Empirical framework reveals how texture and elemental composition affect superconductivity in EuIn₂As₂₋ₓPₓ, indicating design pathways for optimized materials.
This study presents an integrated empirical framework that captures the interplay between crystallographic texture, elemental composition, and superconducting behavior in the Zintl-type compound series EuIn₂As₂₋ₓPₓ (0 ≤ x ≤ 2). By redefining the superconducting composition index (%Si) as a weighted contribution from constituent elements (Eu, In, As, P) and quantifying texture through a composite orientation factor (A), a predictive energy descriptor EEE is constructed. This descriptor correlates strongly with key superconducting parameters, including critical temperature (Tₚ), critical current density (Jₚ), coherence length (ξ), vortex pinning energy (U₀), and magnetic penetration depth (λ). Regression analyses across these properties yield R² values between 0.912 and 0.978, underscoring the robustness of the model. Notably, the intermediate phase EuIn₂AsP (x = 1) serves as a test case where the predicted values align with known experimental behavior. 3D visualizations further illustrate how microstructure and composition jointly influence superconducting performance, offering practical design pathways for texture-optimized Zintl compounds. The study establishes the energy descriptor EEE as a unifying variable for structure–property correlations in anisotropic superconductors.
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Sudhakar Geruganti (2025) studied this question.
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