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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
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Fast optimization of binary clusters using a novel dynamic lattice searching method.

Xia Wu1, Wen Cheng1

  • 1School of Chemistry and Chemical Engineering, Anqing Normal University, Anqing 246011, People's Republic of China.

The Journal of Chemical Physics
|October 3, 2014
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Summary
This summary is machine-generated.

A new BDLS-ILS method efficiently optimizes binary clusters, overcoming limitations of previous approaches for larger systems. This computational method enhances the global optimization of binary clusters, including complex alloy structures.

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Area of Science:

  • Computational chemistry and materials science
  • Investigating atomic-scale structures and properties
  • Developing novel algorithms for molecular modeling

Background:

  • Global optimization of binary clusters presents significant challenges.
  • Existing methods like Binary Dynamic Lattice Searching (BDLS) are limited to small cluster sizes.
  • The homotop problem in binary clusters requires advanced solutions beyond simple lattice searching.

Purpose of the Study:

  • To develop an efficient and robust method for the global optimization of binary clusters.
  • To address the limitations of existing Binary Dynamic Lattice Searching (BDLS) methods.
  • To introduce a hybrid approach combining BDLS with Iterated Local Search (ILS) for enhanced performance.

Main Methods:

  • Development of the Binary Dynamic Lattice Searching with Iterated Local Search (BDLS-ILS) method.
  • Utilizing Iterated Local Search (ILS) to solve the homotop problem, enabling atomic exchange.
  • Application to binary Lennard-Jones clusters up to 100 atoms and (AuPd)79 clusters.

Main Results:

  • The BDLS-ILS method demonstrates significant efficiency in optimizing binary clusters.
  • Successful application to binary Lennard-Jones clusters up to 100 atoms.
  • Accurate study of geometrical structures for (AuPd)79 clusters using DFT-fit Gupta potential parameters.

Conclusions:

  • The proposed BDLS-ILS method is an efficient approach for the global optimization of binary clusters.
  • The integration of ILS effectively resolves the homotop problem, extending applicability to larger systems.
  • The method shows promise for studying complex alloy cluster structures.