Accelerating Phonon Thermal Conductivity Prediction by an Order of Magnitude Through Machine Learning-Assisted Extraction of Anharmonic Force Constants

Documenti analoghi

• Computational uncertainties in lattice thermal conductivity prediction of crystalline solids
  di: Srivastava, Yagyank, et al.
  Pubblicazione: (2025)
• Ab initio Investigation of Thermal Transport in Insulators: Unveiling the Roles of Phonon Renormalization and Higher-Order Anharmonicity
  di: Mandal, Soham, et al.
  Pubblicazione: (2024)
• Thermal Conductivity Limits of MoS$_2$ and MoSe$_2$: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
  di: Kocabas, Tugbey, et al.
  Pubblicazione: (2025)
• Quantum Computing for Phonon Scattering Effects on Thermal Conductivity
  di: Tan, Xiangjun
  Pubblicazione: (2024)
• Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates
  di: Wang, Zeyu, et al.
  Pubblicazione: (2026)