Article, 2024

Accelerating structure search using atomistic graph-based classifiers

The Journal of Chemical Physics, ISSN 1089-7690, 0021-9606, Volume 161, 1, Page 014713, 10.1063/5.0207801

Contributors

Slavensky, Andreas Møller [1] Hammer, Bjørk 0000-0002-7849-6347 (Corresponding author) [1]

Affiliations

  1. [1] Aarhus University
    2. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD]

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.

Keywords

Au12, Global, Lennard-Jones, Voronoi, Voronoi tessellation method, algorithm, atomic system, classifier, combination, dataset, discrimination, energy expression, energy landscape, energy surface, expression, filtering method, first-principles, global optimization, global optimization problems, graph theory, graph-based classifiers, landscape, method, minima, nanoparticles, olivine, optimization, optimization problem, potential energy landscape, potential energy surface, problem, pyroxene, region, risk, risk of stagnation, search, sorting, spectral graph theory, stagnation, structure, structure search, surface, system, tessellation method, theory, use

Funders

  • Danish National Research Foundation
  • The Velux Foundations

Data Provider: Digital Science

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