Predicting Crystal Structures and Ionic Conductivities in Li$_{3}$YCl$_{6-x}$Br$_{x}$ Halide Solid Electrolytes Using a Fine-Tuned Machine Learning Interatomic Potential

Ähnliche Einträge

• Predicting Crystal Structures and Ionic Conductivities in Li 3 YCl 6−x Br x Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential
  von: Jonas Böhm, et al.
  Veröffentlicht: (2026)
• Strain-Dependent Ionic Transport in Li3YCl6 Solid Electrolytes
  von: Huang, Wei-Fan, et al.
  Veröffentlicht: (2026)
• Investigating Ionic Diffusivity in Amorphous Solid Electrolytes using Machine Learned Interatomic Potentials
  von: Seth, Aqshat, et al.
  Veröffentlicht: (2024)
• Parameter-Efficient Fine-Tuning of Machine-Learning Interatomic Potentials for Phonon and Thermal Properties
  von: Grandel, Jonas, et al.
  Veröffentlicht: (2026)
• Li-P-S Electrolyte Materials as a Benchmark for Machine-Learned Interatomic Potentials
  von: Fragapane, Natascia L., et al.
  Veröffentlicht: (2025)