Nanoscale materials modelling using neural networks

Nikolaos Asproulis, Dimitris Drikakis

Research output: Contribution to journalReview articlepeer-review

Abstract

This paper presents the development of a neural network approach in conjunction with molecular dynamics simulations. Molecular dynamics encompasses limitations with regard to computational times required for fine grain simulations. Neural networks can be used as an efficient tool for broadening the computational envelope in parametric investigations of materials using molecular simulations. Here, this concept is validated for a molecular system with an applied side shear, consisting of 560 molecules surrounding a cylindrical void.

Original languageEnglish
Pages (from-to)514-518
Number of pages5
JournalJournal of Computational and Theoretical Nanoscience
Volume6
Issue number3
DOIs
Publication statusPublished - Mar 2009
Externally publishedYes

Keywords

  • Materials modelling
  • Molecular dynamics
  • Nanotechnology
  • Neural networks

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