Investigation On Mechanical And Microstructural Properties Of Friction Stir Welded Aa7075 Gnps Composites

Abstract

In this research work, aluminum alloy AA7075 reinforced with graphene nano platelets (GNPs) newlineprocessed using stir casting technique. Composites were produced using 0, 0.5, 1 and 1.5 Wt.% newlineGNPs. The 1 Wt.% GNPs composites achieved better result as compared to other Wt.% of newlineGNPs. Further, AA7075/GNPs composites were joined successfully using friction stir welding newline(FSW) process. Microstructure of the joints was examined using optical microscope (OM), newlinescanning electron microscope (SEM), and transmission electron microscope (TEM). The newlinemechanical characteristics such as microhardness, tensile strength and wear resistance were newlineinvestigated. Further, X- ray diffraction (XRD), and Raman spectroscopy studied for newlineidentifying the intermetallic compounds. Microstructure of FSW joint exhibits significant newlinechanges in the microstructure after FSW and reported fine and uniform dispersion of GNPs in newlinethe nugget zone witnessing formation of precipitates and well bonding between aluminum alloy newlineand GNPs, resulting in better quality of welds. Especially fine grains were observed in the newlineadvancing side than that of the retreating side as a result higher hardness of 141 HV. Further, newlineFSW process results in enhancement of 75% joint efficiency using optimal process parameters. newlineJoint fracture examination reports ductile failure of joints in heat affected zone represents newlineweakest part with formation of dimples. In addition, comprehensive evaluation of FSW joint newlineassessment is carried out using two different tool pin profiles such as square (SQ) and newlinecylindrical threaded. SQ tool enabled superior material stirring and better dispersion of GNPs, newlineproducing fine, equiaxed grains in the nugget zone. Electron back scatter diffraction analysis newlinepresents reduction in grain size of base material from 38 µm to 9 µm in the nugget zone, newlineresulting in significant enhancement of mechanical properties. In addition machine learning newlinetechniques, the random forest and extreme gradient boost regressor predicts the accurate results newlinefor ultimate tensile strength and microh