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Artificial neural network potential for Au20clusters based on the first-principles.

Lingzhi Cao1,2, Yibo Guo1,2, Wenhua Han2

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Summary

This study develops an artificial neural network (ANN) potential for gold (Au) clusters, accelerating the search for ground-state structures (GSSs). The ANN potential accurately predicts structures and discovers new configurations for Au clusters.

Keywords:
artificial neural networkglobal optimizationgold clusterground state structure

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Nanotechnology

Background:

  • Finding ground-state structures (GSSs) of gold (Au) clusters is computationally challenging due to complex potential energy surfaces (PES).
  • Accurate prediction of cluster structures is crucial for understanding their properties and potential applications.

Purpose of the Study:

  • To develop a high-dimensional artificial neural network (ANN) potential for describing the PES of gold clusters.
  • To accelerate the search for GSSs of gold clusters using machine learning.

Main Methods:

  • A high-dimensional ANN potential was constructed for Au20 clusters.
  • The ANN was trained using data from density functional theory (DFT) calculations and a genetic algorithm.
  • The ANN potential's accuracy was validated by comparing its energy and force predictions with DFT results.

Main Results:

  • The ANN potential accurately reproduced the GSS search process for Au20 clusters, achieving low root-mean-square errors in energy and force.
  • The ANN potential demonstrated good scalability, predicting energies for smaller (Au16-19) and larger (Au21-25) clusters with minimal errors.
  • The application of the ANN potential led to the discovery of two novel structures for Au16 and Au21 clusters, along with several candidate lowest-energy structures.

Conclusions:

  • ANN potentials trained on DFT data can effectively reproduce GSS search processes.
  • This approach significantly accelerates the pre-screening of GSSs for clusters, especially for sizes near the training set.
  • The developed ANN potential is a promising tool for efficiently exploring the PES of gold clusters and discovering new stable configurations.