Experimental Investigation and Machine Learning Modeling of Tribological Characteristics of AZ31/B<sub>4</sub>C/GNPs Hybrid Composites

Experimental Investigation and Machine Learning Modeling of Tribological Characteristics of AZ31/B<sub>4</sub>C/GNPs Hybrid Composites

In this study, the AZ31 hybrid composites reinforced with boron carbide (B<sub>4</sub>C) and graphene nano-platelets (GNPs) are prepared by the stir casting method. The main aim of the study is to study the effect of various wear parameters (reinforcement percentage (R), applied load (L)...

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Main Authors: Dhanunjay Kumar Ammisetti, Bharat Kumar Chigilipalli, Baburao Gaddala, Ravi Kumar Kottala, Radhamanohar Aepuru, T. Srinivasa Rao, Seepana Praveenkumar, Ravinder Kumar
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Crystals
Subjects:
magnesium
stir casting
hybrid composites
wear rate (WR)
coefficient of friction (COF)
machine learning
Online Access:https://www.mdpi.com/2073-4352/14/12/1007
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