Graph theory meets ab initio molecular dynamics: atomic structures and transformations at the nanoscale.

Area of Science:

• Computational chemistry
• Materials science
• Chemical physics

Background:

• Characterizing molecular structure and dynamics is crucial for understanding chemical processes.
• Identifying low-energy isomers and reaction pathways remains a significant challenge in computational chemistry.

Purpose of the Study:

• To introduce novel social permutation invariant coordinates for describing atomic environments.
• To demonstrate the utility of these coordinates in conjunction with ab initio metadynamics for exploring molecular transformations.

Main Methods:

• Development of social permutation invariant coordinates based on the largest eigenvalue and eigenvector of the contact matrix.
• Application of these coordinates within an ab initio metadynamics framework.
• Utilizing the invariance to permutations of identical atoms for robust structural analysis.

Main Results:

• The proposed coordinates effectively capture the signature of order-disorder transitions.
• Combined with ab initio metadynamics, they facilitate the discovery of low-energy molecular and nanocluster isomers.
• Enables blind exploration of isomerization, association, and dissociation reactions.

Conclusions:

• Social permutation invariant coordinates offer a powerful new descriptor for molecular systems.
• This approach enhances the efficiency and scope of computational studies for molecular discovery and reaction exploration.