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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Published on: April 8, 2020

Revised basin-hopping Monte Carlo algorithm for structure optimization of clusters and nanoparticles.

Gustavo G Rondina1, Juarez L F Da Silva

  • 1Instituto de Física de São Carlos, Universidade de São Paulo , Caixa Postal 369, 13560-970, São Carlos, SP, Brazil.

Journal of Chemical Information and Modeling
|August 21, 2013
PubMed
Summary
This summary is machine-generated.

This study enhances the Basin-Hopping Monte Carlo (BHMC) algorithm for global optimization of atomic clusters and nanoparticles. The improved BHMC method efficiently finds stable structures, aiding in understanding nanoparticle and cluster atomic arrangements.

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10:37

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Area of Science:

  • Computational chemistry
  • Materials science
  • Statistical mechanics

Background:

  • Global optimization is crucial for determining the lowest energy structures of atomic clusters and nanoparticles.
  • Traditional Basin-Hopping Monte Carlo (BHMC) methods face challenges in efficiently exploring complex potential energy landscapes.

Purpose of the Study:

  • To present an improved Basin-Hopping Monte Carlo (BHMC) algorithm for unbiased global optimization of clusters and nanoparticles.
  • To enhance the efficiency and accuracy of global structure searches for atomic systems.

Main Methods:

  • Incorporation of eleven novel local and nonlocal trial operators tailored for clusters and nanoparticles.
  • Implementation of static and dynamic operator selection strategies.
  • Inclusion of a filter operator to manage unphysical solutions within the BHMC framework.

Main Results:

  • The revised BHMC method successfully reproduced known global minimum structures for various systems, including Lennard-Jones and Sutton-Chen clusters and nanoparticles.
  • The implementation demonstrated improved efficiency compared to standard BHMC for several systems.
  • Previously unknown global minimum structures were identified for certain cluster and nanoparticle systems.

Conclusions:

  • The enhanced BHMC algorithm provides a robust and efficient tool for global optimization of atomic clusters and nanoparticles.
  • This method facilitates theoretical investigations into the atomic structures of nanomaterials.
  • The improvements offer a valuable approach for discovering novel low-energy configurations in materials science.