Prediction of effect of fabrication parameters on the properties of B4C ceramic particle reinforced AA2024 matrix nanocomposites using neural networks-Reference-Cited by-同舟云学术

Prediction of effect of fabrication parameters on the properties of B4C ceramic particle reinforced AA2024 matrix nanocomposites using neural networks

Published:2024-06 Issue: Volume:39 Page:109279
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Varol Temel,Çanakçı Aykut,Özşahin Şükrü,Beder Murat,Akçay Serhatcan Berk

Publisher

Elsevier BV

Reference72 articles.

1. On the microstructural and mechanical responses of dual-matrix Al-Ni/SiC composites manufactured using accumulative roll bonding;Habba;Alex. Eng. J.,2023

2. The production of AA2024 Matrix-B4C particle reinforced composites by powder metallurgy method and investigation of their properties;Varol,2012

3. Processing, characterization, room temperature mechanical properties and fracture behavior of hot extruded multi-scale B4C reinforced 5083 aluminum alloy based composites;Alizadeh;Trans. Nonferrous Met. Soc. China (Engl. Ed.,2017

4. Influence of Mg addition and T6 heat treatment on microstructure, mechanical and tribological properties of Al–12Si–3Cu based alloy;Beder;Trans. Nonferrous Met. Soc. China,2021

5. Effects of Mn Content on Microstructure, Mechanical and Dry Sliding Wear Properties of Eutectic Al–Si–Cu Alloy;Alemdag;Met. Mater. Int.,2020

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1. Optimization of Dry Sliding Wear in Hot-Pressed Al/B4C Metal Matrix Composites Using Taguchi Method and ANN;Materials;2024-08-15

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