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

Global optimization of binary Lennard-Jones clusters using three perturbation operators.

Tao Ye1, Ruchu Xu, Wenqi Huang

  • 1School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China. yeetao@gmail.com

Journal of Chemical Information and Modeling
|February 22, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces the 3OP algorithm for global optimization of binary Lennard-Jones clusters. The novel heuristic efficiently identifies global minima by navigating local minima, discovering 12 new ones.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Chemical Physics

Background:

  • Global optimization of binary Lennard-Jones clusters is computationally demanding.
  • Challenges include numerous local minima and the need to optimize both atomic positions and types.
  • This requires addressing both continuous and combinatorial optimization problems.

Purpose of the Study:

  • To present a novel heuristic algorithm, termed 3OP, for efficient global optimization of binary Lennard-Jones clusters.
  • To demonstrate the algorithm's capability in navigating complex potential energy surfaces and identifying global minima.
  • To validate the algorithm's performance on a substantial set of benchmark instances.

Main Methods:

  • The proposed 3OP algorithm utilizes three distinct perturbation operators.
  • These operators facilitate efficient transitions between local minima towards lower energy states.
  • The algorithm systematically explores the energy landscape to locate the global minimum.

Main Results:

  • The 3OP algorithm was evaluated on 96x6 instances with up to 100 atoms.
  • It successfully identified most known putative global minima from the Cambridge Cluster Database.
  • Crucially, the algorithm discovered 12 previously unknown global minima.

Conclusions:

  • The 3OP algorithm offers an effective approach for the global optimization of binary Lennard-Jones clusters.
  • Its ability to escape local minima and discover new low-energy structures is a significant advancement.
  • This method enhances the accuracy of cluster structure prediction in computational chemistry.