Computational roadmap of stable Mo-S nanoclusters: atomic structures and magic compositions.

Area of Science:

• Materials Science
• Computational Chemistry
• Nanotechnology

Background:

• Nanoparticles possess unique properties crucial for technological applications.
• Determining the atomic structure of nanoclusters is experimentally challenging.
• Molybdenum-sulfur (Mo-S) nanoclusters are of interest due to their potential applications.

Purpose of the Study:

• To investigate the stability and predict the crystal structures of Mo-S nanoclusters.
• To identify energetically favorable and decomposition-resistant Mo_nS_m compositions.
• To explore the potential of Mo₁₀S₂₀ nanoclusters in thin films and nanotubes.

Main Methods:

• Utilized the evolutionary algorithm USPEX for structure prediction.
• Employed density functional theory (DFT) calculations for stability analysis.
• Applied a selection method based on "magic" clusters, using second-order energy differences and dissociation energies.

Main Results:

• Predicted 29 stable Mo-S nanocluster structures, with only 7 previously synthesized.
• Identified energetically favorable compositions for Mo_nS_m nanoclusters (1 ≤ n ≤ 15, 1 ≤ m ≤ 20).
• Discovered a metastable planar Mo₁₀S₂₀ ring, the smallest known planar Mo-S nanostructure, and studied its thin film and nanotube stability.

Conclusions:

• The study provides significant insights into the structural stability of Mo-S nanoclusters.
• Findings contribute to the understanding of nanocluster chemistry and the design of novel nanomaterials.
• Identified promising Mo-S nanocluster compositions for future experimental synthesis and applications.