Finding Reaction Pathways with Optimal Atomic Index Mappings.

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Physics

Background:

• Discovering complex reaction pathways is computationally prohibitive with current density-functional theory (DFT) methods.
• Existing simulation techniques struggle with the vast number of energy evaluations and atomic mapping possibilities for intricate reactions.

Purpose of the Study:

• To develop a novel computational approach for efficiently identifying complex reaction and transformation pathways.
• To overcome the limitations of existing DFT methods in determining atomic mappings and exploring numerous intermediate states.

Main Methods:

• A penalty function invariant under index permutations was employed to bias the potential energy surface.
• Minima-hopping-based global optimization was performed on the biased potential energy surface to locate the global minimum (reaction product).
• The method was validated on a Lennard-Jones cluster (LJ38) and applied to C60 and C20H20 systems.

Main Results:

• The developed method successfully identified relevant intermediate states for the lowest energy reaction pathway in the benchmark LJ38 system.
• Significantly fewer intermediate states were required compared to previous methods for pathway discovery.
• Valuable insights into the synthesis of C60 and C20H20 molecules were obtained from the identified reaction pathways.

Conclusions:

• The novel computational strategy enables rapid and efficient discovery of complex reaction pathways.
• This approach significantly reduces the computational cost associated with exploring reaction mechanisms.
• The method provides crucial information for understanding and designing synthetic routes for complex molecules.