The bcc coating of Lennard-Jones crystal nuclei vanishes with a change of local structure detection algorithm

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Main Authors: Gispen, Willem, Ortíz, Alberto Pérez de Alba, Dijkstra, Marjolein
Format: Preprint
Published: 2024
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author Gispen, Willem
Ortíz, Alberto Pérez de Alba
Dijkstra, Marjolein
author_facet Gispen, Willem
Ortíz, Alberto Pérez de Alba
Dijkstra, Marjolein
contents Since the influential work of ten Wolde, Ruiz-Montero, and Frenkel [Phys. Rev. Lett. 75, 2714 (1995)], crystal nucleation from a Lennard-Jones fluid has been regarded as a paradigmatic example of metastable crystal ordering at the surface of a critical nucleus. We apply seven commonly used local structure detection algorithms to characterize crystal nuclei obtained from transition path sampling simulations. The polymorph composition of these nuclei varies significantly depending on the algorithm used. Our results indicate that one should be very careful when characterizing the local structure near solid-solid and solid-fluid interfaces. Particles near such interfaces exhibit a local structure distinct from that of bulk fluid or bulk crystal phases. We argue that incorporating outlier detection into the local structure detection method is beneficial, leading to greater confidence in the classification results. Interestingly, the bcc coating nearly disappears when adopting a machine learning method with outlier detection.
format Preprint
id arxiv_https___arxiv_org_abs_2412_03276
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The bcc coating of Lennard-Jones crystal nuclei vanishes with a change of local structure detection algorithm
Gispen, Willem
Ortíz, Alberto Pérez de Alba
Dijkstra, Marjolein
Soft Condensed Matter
Since the influential work of ten Wolde, Ruiz-Montero, and Frenkel [Phys. Rev. Lett. 75, 2714 (1995)], crystal nucleation from a Lennard-Jones fluid has been regarded as a paradigmatic example of metastable crystal ordering at the surface of a critical nucleus. We apply seven commonly used local structure detection algorithms to characterize crystal nuclei obtained from transition path sampling simulations. The polymorph composition of these nuclei varies significantly depending on the algorithm used. Our results indicate that one should be very careful when characterizing the local structure near solid-solid and solid-fluid interfaces. Particles near such interfaces exhibit a local structure distinct from that of bulk fluid or bulk crystal phases. We argue that incorporating outlier detection into the local structure detection method is beneficial, leading to greater confidence in the classification results. Interestingly, the bcc coating nearly disappears when adopting a machine learning method with outlier detection.
title The bcc coating of Lennard-Jones crystal nuclei vanishes with a change of local structure detection algorithm
topic Soft Condensed Matter
url https://arxiv.org/abs/2412.03276