Prediction of wear properties of graphene-Si3N4 reinforced titanium hybrid composites by artificial neural network

In this study, we have employed artificial neural network (ANN) method to predict wear properties of titanium hybrid composites produced by powder metallurgy (PM) method. Titanium (Ti) was used as a matrix materials and graphene nano-platelets (GNPs)-Si3N4 were used as reinforcement materials in hyb...

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Veröffentlicht in:	Materials research express 2020-08, Vol.7 (8), p.086511
Hauptverfasser:	Mutuk, Tu ba, Gürbüz, Mevlüt, Mutuk, Halil
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial neural network Artificial neural networks Back propagation networks Graphene hybrid composite Hybrid composites Matrix materials Neural networks Platelets (materials) Powder metallurgy Si3N4 Silicon nitride Titanium Wear rate
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