Graph neural network-based structural classification of glass-forming liquids and its interpretation via self-attention mechanism

Documenti analoghi

• Elucidation of the Correlation between Molecular Conformation and Shear Viscosity of Polymer Melts under Steady-State Shear Flow
  di: Sakamaki, Yuhi, et al.
  Pubblicazione: (2025)
• Machine learning evaluation of structural descriptors for supercooled water
  di: Yoshikawa, Kohei, et al.
  Pubblicazione: (2026)
• Persistent Homology Reveals the Role of Stiffness in Forming Topological Glasses in Dense Solutions of Ring Polymers
  di: Goto, Shota, et al.
  Pubblicazione: (2024)
• Atomistic analysis of nematic phase transition in 4-cyano-4$^{\prime}$-$n$-alkyl biphenyl liquid crystals: Sampling for the first-order phase transition and the free-energy decomposition
  di: Ogita, Shunsuke, et al.
  Pubblicazione: (2024)
• Towards interpreting the thermally activated $β$ dynamics in metallic glass with the structural constraint neural network
  di: Jiang, Xiao, et al.
  Pubblicazione: (2024)