Wear resistance and tribological properties of GNPs and MWCNT reinforced AlSi18CuNiMg alloys produced by stir casting

Turan M. E., Aydin F., Sun Y., Zengin H., Akınay Y.

Tribology International, cilt.164, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 164
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.triboint.2021.107201
  • Dergi Adı: Tribology International
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Chimica, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Stir casting, AlSiCuNiMg alloy, MWCNT, GNPs, Wear, Statistical analysis, TENSILE PROPERTIES, MECHANICAL-PROPERTIES, TEMPERATURE TENSILE, SI ALLOYS, AL, COMPOSITES, BEHAVIOR, MICROSTRUCTURE, PERFORMANCE, OPTIMIZATION
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

© 2021 Elsevier LtdThe present work aims to produce Multiwalled Carbon Nanotube (MWCNT) and Graphene Nanoplatelets (GNPs) reinforced AlSiCuNiMg alloy matrix composites via stir casting. The wear resistance and tribological performances of produced materials are examined by steel balls in dry sliding conditions under loads of 10 N, 20 N, and 40 N. The composites were produced by the combination of semi powder metallurgy and stir casting techniques and then a solid-solution + aging process was applied. The microstructures and phase-type of all specimens were examined by Scanning Electron Microscope (SEM), X-ray diffraction (XRD) and Transmission Electron Microscope (TEM). The results of this study show that the wear rates of the matrix decreased significantly with the addition of GNPs and MWCNTs reinforcements. When sliding speed increased, wear rates for all produced samples decrease. Graphene reinforced composite exhibited the best tribological behavior among the prepared samples. The design of test conditions and the analysis of output responses were studied by statistical analysis of Taguchi array, analysis of variance (ANOVA) and regression models. ANOVA indicated that the wear rate was mainly affected by material content followed by sliding speed and applied load. The wear mechanisms were identified by characterizations of worn surface, wear debris and counterface material.