High-throughput computation and machine learning modeling of magnetic moments and Mössbauer parameters for Fe-based intermetallics

Documenti analoghi

• Data-efficient machine-learning of complex Fe-Mo intermetallics using domain knowledge of chemistry and crystallography
  di: Forti, Mariano, et al.
  Pubblicazione: (2025)
• Origin of the yield stress anomaly in L12 intermetallics unveiled with physically-informed machine-learning potentials
  di: Xu, Xiang, et al.
  Pubblicazione: (2024)
• A continuum, computational study of morphogenesis in lithium intermetallic interfaces
  di: Shojaei, Mostafa Faghih, et al.
  Pubblicazione: (2024)
• Optimizing $α''$-Fe$_{16}$N$_2$ as permanent magnet via alloying
  di: Zhao, Bo, et al.
  Pubblicazione: (2025)
• Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing
  di: Xia, Weiyi, et al.
  Pubblicazione: (2025)