Geometry optimization of atomic clusters using a heuristic method with dynamic lattice searching.

Area of Science:

• Computational materials science
• Chemical physics
• Condensed matter physics

Background:

• Determining the ground-state structure of atomic clusters is crucial for understanding their properties.
• Existing methods often struggle with large cluster sizes and complex potential energy landscapes.

Purpose of the Study:

• To present a novel global optimization method for finding the global-minimum structures of atomic clusters.
• To assess the efficiency and applicability of the method to Lennard-Jones and silver clusters.

Main Methods:

• Combines dynamic lattice searching with a two-phase local minimization technique.
• Applies the method to Lennard-Jones clusters (N=13-140) and silver clusters (N=13-140, 300) using the Gupta potential.

Main Results:

• The method demonstrates high efficiency in identifying global-minimum structures.
• Numerous new global minima were discovered for silver clusters, surpassing previous literature findings.
• Identified 12 particularly stable silver clusters within the size range N=13-140.

Conclusions:

• The developed global optimization method is a powerful and promising tool for theoretical determination of atomic cluster ground-state structures.
• The findings provide valuable insights into the stability and structural properties of silver clusters.
• The method's success suggests broader applicability to other atomic and molecular systems.