Machine learning molecular dynamics reveals the structural origin of the first sharp diffraction peak in high-density silica glasses

Kobayashi, Keita ; Okumura, Masahiko   ; Nakamura, Hiroki  ; Itakura, Mitsuhiro  ; Machida, Masahiko  ; Urata, Shingo*; Suzuya, Kentaro

The first sharp peak diffraction peak (FSDP) in the structure factor of amorphous materials is thought to reflect the medium-range order structure in amorphous materials, and the structural origin of the FSDP has been a subject of ongoing debate. In this study, we employed machine learning molecular dynamics (MLMD) with nearly first-principles calculation accuracy to investigate the structural origin of the FSDP in high-density silica glass. First, we successfully reproduced various experimental data of high-density silica glass using MLMD. Furthermore, we revealed that the development (or reduction) of the FSDP in high-density silica glass is characterized by the deformation behavior of ring structures in Si-O covalent bond networks under compression.