Revealing the Void-Size Distribution of Silica Glass using Persistent Homology
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911278566473728 |
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| author | Atila, Achraf Bakhouch, Yasser Xie, Zhuocheng |
| author_facet | Atila, Achraf Bakhouch, Yasser Xie, Zhuocheng |
| contents | Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on the ring statistics as a metric for the medium-range structure, which, however, provides an incomplete picture of the glassy structure. Here, we use atomistic simulations and state-of-the-art topological analysis tools, namely persistent homology (PH), to analyze the medium-range structure of the archetypal oxide glass (Silica) at ambient temperatures and with varying pressures. PH presents an unbiased definition of loops and voids, providing an advantage over other methods for studying the structure and topology of complex materials, such as glasses, across multiple length scales. We captured subtle topological transitions in medium-range order and cavity distributions, providing new insights into glass structure. Our work provides a robust way for extracting the void distribution of oxide glasses based on persistent homology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_05484 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Revealing the Void-Size Distribution of Silica Glass using Persistent Homology Atila, Achraf Bakhouch, Yasser Xie, Zhuocheng Disordered Systems and Neural Networks Materials Science Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on the ring statistics as a metric for the medium-range structure, which, however, provides an incomplete picture of the glassy structure. Here, we use atomistic simulations and state-of-the-art topological analysis tools, namely persistent homology (PH), to analyze the medium-range structure of the archetypal oxide glass (Silica) at ambient temperatures and with varying pressures. PH presents an unbiased definition of loops and voids, providing an advantage over other methods for studying the structure and topology of complex materials, such as glasses, across multiple length scales. We captured subtle topological transitions in medium-range order and cavity distributions, providing new insights into glass structure. Our work provides a robust way for extracting the void distribution of oxide glasses based on persistent homology. |
| title | Revealing the Void-Size Distribution of Silica Glass using Persistent Homology |
| topic | Disordered Systems and Neural Networks Materials Science |
| url | https://arxiv.org/abs/2507.05484 |