Accelerating structure search using atomistic graph-based classifiers

Andreas Møller Slavensky; Bjørk Hammer

doi:10.1063/5.0207801

Accelerating structure search using atomistic graph-based classifiers

Andreas Møller Slavensky, Bjørk Hammer^*

^*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

2 Citationer (Scopus)

Abstract

We introduce an atomistic classifier based on a combination of spectral graph theory and a Voronoi tessellation method. This classifier allows for the discrimination between structures from different minima of a potential energy surface, making it a useful tool for sorting through large datasets of atomic systems. We incorporate the classifier as a filtering method in the Global Optimization with First-principles Energy Expressions (GOFEE) algorithm. Here, it is used to filter out structures from exploited regions of the potential energy landscape, whereby the risk of stagnation during the searches is lowered. We demonstrate the usefulness of the classifier by solving the global optimization problem of two-dimensional pyroxene, three-dimensional olivine, Au₁₂, and Lennard-Jones LJ₅₅ and LJ₇₅ nanoparticles.

Originalsprog	Engelsk
Artikelnummer	014713
Tidsskrift	Journal of Chemical Physics
Vol/bind	161
Nummer	1
ISSN	0021-9606
DOI	https://doi.org/10.1063/5.0207801
Status	Udgivet - jul. 2024

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Accelerating structure search using atomistic graph-based classifiers

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