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10:37
Spatial Separation of Molecular Conformers and Clusters
Published on: January 9, 2014
Generation and characterization of low-energy structures in atomic clusters
J M C Marques1, A A C C Pais, P E Abreu
1Departamento de Química, Universidade de Coimbra, 3004-535 Coimbra, Portugal. qtmarque@ci.uc.pt
Journal of Computational Chemistry
|November 3, 2009
Summary
Controlling argon cluster structures during optimization is influenced by initial box shape and volume. Analysis reveals correlations between energy, nearest neighbors, and atomic distances in optimized clusters.
Area of Science:
- Computational physics and chemistry
- Atomic and molecular clusters
- Materials science
Background:
- Understanding atomic cluster structures is crucial for materials science.
- Local optimization methods are widely used but require careful parameterization.
- The influence of initial conditions on final optimized structures is not fully understood.
Purpose of the Study:
- To investigate factors controlling the structure of argon clusters during local optimization.
- To assess the impact of initial structure generation parameters (box volume and shape).
- To characterize the optimization process using nearest-neighbor analysis.
Main Methods:
- Local optimization of argon clusters (30-55 atoms).
- Generation of initial structures within boxes of varying volume and shape.
- Nearest-neighbor analysis to characterize final optimized structures.
- Correlation analysis between optimized energy, nearest neighbors, and interatomic distances.
Main Results:
- Initial box dimensions significantly affect the resulting argon cluster structures.
- Optimized cluster energy correlates with the number of nearest neighbors.
- The degree of structural preservation from initial to optimized states varies.
- Average departure from the diatomic reference distance is linked to cluster energy.
Conclusions:
- Box parameters are critical for controlling argon cluster structures in local optimization.
- Nearest-neighbor analysis provides insights into the energy landscape of atomic clusters.
- This methodology aids in exploring complex energy landscapes for cluster research.
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