Kick: constraining a stochastic search procedure with molecular fragments

Area of Science:

• Computational Chemistry
• Chemical Physics

Background:

• The Kick program by Bera et al. provides a foundation for exploring molecular potential energy surfaces.
• Efficiently searching these surfaces is crucial for understanding chemical reactions and molecular structures.

Purpose of the Study:

• To present an extension of the Kick program utilizing chemically sensible molecular fragments.
• To demonstrate the algorithm's capability in rapidly exploring reduced potential energy surface regions.
• To identify low-lying isomers and global energy minima for various chemical systems.

Main Methods:

• An automated stochastic search algorithm was developed, incorporating chemically sensible molecular fragments.
• The modified algorithm significantly reduces the search space of the potential energy surface.
• The approach was applied to diverse chemical systems, including transition metal clusters and dipeptide microsolvation.

Main Results:

• The enhanced algorithm achieves rapid exploration of the potential energy surface.
• Candidate global energy minima were identified for several chemical systems.
• The procedure proved effective for studying reactions involving transition metal clusters.
• The method was successfully applied to the microsolvation of a small dipeptide.

Conclusions:

• The extended Kick program offers a computationally efficient method for exploring molecular potential energy surfaces.
• This approach is valuable for identifying stable molecular isomers and reaction pathways.
• The algorithm's utility is demonstrated in complex chemical scenarios like transition metal cluster reactions and solvation studies.