Subnano Pt Particles from a First-Principles Stochastic Surface Walking Global Search

Area of Science:

• Physical Chemistry
• Materials Science
• Computational Chemistry

Background:

• Subnanometer transition metal particles are crucial in chemistry but challenging to characterize.
• Determining the structure of subnanometer clusters is essential for predicting their properties.

Purpose of the Study:

• To explore structure configurations of subnanometer platinum-nitrogen (PtN) clusters (N=12-46).
• To identify stable structures and understand the evolution of their architecture and properties.

Main Methods:

• Utilized first-principles Stochastic Surface Walking (SSW) global search.
• Conducted parallel SSW searches to collect thousands of structure candidates for each cluster.
• Analyzed structural properties, stability, electronic characteristics, and binding energies.

Main Results:

• Discovered 20 new global minima structures across 35 PtN clusters.
• Identified magic number clusters (N=14, 18, 22, 27, 36, 44) with enhanced stability.
• Observed metallic characteristics, diminishing HOMO-LUMO gap, reduced binding energy, and higher Fermi level compared to bulk platinum.
• Revealed the emergence of a rigid core and soft shell 3D architecture for N > 22, with lattice match being key for stability.

Conclusions:

• First-principles global search is effective for revealing subnanometer cluster structures.
• PtN clusters exhibit unique electronic properties and high chemical activity due to their size and structure.
• The core-shell architecture is a significant structural motif in these subnanometer clusters.