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Related Experiment Video

Updated: Jun 29, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Global optimization method for cluster structures.

Yin Wang¹, Jun Zhuang, Xi-Jing Ning

¹Applied Ion Beam Physics Laboratory, Institute of Modern Physics, Fudan University, Shanghai 200433, China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|October 15, 2008

Summary

This summary is machine-generated.

A novel time-going-backward quasidynamics method enhances global optimization for cluster structures. This approach efficiently overcomes energy barriers, yielding more stable configurations than traditional annealing and genetic algorithms.

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Last Updated: Jun 29, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

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Published on: February 15, 2017

Area of Science:

Computational Chemistry
Materials Science
Chemical Physics

Background:

Global optimization of cluster structures is crucial for understanding material properties.
Traditional methods like annealing can get trapped in local minima, failing to find the most stable configurations.

Purpose of the Study:

To develop and evaluate a new quasidynamics method for efficient global optimization of atomic and molecular clusters.
To demonstrate the method's superiority over existing techniques in overcoming potential energy barriers and finding global minima.

Main Methods:

Development of a time-going-backward quasidynamics algorithm.
Application to Lennard-Jones (LJ) clusters (38 atoms) and C60 clusters using the Brenner potential.
Comparison with common annealing methods and a genetic algorithm for small carbon clusters (Cn, n=21-30).

Main Results:

The quasidynamics method shows a significantly higher probability of overcoming potential barriers compared to common annealing methods.
The method successfully identified the most stable isomers for LJ38 and C60 clusters, which are challenging for standard approaches.
For small carbon clusters (n=21-30), the quasidynamics method achieved lower potential energies than a genetic algorithm.

Conclusions:

The time-going-backward quasidynamics method is a powerful tool for global optimization of cluster structures.
This novel approach offers improved efficiency and accuracy in finding stable molecular and atomic configurations.
The method holds promise for advancing research in materials science and computational chemistry.