The
oxygen reduction reaction (ORR) is a major factor that drives
galvanic corrosion. To better understand how to tune materials to
better inhibit catalytic ORR, we have identified an in silico procedure for predicting elemental dopants that would cause common,
natively formed titanium oxides to better suppress this reaction.
In this work, we created an amorphous TiO2 surface model
that is in good agreement with experimental radial distribution function
data and contains reaction sites capable of replicating experimental
ORR overpotentials. Dopant performance trends predicted with our quantum
chemistry model mirrored experimental results, and our top three predicted
dopants (Mn, Al, and V, each present at doping concentrations of 1%)
were experimentally verified to lower ORR currents under alkaline
conditions by up to 77% vs the undoped material. These results show
the robustness of calculated thermodynamic descriptors for identifying
poor, TiO2-based ORR catalysts. This also opens the possibility
of using quantum chemistry to guide the design of coating materials
that would better resist the ORR and presumably galvanic corrosion.
The reduction of nanodevices has given recent attention to nanoporous materials due to their structure and geometry. However, the thermophysical properties of these materials are relatively unknown. In this article, an expression for thermal conductivity of nanoporous structures is derived based on the assumption that the finite size of the ligaments leads to electron-ligament wall scattering. This expression is then used to analyze the thermal conductivity of nanoporous structures in the event of electron-phonon nonequilibrium.
Modeling of dealloying has often used a local bond-breaking approach to define the energy barrier to simulate dissolution and surface diffusion. The energy barriers are tacitly assumed to be independent of the local solution chemistry at the metal/solution interface. In this work, an interaction energy parameter is added to the local bond-breaking model that accounts for the species-specific physics of the actual atom-water molecule, atom-ion interactions and allows complex atomistic behavior to be abstracted in the modeling of the diffusion and dissolution processes. Variations in the interactions of the electrolyte components with the metal atoms led to the prediction of different surface morphologies on a binary alloy sample surface that mirror the behaviors experimentally observed in dealloying experiments in Au–Cu alloys including the formation of Au-enriched surface islands at applied potentials below the critical potential and three-dimensional porosity at applied potentials above the critical potential.
Measurements of galvanic corrosion between UNS S13800 and UNS A97075 in bulk and equilibrated droplet electrolytes are compared with theoretical predictions of the corrosion current using calculations of the static diffusion-limited current, the classic Cottrell equation, and chemical reaction pathway models. The droplet electrolyte experiments use disks of stainless steel embedded in the aluminum alloy but isolated from electrical contact by an epoxy ring and connected via a zero-resistance ammeter potentiostat. Discrepancies between the measured and expected corrosion current for the droplet electrolyte are analyzed and a mechanism that relies on chemical reactions in the electrolyte to form corrosion products that block ion transport and suppress further oxidation is proposed. Electrochemical impedance spectroscopy and mass measurements are used to monitor changing solution properties in the equilibration of the droplet with the temperature and relative humidity environment of the atmospheric corrosion chamber.
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