Computationally efficient characterization of potential energy surfaces based on fingerprint distances

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Physics

Background:

• Analyzing the network of potential energy minima and reaction pathways is crucial for understanding material properties.
• Calculating transition states and reaction pathways for multi-atomic systems is computationally intensive.

Purpose of the Study:

• To develop a computationally efficient method for analyzing the energy landscape of multi-atomic systems.
• To approximate the network of minima, their connectivity, and interconversion energies.

Main Methods:

• Combines the minima hopping global optimization method with the principle that uphill barriers increase with structural distance.
• Replaces exact transition state calculations with approximate concepts.

Main Results:

• Generates an approximate network of minima and their connectivity without significant additional computational cost.
• Provides a qualitative understanding of thermodynamic, dynamic, and structural properties via disconnectivity graph analysis.
• Identifies potential interconversion pathways for advanced methods like transition path sampling.

Conclusions:

• The developed method offers a computationally feasible approach to explore complex energy landscapes.
• It aids in predicting system properties and deciding on the necessity of exact transition state computations.
• Enables the discovery of physically relevant pathways for further detailed studies.