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

Area of Science:

• Materials Science
• Condensed Matter Physics
• Computational Chemistry

Background:

• The first sharp diffraction peak (FSDP) is a key indicator of medium-range order (MRO) in amorphous materials.
• The structural origin of FSDP in polyhedral network glasses, like silica, remains debated.
• Understanding MRO is crucial for tailoring material properties.

Purpose of the Study:

• To investigate the structural origin of FSDP in high-density silica glasses.
• To explore the influence of compression on MRO in silica glass.
• To elucidate the relationship between ring structure and MRO.

Main Methods:

• Machine learning molecular dynamics (MLMD) simulations were employed.
• Simulations accurately reproduced experimental structural properties of densified silica glasses.
• Analysis focused on ring center periodicity and shape in simulated structures.

Main Results:

• MLMD simulations successfully modeled high-density silica glass structures.
• Changes in FSDP intensity correlated with compression temperature.
• The periodicity and shape of silica rings were identified as origins of MRO changes.
• Ring deformation under compression directly influences MRO.

Conclusions:

• The study clarifies the structural basis for MRO variations in densified silica glass.
• Ring deformation is the primary mechanism driving FSDP changes.
• MLMD simulations provide a powerful tool for understanding amorphous material structures.