Abstract
The dielectric properties of disordered crystalline materials are governed by long-range orientational correlations arising from local structural disorder. We present a statistical and topological framework that connects hydrogen-bond network features to macroscopic dielectric anisotropy. Using hexagonal ice as a model system, we represent the network as a directed graph and employ the polarization index, originally introduced in the GenIce software, to measure the net traversal of percolating hydrogen-bond chains through the periodic lattice. Effective bond dipole moments, determined from moderately sized simulation cells, are combined with the variance of the polarization index to predict dielectric constants for much larger cells without additional computations on three-dimensional structures. We validate this Polarization Index-Based Effective Dipole (PIBED) model using the AMOEBA14 and neural network potentials, with and without nuclear quantum effects. The results agree with the estimates from the traditional Total Dipole Fluctuation (TBF) model and exhibit improved statistical convergence, enabling robust estimation of the small dielectric anisotropy of ice Ih. Our findings establish a generalizable method for quantifying dielectric response in disordered crystals and may offer insights into the dielectric behavior of partially ordered systems such as hybrid perovskites and solid-state proton conductors.
Similar content being viewed by others

Data availability
The input files and representative structures used in this study are available on Zenodo at https://doi.org/10.5281/zenodo.17994911.
References
Keen, D. A. & Goodwin, A. L. The crystallography of correlated disorder. Nature 521, 303–309 (2015).
Bernal, J. D. & Fowler, R. H. A theory of water and ionic solution, with particular reference to hydrogen and hydroxyl ions. J. Chem. Phys. 1, 515–548 (1933).
Simonov, A. & Goodwin, A. L. Designing disorder into crystalline materials. Nat. Rev. Chem. 4, 657–673 (2020).
Kang, S., Lee, S., Lee, H. & Kang, Y.-M. Manipulating disorder within cathodes of alkali-ion batteries. Nat. Rev. Chem. 8, 587–604 (2024).
Neumeier, J. J. Elastic constants, bulk modulus, and compressibility of H2O ice Ih for the temperature range 50 K-273 K. J. Phys. Chem. Ref. Data 47, 033101 (2018).
Kawada, S. Dielectric properties of heavy ice ih (D2O ice). J. Phys. Soc. Jpn. 47, 1850–1856 (1979).
Wörz, O. & Cole, R. Dielectric properties of ice I. J. Chem. Phys. 51, 1546–1551 (1969).
Johari, G. P. & Jones, S. J. The orientation polarization in hexagonal ice parallel and perpendicular to the c-axis. J. Glaciol. 21, 259–276 (1978).
Schönherr, M., Slater, B., Hutter, J. & VandeVondele, J. Dielectric properties of water ice, the ice Ih/XI phase transition, and an assessment of density functional theory. J. Phys. Chem. B 118, 590–596 (2014).
Barkema, G. & Boer, J. D. Properties of a statistical model of ice at low temperatures. J. Chem. Phys. 99, 2059–2067 (1993).
Nagle, J. Dielectric constant of ice. J. Chem. Phys. 61, 883–888 (1974).
Popov, I. et al. The low-temperature dynamic crossover in the dielectric relaxation of ice Ih. Phys. Chem. Chem. Phys. 19, 28610–28620 (2017).
Rick, S. W. & Haymet, A. Dielectric constant and proton order and disorder in ice Ih: Monte Carlo computer simulations. J. Chem. Phys. 118, 9291–9296 (2003).
Rick, S. W. A reoptimization of the five-site water potential (TIP5P) for use with Ewald sums. J. Chem. Phys 120, 6085–6093 (2004).
Lindberg, G. E. & Wang, F. Efficient sampling of ice structures by electrostatic switching. J. Phys. Chem. B 112, 6436–6441 (2008).
Rusnak, A. J., Pinnick, E. R., Calderon, C. E. & Wang, F. Static dielectric constants and molecular dipole distributions of liquid water and ice-Ih investigated by the PAW-PBE exchange-correlation functional. J. Chem. Phys. 137, 034510 (2012).
MacDowell, L. G. & Vega, C. Dielectric constant of ice Ih and ice V: a computer simulation study. J. Phys. Chem. B 114, 6089–6098 (2010).
Aragones, J., MacDowell, L. & Vega, C. Dielectric constant of ices and water: a lesson about water interactions. J. Phys. Chem. A 115, 5745–5758 (2011).
Laury, M. L., Wang, L.-P., Pande, V. S., Head-Gordon, T. & Ponder, J. W. Revised parameters for the amoeba polarizable atomic multipole water model. J. Phys. Chem. B 119, 9423–9437 (2015).
Duignan, T. T. The potential of neural network potentials. ACS Phys. Chem. Au 4, 232–241 (2024).
Schran, C., Brezina, K. & Marsalek, O. Committee neural network potentials control generalization errors and enable active learning. J. Chem. Phys 153, 104105 (2020).
Matsumoto, M., Yagasaki, T. & Tanaka, H. Genice: hydrogen-disordered ice generator. J. Comput. Chem. 39, 61–64 (2018).
Matsumoto, M., Yagasaki, T. & Tanaka, H. Novel algorithm to generate hydrogen-disordered ice structures. J. Chem. Inf. Model. 61, 2542–2546 (2021).
Bonnet, N. & Marzari, N. Static dielectric permittivity of ice from first principles. Phys. Rev. Lett. 113, 245501 (2014).
Adams, D. J. Monte Carlo calculations for the ice-rules model with and without Bjerrum defects. J. Phys. C Solid State Phys. 17, 4063 (1984).
Comes, R., Lambert, M. & Guinier, A. The chain structure of BaTiO3 and KNbO3. Solid State Commun. 6, 715–719 (1968).
Gigli, L. et al. Thermodynamics and dielectric response of BaTiO3 by data-driven modeling. Npj Comput. Mater. 8, 209 (2022).
Motta, C. et al. Revealing the role of organic cations in hybrid halide perovskite CH3NH3PbI3. Nat. Commun. 6, 7026 (2015).
Wood, B. C. & Marzari, N. Proton dynamics in superprotonic CsHSO4. Phys. Rev. B 76, 134301 (2007).
Matsumoto, M., Yagasaki, T. & Tanaka, H. GenIce-core: efficient algorithm for generation of hydrogen-disordered ice structures. J. Chem. Phys. 160, 094101 (2024).
Matsumoto, M. Genice2 https://github.com/vitroid/GenIce (2015).
The Engineering ToolBox. Ice – Thermal Properties. Available at: https://www.engineeringtoolbox.com/ice-thermal-properties-d_576.html. (2004). (accessed 13 February 2026).
Rackers, J. A. et al. Tinker 8: software tools for molecular design. J. Chem. Theory Comput. 14, 5273–5289 (2018).
Kühne, T. D. et al. CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations. J. Chem. Phys 152, 194103 (2020).
Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys 103, 8577–8593 (1995).
Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007).
Ceriotti, M., Parrinello, M., Markland, T. E. & Manolopoulos, D. E. Efficient stochastic thermostatting of path integral molecular dynamics. J. Chem. Phys. 133, 124104 (2010).
Eltareb, A., Lopez, G. E. & Giovambattista, N. Nuclear quantum effects on the thermodynamic, structural, and dynamical properties of water. Phys. Chem. Chem. Phys. 23, 6914–6928 (2021).
Habershon, S., Markland, T. E. & Manolopoulos, D. E. Competing quantum effects in the dynamics of a flexible water model. J. Chem. Phys. 131, 024501 (2009).
Paesani, F., Zhang, W., Case, D. A., Cheatham, T. E. & Voth, G. A. An accurate and simple quantum model for liquid water. J. Chem. Phys. 125, 184507 (2006).
Johari, G. & Whalley, E. The dielectric properties of ice Ih in the range 272-133 K. J. Chem. Phys 75, 1333–1340 (1981).
Acknowledgements
This work was supported by the National Research, Development and Innovation Office of Hungary (NKFI, Grant No. FK142784).
Funding
Open access funding provided by HUN-REN Research Centre for Natural Sciences.
Author information
Authors and Affiliations
Contributions
A.M. conceived and supervised the project. Z.T.N. and A.M. analyzed and interpreted the data. Z.T.N. performed the simulations. Z.T.N. and A.M. prepared the figures and wrote the manuscript. All authors approved the final version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Tohidi Nafe, Z., Madarász, Á. Dielectric properties of disordered crystalline materials: a computational case study on hexagonal ice. npj Comput Mater (2026). https://doi.org/10.1038/s41524-026-01998-y
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41524-026-01998-y

