"Compressing liquid": an efficient global minima search strategy for clusters.

Area of Science:

• Computational Chemistry
• Materials Science
• Nanotechnology

Background:

• Determining the global minimum energy structure of atomic clusters is crucial for understanding their properties.
• Existing global search methods can be computationally expensive and may not always find the true global minimum.

Purpose of the Study:

• To introduce and evaluate a novel global search strategy, the "compressing liquid" method, for identifying the lowest energy structures of atomic clusters.
• To assess the efficiency of this new method on Lennard-Jones clusters and medium-sized silicon clusters.

Main Methods:

• The "compressing liquid" strategy involves using a random liquid structure fragment as the initial geometry.
• Iterative "compressing" operations and Monte Carlo adjustments of atomic positions, followed by structural optimization, are performed.
• The method was applied to Lennard-Jones clusters and silicon clusters (Si(n), n=40-60).

Main Results:

• The "compressing liquid" method demonstrated fair efficiency in finding global minima for Lennard-Jones clusters.
• For medium silicon clusters, the method successfully identified the best candidates for most sizes.
• Novel non-fullerene-based structures were discovered for certain silicon cluster sizes, which were not found using endohedral-fullerene strategies.

Conclusions:

• The "compressing liquid" method is a highly efficient approach for the global minima search of atomic clusters.
• This new strategy offers a promising alternative for exploring complex cluster energy landscapes and discovering new structural motifs.