Study on dry sliding wear behavior and machine learning models for wear rate prediction of nano hybrid 2219 MMCs reinforced with n-B4C & MoS2

This study examines the dry sliding wear behaviour of stir-cast Aluminium 2219 nano composites reinforced with nano boron carbide and a hybrid combination of nano boron carbide & Molybdenum disulfide particles. The wear properties were analyzed under varying conditions of sliding speed (0.65–13....

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Bibliographic Details
Published in:	Results in surfaces and interfaces 2025-08, Vol.20, p.100623, Article 100623
Main Authors:	Siddeshkumar, N.G., Manjula, H.M., Balakrishnan, K., Pramod, T.C., Latha Shankar, B., Ali Khan, Arshan, Pruthvi, H.M., Pawan K, Santosh, Nandakumar, M.B., Prabhu, Subramanya R., Durga Prasad, C.
Format:	Article
Language:	English
Subjects:	Dry sliding wear Machine learning Nano metal matrix composites Regression models Specific wear rate
Citations:	Items that this one cites
Online Access:	Get full text
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