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

N Nydia Roxana Varela-Rosales (Institute for Multiscale Simulation, IZNF, Friedrich-Alexander-Universität Erlangen-Nürnberg 1 , 91058 Erlangen,) M Michael Engel

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.

Article Details

Volume / Issue Vol. 163, Issue 22
Published December 14, 2025
ISSN 0021-9606
Publisher American Institute of Physics

Journal Info

The Journal of Chemical Physics

American Institute of Physics

ISSN: 0021-9606 Physical Sciences

Authors (2)

N

Nydia Roxana Varela-Rosales

Institute for Multiscale Simulation, IZNF, Friedrich-Alexander-Universität Erlangen-Nürnberg 1 , 91058 Erlangen,

M

Michael Engel