Clustering analysis to identify structural and density heterogeneity in Mg2SiO4 glass

Spatial distribution of HD (blue) and LD (gray) regions in Mg 2 SiO 4 glass (A) and the largest 10 clusters within the HD region (B). In this study, advanced data analysis techniques combined with molecular dynamics simulations are employed to investigate the structural characteristics of Mg 2 SiO 4 glass. Key structural features, including short-range order, intermediate-range order, and ring statistics, are analyzed to elucidate the distribution of Mg 2+ ions and their influence on the glass network. The DBSCAN clustering algorithm, integrated with structural analysis methods, reveals micro-phase separation with distinct Mg-rich regions. Additionally, the results highlight significant structural and density heterogeneities. To further clarify this phenomenon, a two-phase model is proposed, and the structural characteristics of each phase are characterized. The findings reveal the presence of both a high-density phase and a low-density phase, along with distinct differences in intermediate-range order between these phases. Furthermore, void distribution analysis provides deeper insights into the structural heterogeneity of Mg 2 SiO 4 glass. Advanced 3D visualization techniques offer an in-depth perspective on the atomic-scale complexity of this multi-component oxide glass. These results not only advance the fundamental understanding of amorphous Mg 2 SiO 4 but also provide valuable insights for tailoring material properties in advanced technological applications.

Authors

Institutions

Publication Details

Journal
Computational Materials Science
Published
2025-06-03
DOI
https://doi.org/10.1016/j.commatsci.2025.114019
Citations
1
Primary Topic
Glass properties and applications
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Clustering analysis to identify structural and density heterogeneity in Mg2SiO4 glass

Mai Thị Lan, Hong Van Nguyen, Dung Tri Pham
1 citations
Computational Materials Science
Glass properties and applications
0.73
article

Clustering analysis to identify structural and density heterogeneity in Mg2SiO4 glass

Mai Thị Lan, Hong Van Nguyen, Dung Tri Pham
article en
1 citations

Abstract

Spatial distribution of HD (blue) and LD (gray) regions in Mg 2 SiO 4 glass (A) and the largest 10 clusters within the HD region (B). In this study, advanced data analysis techniques combined with molecular dynamics simulations are employed to investigate the structural characteristics of Mg 2 SiO 4 glass. Key structural features, including short-range order, intermediate-range order, and ring statistics, are analyzed to elucidate the distribution of Mg 2+ ions and their influence on the glass network. The DBSCAN clustering algorithm, integrated with structural analysis methods, reveals micro-phase separation with distinct Mg-rich regions. Additionally, the results highlight significant structural and density heterogeneities. To further clarify this phenomenon, a two-phase model is proposed, and the structural characteristics of each phase are characterized. The findings reveal the presence of both a high-density phase and a low-density phase, along with distinct differences in intermediate-range order between these phases. Furthermore, void distribution analysis provides deeper insights into the structural heterogeneity of Mg 2 SiO 4 glass. Advanced 3D visualization techniques offer an in-depth perspective on the atomic-scale complexity of this multi-component oxide glass. These results not only advance the fundamental understanding of amorphous Mg 2 SiO 4 but also provide valuable insights for tailoring material properties in advanced technological applications.

Computational Materials ScienceVol. 257
Hanoi University of Science and Technology (VN)
Openalex Percentile: Top 36%
Glass properties and applications
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Clustering analysis to identify structural and density heterogeneity in Mg2SiO4 glass — Mai Thị Lan, Hong Van Nguyen, et al. · Computational Materials Science (2025) | TGRS Research Map | TGRS