How to Quantify and Avoid Finite Size Effects in Computational Studies of Crystal Nucleation: The Case of Heterogeneous Ice Nucleation
Sarwar Hussain, Amir Haji-Akbari

TL;DR
This study investigates finite size effects in computational crystal nucleation studies, especially for heterogeneous ice nucleation, and proposes criteria to minimize these effects for more accurate rate calculations.
Contribution
It introduces a jumpy forward flux sampling approach to analyze how system size influences nucleation rates and identifies regimes where finite size effects are minimized.
Findings
Finite size effects depend on INP size and nucleus spanning.
Proximal nuclei can artificially enhance nucleation.
Minimal finite size effects occur when nuclei are neither spanning nor proximal.
Abstract
Computational studies of crystal nucleation can be impacted by finite size effects, primarily due to unphysical interactions between crystalline nuclei and their periodic images. It is, however, not always feasible to systematically investigate the sensitivity of nucleation kinetics and mechanism to system size due to large computational costs of nucleation studies. Here, we use jumpy forward flux sampling to accurately compute the rates of heterogeneous ice nucleation in the vicinity of square-shaped model structureless ice nucleating particles (INPs) of different sizes, and identify three distinct regimes for the dependence of rate on the INP dimension, . For small INPs, the rate is a strong function of due to artificial spanning of critical nuclei across the periodic boundary. Intermediate-sized INPs, however, give rise to the emergence of non-spanning 'proximal` nuclei that…
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