Topological contribution to the split first peak of the liquid water structure factor using the MACE machine-learning potential

The splitting of the principal peak in the structure factor of liquid water is commonly interpreted as evidence of a competition between two distinct local environments. Here, we show that this peak splitting is captured by medium-range topological features of the hydrogen-bond network. Using atomistic simulations, we systematically decompose the structure factor into contributions from hydrogen-bonded rings of different sizes. We find that 5-8-membered rings, which dominate the network topology of liquid water at low temperatures, can directly explain the experimentally observed bimodal scattering signal. Among these, 5-membered rings are particularly persistent, maintaining distinct structural signatures even above room temperature. Our findings establish a direct link between the network topology of liquid water and experimentally accessible diffraction features and provide a topological perspective on the nature of the split first diffraction peak in tetrahedral materials.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2026-08-20
DOI
https://doi.org/10.1063/5.0337533
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

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article

Topological contribution to the split first peak of the liquid water structure factor using the MACE machine-learning potential

Fausto Martelli, Zoé Faure Beaulieu, Volker L. Deringer
The Journal of Chemical Physics
Machine Learning in Materials Science
article

Topological contribution to the split first peak of the liquid water structure factor using the MACE machine-learning potential

Fausto Martelli, Zoé Faure Beaulieu, Volker L. Deringer
article en

Abstract

The splitting of the principal peak in the structure factor of liquid water is commonly interpreted as evidence of a competition between two distinct local environments. Here, we show that this peak splitting is captured by medium-range topological features of the hydrogen-bond network. Using atomistic simulations, we systematically decompose the structure factor into contributions from hydrogen-bonded rings of different sizes. We find that 5-8-membered rings, which dominate the network topology of liquid water at low temperatures, can directly explain the experimentally observed bimodal scattering signal. Among these, 5-membered rings are particularly persistent, maintaining distinct structural signatures even above room temperature. Our findings establish a direct link between the network topology of liquid water and experimentally accessible diffraction features and provide a topological perspective on the nature of the split first diffraction peak in tetrahedral materials.

The Journal of Chemical PhysicsVol. 165(7)
University of Oxford (GB), Institute for Complex Systems (IT), Sapienza University of Rome (IT)
UK Research and Innovation, IBM Research
Clean water and sanitation
Openalex Percentile: Top 22%
Machine Learning in Materials Science
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