Triboinformatic analysis and prediction of B4C and granite powder filled Al 6082 composites using machine learning regression models

Triboinformatic analysis and prediction of B4C and granite powder filled Al 6082 composites using machine learning regression models

Abstract The traditional methods for fabricating and evaluating wear properties are inherently time-consuming and financially demanding. To address these challenges, machine learning (ML) has emerged as a potent approach in predicting the mechanical and tribological behavior of advanced materials, i...

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Bibliographic Details
Main Authors: Amit Aherwar, Anamika Ahirwar, Vimal Kumar Pathak
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Al 6082-T651
B4C
Waste granite powder
Hybrid composites
Wear
Machine learning
Online Access:https://doi.org/10.1038/s41598-025-12603-5
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https://doi.org/10.1038/s41598-025-12603-5

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