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.
Authors
- Nydia Roxana Varela-Rosales (ORCID: https://orcid.org/0000-0002-3703-6117)
- Michael Engel (ORCID: https://orcid.org/0000-0002-7031-3825)
Institutions
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- FMP Technology (Germany) (DE)
- Future University Hakodate (JP)
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