A data-driven comparative study of thermomechanical properties in rare-earth zirconate and tantalate oxides for thermal barrier coatings

Abstract

Rare-earth (RE) zirconates and tantalates are promising candidates for next-generation thermal barrier coatings (TBCs) due to their high-temperature stability and low thermal conductivity. However, the substantial compositional complexity introduced by multiple RE element substitutions poses significant challenges for systematic property optimization. To address these challenges, a high-throughput, data-driven computational framework was employed to systematically investigate and compare structural stability, thermodynamic properties, lattice thermal conductivity (κ_L) and fracture toughness (K_IC) of RE₂Zr₂O₇ and RE₃TaO₇ oxides (RE = Sc, Y, La ~ Lu) in their pyrochlore and Weberite-type structures, respectively. κ_L and intrinsic K_IC were systematically evaluated using phonon-scattering and Griffith-based models. The results reveal that RE₃TaO₇ exhibits consistently lower κ_L than RE₂Zr₂O₇ due to its low symmetry, heavier atomic masses and higher structural disorder. Interestingly, theoretical predictions indicate slightly higher intrinsic K_IC in RE₂Zr₂O₇, which is attributed to its ordered vacancy sublattice and symmetric bonding. In contrast, experimental data often report superior K_IC for RE₃TaO₇, likely due to extrinsic microstructural effects not captured in idealized calculations. Correlation and SHapley Additive exPlanations analyses further reveal that bond energy, charge disorder and bond-length heterogeneity are key descriptors governing κ_L and K_IC. These findings provide mechanistic insight into structure–property relationships and offer a predictive framework for the rational design of RE oxide TBC materials.

Highlights
• Integrating high-throughput first-principles calculations, lattice-level descriptor engineering and interpretable machine learning to design RE₂Zr₂O₇ and RE₃TaO₇ (RE = Sc, Y, La ~ Lu) oxide-based thermal barrier materials.
• Data-driven selection and classification of key physical descriptors (bond energy, charge disorder, bond-length heterogeneity) enable predictive modeling of κ_L and K_IC across 17 rare-earth elements.
• Combining thermodynamic stability analysis, phonon-based transport models and SHapley Additive exPlanations interpretability to establish structure–property relationships and guide rational oxide design.

Keywords

Rare-earth oxides / fracture toughness / lattice thermal conductivity / key physical parameter / first-principles

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