Wear Characterization and Coefficient of Friction Prediction Using a Convolutional Neural Network Model for Chromium-Coated SnSb11Cu6 Alloy

Wear Characterization and Coefficient of Friction Prediction Using a Convolutional Neural Network Model for Chromium-Coated SnSb11Cu6 Alloy

Enhancing the durability and tribological performance of babbitt alloys is critical for high-stress applications in automotive, marine, and industrial machinery. The present study explores the electrodeposition of chromium coatings on SnSb11Cu6 alloys to improve their microstructural, mechanical, an...

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Bibliographic Details
Main Authors: Mihail Kolev, Vladimir Petkov, Veselin Petkov, Rositza Dimitrova, Shaban Uzun, Boyko Krastev
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Lubricants
Subjects:
SnSb11Cu6
chromium coatings
wear behavior
coefficient of friction
convolutional neural network
deep learning
Online Access:https://www.mdpi.com/2075-4442/13/5/200
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