Tarek Othman

In this study, the focus was on investigating the coefficient of friction (COF), wear, and corrosion characteristics of an AA5083 aluminum matrix composite reinforced with multi-walled carbon nanotubes/graphene nanoparticles (MWCNs/GNs). The composite was fabricated using the stir-rheo-squeeze casting technique. Several key factors were explored, including the volume fraction of MWCNs/GNs, sliding speed, applied load, and wear mechanism. The research highlighted the improved tribological performance of the MWCN/GN-reinforced nanocomposite compared to the AA5083 matrix without any reinforcement. Throughout the investigation, raising the weight fraction of MWCNs/GNs guided to a gradual decline COF, wear mass loss, and corrosion rate. The optimal improvement was achieved at a volume fraction of 2 wt% of MWCNs/GNs. On the other hand, both the applied load and sliding speed were found to have an adverse effect, resulting in increased coefficient of friction, wear mass loss, and corrosion rate. The wear behavior exhibited a linear relationship across all ranges of applied loads, indicating consistent wear characteristics. To gain insights into the microstructure changes, (SEM) and (EDX) were utilized before and after the wear tests. The reinforcement of MWCNs/GNs acted as a solid lubricant, effectively reducing friction between the aluminum matrix and counterpart material. This enhancement substantially increased the wear resistance of the AA5083 matrix composite as the COF and corrosion rate reached the optimal value of 0.31 and 430 mm/year, respectively.

Carbon-based nanomaterials are showing promising potential in a variety of applications. Owing to their distinctive structure, multiwalled carbon nanotubes (MWCNTs) posses unique thermal, mechanical, and optical properties. These properties allowed MWCNTs to surpass other nanomaterials when it comes to nanofluids' applications. They are proven to have a significant role in the overall fluid thermophysical characteristics. This role can either be in compliance with the application requirements or not. Besides, this role's scale depends on the magnitude of the interaction between the MWCNTs and the base fluid molecules. In this chapter, the underlying mechanisms that govern these interactions are discussed, focusing on nanofluid stability, thermal conductivity, heat capacity, wettability, and rheological properties. Besides, two main applications of MWCNT-based nanofluids in metal cutting and solar energy are provided. This work aims to provide an in-depth and holistic understanding of MWCNT-based nanofluid properties and how these properties affect the nanofluid performance in different applications.

The current study aims to explore the tensile fracture mechanism and thermo-mechanical efficiency of polyamide-6 (PA6) reinforced with titanium dioxide (TiO2) and multiwalled carbon nanotubes (MWCNTs). The uniform dispersion of the MWCNTs and appreciable interfacing between PA6, TiO2, and MWCNTs were revealed in the fractography figures. The crystallization temperature and degree of crystallinity have been enhanced by the addition of nanoparticles to the PA6 matrix. Young?s modulus, tensile strength, and Charpy impact strength improved proportionally concerning reinforcement content. The essential work of fracture (EWF) method was applied to evaluate the toughening and fracture behavior of PA6 hybrid systems. Considerable improvement (+60.6%) in the EWF of PA6?TiO2?MWCNT nanocomposites was observed at 4 wt.% CNT and 2 wt.% TiO2. Limiting oxygen index (LOI) findings demonstrate that a polymer with a combination containing titanium dioxide and multiwalled carbon nanotubes has a highly substantial retardant influence. As a result, the TiO2?CNT combination acts as a synergist filler, offering versatile PA6 composite products.

A statistical optimization based on experimental work was conducted to consider ultimate tensile strength (UTS) and elongation of dissimilar joints between AA5454 and AA7075 by friction stir weld (FSW). The goal of this work is to develop a comparative study of the optimization of FSW parameters using different orthogonal arrays, i.e., L12 and L16. Four parameters correlated to softening and forging requirements (rotational speed, traverse speed, tilt angle, and plunge depth), one parameter associated with the location of base metal in the dissimilar joint, and two parameters related to an FSW tool (pin profile and Dshoulder/dpin ratio) were considered and arranged in the employed arrays. Moreover, the investigation explored the microstructure and fractography of dissimilar joints and base metals by using optical and scanning electron microscopes. The results showed that the L16OA is more accurate than L12OA for the optimization of seven parameters due to the small statistical errors. For UTS, the errors range from 0.78 to 24% for L16OA and from 27.23 to 44.14% for L12OA. For elongation, the errors run from 11 to 12.9% for L16OA and from 33.77 to 49.73% for L12OA. The accuracies of generated models range from 50 to 99.5% for L16OA and range from 30.7 to 94.9% for L12OA. Tightening the levels (narrow domain) is the main reason for switching some optimum levels between both arrays. The highest UTS obtained is 221 MPa based on the optimum levels attained from L16OA, and the highest elongation is 12.83% according to the optimum levels acquired from L12OA. Despite the deficiency of effective intermixing, the study revealed that FSW acceptably could assemble joints between AA5454 and AA7075, presenting the proficiency of FSW with welding dissimilar aluminum alloys.