Artificial neural network investigation of hardness and fracture toughness of hydroxylapatite

EVİS Z., Arcaklioglu E.

CERAMICS INTERNATIONAL, vol.37, no.4, pp.1147-1152, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 4
  • Publication Date: 2011
  • Doi Number: 10.1016/j.ceramint.2010.10.037
  • Journal Name: CERAMICS INTERNATIONAL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1147-1152
  • Keywords: Hardness, Hydroxylapatite, Fracture toughness, Artificial neural network, MECHANICAL-PROPERTIES, NANOCRYSTALLINE HYDROXYAPATITE, MICROSTRUCTURE, DENSIFICATION, PREDICTION, GLASS
  • Middle East Technical University Affiliated: Yes

Abstract

Hardness and fracture toughness of hydroxylapatite were investigated by artificial neural network (ANN). Hardness and fracture toughness of hydroxylapatite were predicted by using its sintering temperature, sintering time, relative density, and grain size with ANN. It was found that prediction results of its hardness and fracture toughness closely matched with the experimental results. (C) 2010 Elsevier Ltd and Techna Group S.r.l. All rights reserved.