High-throughput reaction engineering to assess the oxidation stability of MAX phases
High-throughput reaction engineering to assess the oxidation stability of MAX phases
复制标题
高通量反应工程评估 MAX 相的氧化稳定性
DOI:
10.1038/s41524-020-00464-7
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发表时间:
2021-01-04
影响因子:
9.7
通讯作者:
Arroyave, R.
中科院分区:
文献类型:
--
作者:
Sauceda, D.;Singh, P.;Arroyave, R.
The resistance to oxidizing environments exhibited by some M(n+1)AX(n) (MAX) phases stems from the formation of stable and protective oxide layers at high operating temperatures. The MAX phases are hexagonally arranged layered nitrides or carbides with general formula M(n+1)AX(n), n=1, 2, 3, where M is early transition elements, A is A block elements, and X is C/N. Previous attempts to model and assess oxide phase stability in these systems has been limited in scope due to higher computational costs. To address the issue, we developed a machine-learning driven high-throughput framework for the fast assessment of phase stability and oxygen reactivity of 211 chemistry MAX phase M(2)AX. The proposed scheme combines a sure independence screening sparsifying operator-based machine-learning model in combination with grand-canonical linear programming to assess temperature-dependent Gibbs free energies, reaction products, and elemental chemical activity during the oxidation of MAX phases. The thermodynamic stability, and chemical activity of constituent elements of Ti2AlC with respect to oxygen were fully assessed to understand the high-temperature oxidation behavior. The predictions are in good agreement with oxidation experiments performed on Ti2AlC. We were also able to explain the metastability of Ti2SiC, which could not be synthesized experimentally due to higher stability of competing phases. For generality of the proposed approach, we discuss the oxidation mechanism of Cr2AlC. The insights of oxidation behavior will enable more efficient design and accelerated discovery of MAX phases with maintained performance in oxidizing environments at high temperatures.