Abstract
The resistance to oxidizing environments exhibited by some Mn+1AXn (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 Mn+1AXn, 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 M2AX. 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.
Highlights
Mn+1AXn (MAX) phases belong to the group of ternary carbides and nitrides in which M is early transition metal, A is group 13–16 element and X is C or N1–3
The potential oxidation resistance of a candidate MAX phase depends on its ability to form a stable passivating oxide layer as weakly bonded elements that typically reside in the A-sites react with oxygen in the environment
Experimental enthalpy and total energy database of 1b–d, which possibly originates from the use of 0 K cell volumes of transition metal oxides and other phases, required to predict finite-temperature Gibbs’ free energies (ΔGform) by screening and sparsifying operator (SISSO), are taken from the NIST-JANAF thermochemical tables[25,26], Open Quantum Materials Database (OQMD)[27], and first-principles the involved phases as a feature used to compute the finitetemperature Gibbs free energy of formation
Summary
Mn+1AXn (MAX) phases belong to the group of ternary carbides and nitrides in which M is early transition metal, A is group 13–16 element and X is C or N1–3. Despite the fact that the assessment of oxidation behavior in MAX phases is of critical importance for their further development as a high-temperature structural or coating material, to date there is no current computational approach capable of quickly assessing the oxide phase stability of arbitrary MAX phase compositions Such an approach could in turn be used to guide the experimental discovery and optimization of MAX phases with superior hightemperature performance under oxidizing conditions. Experimental enthalpy and total energy database of 1b–d, which possibly originates from the use of 0 K cell volumes of transition metal oxides and other (binary, ternary) phases, required to predict finite-temperature Gibbs’ free energies (ΔGform) by SISSO, are taken from the NIST-JANAF thermochemical tables[25,26], Open Quantum Materials Database (OQMD)[27], and first-principles the involved phases as a feature used to compute the finitetemperature Gibbs free energy of formation. We present a detailed discussion on our predictions on oxidation behavior of Cr2AlC in order to show the generality of our scheme
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