High temperature oxidation behavior of disordered (Ti0.5Zr0.5)2AlC MAX phase via a Machine Learning-Augmented DFT Approach

P. Singh; D. Sauceda; R. Arroyavea

doi:10.1016/j.mlblux.2021.100062

High temperature oxidation behavior of disordered (Ti0.5Zr0.5)2AlC MAX phase via a Machine Learning-Augmented DFT Approach

Materials Science 2021-05-11 v1

Authors: P. Singh , D. Sauceda , R. Arroyavea

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Abstract

The Zr-based MAX phases have attracted considerable attention for their outstanding irradiation behavior and high neutron transparency relevant to nuclear power generation technologies. In spite of increased understanding of physical behavior crystalline MAX phases, the high-temperature oxidation behavior and reaction mechanism of disordered MAX phases both from theory and experiments are not well understood due to increased system complexity. Here, we present a detailed comparative assessment of high-temperature thermodynamic-stability and oxidation behavior (reaction-products and chemical activity) of ordered Ti2AlC and disordered (Ti0.5Zr0.5)2AlC. We believe that the new insights will enhance our understanding of oxidation process in disordered MAX phases.

Keywords

MAX phases disordered materials high-temperature oxidation machine learning density functional theory thermodynamic stability

Cite

@article{arxiv.2101.07460,
  title  = {High temperature oxidation behavior of disordered (Ti0.5Zr0.5)2AlC MAX phase via a Machine Learning-Augmented DFT Approach},
  author = {P. Singh and D. Sauceda and R. Arroyavea},
  journal= {arXiv preprint arXiv:2101.07460},
  year   = {2021}
}

Comments

8 pages; 2 Figures; 1 Table

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