Nanoscale materials modelling using neural networks

Nikolaos Asproulis, Dimitris Drikakis

Research output: Contribution to journalArticle

21 Citations (Scopus)

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 - 1 Mar 2009

Keywords

  • materials modelling
  • molecular dynamics
  • nanotechnology
  • neural networks

Fingerprint Dive into the research topics of 'Nanoscale materials modelling using neural networks'. Together they form a unique fingerprint.

  • Cite this