Solid-angle nearest-neighbor method for size-disperse systems of spheres

Identifying nearest neighbors accurately is essential in particle-based simulations, from analyzing local structure to detecting phase transitions. While parameter-free methods, such as Voronoi tessellation and the solid-angle nearest-neighbor (SANN) algorithm, are effective in monodisperse systems, they become less reliable in mixtures with large size disparities. We introduce SANNR, a generalization of SANN that incorporates particle radii into the solid-angle criterion for robust, size-sensitive neighbor detection. We compare SANNR against Voronoi, Laguerre, and SANN in binary and size-disperse sphere mixtures. Using Wasserstein distance metrics, we show that SANNR closely matches size-aware Laguerre tessellation while preserving the geometric continuity of SANN. Applied to the crystallization of the complex AB13 phase, SANNR improves detection of local bond-orientational order and better captures the emergence of global symmetry. SANNR, thus, offers a smooth, parameter-free, and extensible framework for neighbor detection in polydisperse and multicomponent systems.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-12-12
DOI
https://doi.org/10.1063/5.0295910
Citations
1
Primary Topic
Block Copolymer Self-Assembly
Type
article
Field-Weighted Citation Impact
0.52
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article

Solid-angle nearest-neighbor method for size-disperse systems of spheres

Nydia Roxana Varela-Rosales, Michael Engel
1 citations
The Journal of Chemical Physics
Block Copolymer Self-Assembly
0.52
article

Solid-angle nearest-neighbor method for size-disperse systems of spheres

Nydia Roxana Varela-Rosales, Michael Engel
article en
1 citations

Abstract

Identifying nearest neighbors accurately is essential in particle-based simulations, from analyzing local structure to detecting phase transitions. While parameter-free methods, such as Voronoi tessellation and the solid-angle nearest-neighbor (SANN) algorithm, are effective in monodisperse systems, they become less reliable in mixtures with large size disparities. We introduce SANNR, a generalization of SANN that incorporates particle radii into the solid-angle criterion for robust, size-sensitive neighbor detection. We compare SANNR against Voronoi, Laguerre, and SANN in binary and size-disperse sphere mixtures. Using Wasserstein distance metrics, we show that SANNR closely matches size-aware Laguerre tessellation while preserving the geometric continuity of SANN. Applied to the crystallization of the complex AB13 phase, SANNR improves detection of local bond-orientational order and better captures the emergence of global symmetry. SANNR, thus, offers a smooth, parameter-free, and extensible framework for neighbor detection in polydisperse and multicomponent systems.

The Journal of Chemical PhysicsVol. 163(22)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), FMP Technology (Germany) (DE), Future University Hakodate (JP)
Openalex Percentile: Top 29%
Block Copolymer Self-Assembly
0.52
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