984.Y. Zhu et al., Acta Mater., 189 (2020).

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