Year: 2025
Type: preprint
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 AB$_{13}$ 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.
Source: arXiv (Cornell University)
DOI: 10.1063/5.0295910
Authors: Varela-Rosales, Nydia Roxana, Engel, Michael
Language: English
Subfield: Physical and Theoretical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
Funder: Deutsche Forschungsgemeinschaft
Award: G4702395205
OpenAlex ID: W7075994005
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