Published November 25, 2021 | Version v1
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Graph theory-based structural analysis on density anomaly of silica glass

  • 1. Department of Materials Science and Engineering, Massachusetts Institute of Technology
  • 2. Technology General Division, Planning Division, AGC Inc.
  • 3. Innovative Technology Laboratories, AGC Inc.

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Description

Understanding the structure of glassy materials represents a tremendous challenge for both experiments and computations. Despite decades of scientific research, for instance, the structural origin of the density anomaly in silica glasses is still not well understood. Atomistic simulations based on molecular dynamics (MD) produce atomically resolved structure, but extracting insights about the role of disorder in the density anomaly is challenging. Here, we propose to quantify the topological differences between structural arrangements from MD trajectories using a graph-theoretical approach, such that structural differences in silica glasses that exhibit density anomaly can be captured. To balance the accuracy and speed of the MD simulations, we utilized force matching potentials to generate the silica glass structures. This approach involves casting all-atom glass configurations as networks, and subsequently applying a graph-similarity metric (D-measure). Calculated D-measure values are then taken as the topological distances between two configurations. By measuring the topological distances of configurations in silica glass simulated structures across a range of temperatures, distinct structural features could be observed at temperatures higher than the fictive temperature. In addition to quantifying structural changes in the full simulation box, we compared topological distances between local atomic environments in the glass and crystalline silica phases. Evidence from this approach suggests that more coesite-like local structures, which are less symmetric, emerge in silica glasses when density is at a minimum during the heating process.

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References

Preprint (Preprint where the data is discussed)
A.R.Tan, S.Urata, M.Yamada, R.Gómez-Bombarelli. arXiv:2111.07452 (2021)

Journal reference
A. R. Tan, S. Urata, M. Yamada, R. Gómez-Bombarelli. Computational Materials Science 225, 112190 (2023), doi: 10.1016/j.commatsci.2023.112190