AFFCK: Adaptive Force-Field-Assisted ab Initio Coalescence Kick Method for Global Minimum Search

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Physics

Background:

• Global optimization of molecular structures is crucial but often computationally expensive.
• Existing methods like Coalescence Kick (CK) can be slow and get stuck in local minima.
• There is a need for faster and more efficient global optimization techniques.

Purpose of the Study:

• To introduce and evaluate the Adaptive Force-Field-Assisted Coalescence Kick (AFFCK) method.
• To demonstrate AFFCK's ability to accelerate the search for global minima in molecular clusters.
• To compare AFFCK's performance against traditional ab initio CK methods.

Main Methods:

• Developed AFFCK, integrating classical force field (FF) optimization as an intermediate step.
• Employed system-specific, on-the-fly FF development.
• Incorporated symmetry operations and a structure-recognition routine to enhance search diversity and efficiency.
• Utilized Density Functional Theory (DFT) for final energy calculations.

Main Results:

• AFFCK significantly accelerates the generation of stationary points compared to pure ab initio CK.
• FF energies accurately predict DFT energies, enabling effective screening of thousands of structures.
• AFFCK identified a new, significantly lower-energy global minimum for Pt8 clusters.
• The method confirmed known global minima for boron clusters (B5(-), B8, B9(-)).

Conclusions:

• AFFCK offers a substantial speed improvement over traditional ab initio CK for global optimization.
• The integration of FF optimization and symmetry operations enhances efficiency and search space coverage.
• AFFCK is a powerful tool for exploring potential energy surfaces, particularly for systems like metal clusters.