Penghao Xiao^1*, Brandon Wood^2*

1 Department of Physics & Atmospheric Science, Dalhousie University, Halifax, NS B3H 4J5, Canada

2 Materials Science Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA

* Corresponding authors emails: pxiao@dal.ca, wood37@llnl.gov

DOI10.24435/materialscloud:w1-mx [version v1]

Publication date: Nov 14, 2024

How to cite this record

Penghao Xiao, Brandon Wood, Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys, Materials Cloud Archive 2024.181 (2024), https://doi.org/10.24435/materialscloud:w1-mx

Description

Passivation oxide formation is the key for corrosion control of metal alloys. The kinetics of competing oxide formation and dissolution determines alloy corrosion behaviors in aqueous solution. Despite the important role of the multi-component oxide evolution, little has been known on the kinetics from the atomistic level. We have built a computational framework that enables simulations of competing kinetic processes in multi-component oxides from first principles. The effects of applied voltage, pH and temperature on oxide growth, dissolution and reprecipitation can all be captured in this model. Combining with our experimental measurements on Alloy 22 and a Ni80%-Cr20% model alloy, we identified three voltage regimes with distinct oxide thicknesses and compositions. The oxide energetics of various stoichiometries are calculated by the density functional theory (DFT). Then the obtained data are used to train a surrogate lattice Hamiltonian with the cluster expansion (CE) method. Finally, kinetic Monte Carlo (KMC) simulations are run with the cation hopping barriers calculated on-the-fly based on the local environments from the combination of the above Hamiltonian and the linear Brønsted−Evans−Polanyi (BEP) relation.

Materials Cloud sections using this data

Files

File name	Size	Description
DFT_training_data.zip MD5md5:a7a7c4d0d75458906b9e56b751d1a0fd	11.5 MiB	DFT results used to train the cluster expansion model. Structures are in POSCAR format, and energies are in OSZICAR. VASP input parameters are provided in a python script "setmag_runvasp_NiCr.py".
cluster_expansion_results.zip MD5md5:9cde3a6c7f958f936a834c7a97cefff7	437.7 KiB	cluster expansion input and results
KMC_final_structure_analysis.zip MD5md5:3fe0e1fc7d6ba37533dfee47b24ebdaf	5.3 MiB	composition analysis of the final KMC structure (input structures, PYTHON scripts and output)

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

VASP cluster expansion kinetics Ni Cr oxide