Artificial neural network investigation of hardness and fracture toughness of hydroxylapatite

EVİS Z., Arcaklioglu E.

CERAMICS INTERNATIONAL, cilt.37, sa.4, ss.1147-1152, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 4
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.ceramint.2010.10.037
  • Dergi Adı: CERAMICS INTERNATIONAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1147-1152
  • Anahtar Kelimeler: Hardness, Hydroxylapatite, Fracture toughness, Artificial neural network, MECHANICAL-PROPERTIES, NANOCRYSTALLINE HYDROXYAPATITE, MICROSTRUCTURE, DENSIFICATION, PREDICTION, GLASS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.