Multi-parameter optimization of SPS conditions for high-performance MgB2: A statistical approach


AĞIL H.

Physica C: Superconductivity and its Applications, cilt.641, 2026 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 641
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.physc.2026.1354831
  • Dergi Adı: Physica C: Superconductivity and its Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Chemical Abstracts Core, Compendex, INSPEC
  • Anahtar Kelimeler: Critical current density (Jc), MgB2 superconductors, Multivariate statistical analysis, Principal Component Analysis (PCA), Spark Plasma Sintering (SPS)
  • Hakkari Üniversitesi Adresli: Evet

Özet

Spark Plasma Sintering (SPS) temperature critically governs the microstructural development and superconducting performance of MgB2 bulk superconductors. In this study, MgB2 bulks were fabricated at different SPS temperatures, and their density, porosity, grain size, critical current density (Jc), and magnetic levitation properties were systematically evaluated. To move beyond conventional qualitative interpretations, Pearson correlation analysis, multiple linear regression, and principal component analysis (PCA) were jointly employed to quantitatively assess the relative and competing effects of microstructural parameters on Jc. The results demonstrate that densification is the dominant parameter controlling Jc at 20 K, exhibiting a strong positive correlation with superconducting and levitation performance, while porosity acts as the primary detrimental factor. Grain growth shows a secondary limiting effect by reducing flux pinning efficiency at higher sintering temperatures. Multiple linear regression confirms density as the most influential predictor of Jc. In contrast, PCA reveals that SPS temperature, density, and Jc cluster along a common high-performance axis, distinct from grain size–related mechanisms. These findings provide a quantitative, data-driven framework for understanding SPS-induced performance optimization in MgB2 and offer broader insights into processing–structure–property relationships in bulk superconductors.