Enhancing DFT-based energy landscape exploration by coupling quantum mechanics and static modes.

Area of Science:

• Computational Materials Science
• Surface Science
• Solid-State Physics

Background:

• Investigating atomic-scale diffusion at surfaces, interfaces, and bulk is computationally intensive.
• Traditional multi-scale modeling requires extensive prospective calculations and significant human resources.
• Accurate prediction of atomic diffusion is crucial for understanding material properties and processes.

Purpose of the Study:

• To present a novel workflow coupling Static Mode (SM) and Quantum Mechanics (QM) for efficient atomic diffusion studies.
• To reduce the computational time and human workload associated with *ab initio* calculations for diffusion.
• To screen, score, and select significant events for studying atomic diffusion.

Main Methods:

• Coupling of Static Mode (SM) calculations with Quantum Mechanics (QM) for energy landscape exploration.
• Systematic SM exploration to determine strain fields under localized stresses.
• Density Functional Theory (DFT) calculations to refine and relax the most relevant atomic deformations.

Main Results:

• The QM-SM approach effectively guides the exploration of energy landscapes by optimizing significant event selection.
• Demonstrated reduction in exploration time and human load for *ab initio* diffusion studies.
• Successful application in identifying atomic diffusion for a molecule grafting on an oxide surface and a point defect in a bulk material.

Conclusions:

• The QM-SM workflow provides an efficient strategy for identifying and studying atomic diffusion.
• This approach significantly accelerates the screening and selection of relevant atomic events.
• The method is versatile, applicable to diverse systems like surface functionalization and bulk defect dynamics.