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Tribology is the study of moving surfaces, and it has a variety of effects on our lives. From an economic point of view, wear is one of the most important aspects of an industry’s viability. Parts of the machine can wear out, and they need to be replaced. This is especially important for polymer-based materials. Therefore, it is important to reduce maintenance costs and improve machine reliability in a variety of engineering applications through proper material selection. The present investigation deals with the fabrication of manganese dioxide (MnO2)/epoxy nanocomposite and investigates its tribological properties. The MnO2/epoxy nanocomposites were fabricated via a solution mixing technique. The phase identification and surface morphology of the sample was examined by X-ray diffractometer and field emission scanning electron microscope, respectively. The mass density, micro-hardness, and specific wear rate data of samples revealed that the mass density, micro-hardness, and wear resistance of the samples increased with the addition of MnO2 in the epoxy matrix. The nanocomposite sample containing 0.5 wt. % MnO2 loading in the epoxy matrix shows higher density, micro-hardness, and wear resistance compared to other samples. The result also shows that with the addition of MnO2 in the epoxy matrix, the coefficient of friction of the samples is increased. The percentage reduction in specific wear rate due to the addition of 0.5 wt. % MnO2 in neat epoxy is 68.10%, whereas the percentage increase in the coefficient of friction is 19.30%. The results of the analysis of variance show the effect of adding wt. % of MnO2 in the epoxy matrix is significant in the tribological responses. The worn surface analysis shows that the fatigue wear mode seems to be the dominating mode of wear for all samples as compared to the other modes of wear. The properties of MnO2/epoxy nanocomposite data revealed that the developed material may be used in the automotive industry as a structural material, fabrication of snow sled, ball bearing housing, or plastic gear materials with adequate lubrication.

Recent research has shown that carbon nanotube (CNT) acts as a model reinforcement material for fabricating nanocomposites. The addition of CNT as a reinforcing material into the matrix improves the mechanical, thermal, tribological, and electrical properties. In this research paper multiwalled carbon nanotube (MWCNT), with different weight percentage (5%, 10%, and 15%), was reinforced into manganese dioxide (MnO 2 ) matrix using solution method. The different weight % of MWCNT/MnO 2 nanocomposite powders was compacted and then sintered. The phase analysis, morphology, and chemical composition of the nanocomposites were examined by X-ray diffractometer, Field Emission Scanning Electron Microscope (FESEM), and Energy Dispersive X-Ray (EDX), respectively. The XRD analysis indicates the formation of MWCNT/MnO 2 nanocomposites. The FESEM surface morphology analysis shows that MnO 2 nanotube is densely grown on the surface of MWCNT. Further, microhardness of MWCNT/MnO 2 nanocomposite was measured and it was found that 10 wt% has higher microhardness in comparison to 5 and 15 wt%. The microhardness of the composites is influenced by mass density, nanotube weight fraction, arrangement of tubes, and dispersion of MWCNT in H 2 SO 4 (aq) solution.

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Engineering materials and their development are essential for a civilized society, and they have always played a key role in the industrialization of a country. The performance of materials can be increased by selecting appropriate fabrication process parameters. In this paper, the effect of fabrication processing parameters on multi-responses of lightweight material, namely, functionalized multiwalled carbon nanotubes-aluminum nanocomposite have been investigated through Taguchi-based grey relational analysis. Ethanol wt. %, milling time, compaction pressure, and sintering temperature were considered controlled parameters. Phase, surface morphology, and chemical compositions of the nanocomposite have been analyzed by X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray techniques. The scanning electron microscope images revealed that the optimal parameter combination is essential for decreasing void and crack formation during the powder metallurgy process and increasing the material performance index. Grey relational analysis was performed to evaluate optimal sample fabrication processing parameters by using grey relational grade as performance index measurement. The most influential parameter was investigated using main effect plots, interaction plots, contour plots, and analysis of variance. The results show that the optimal combination of sample fabrication parameters is A1B2C3D3. The results also show that the compaction pressure has a stronger correlation to the responses with a 46.92% contribution followed by sintering temperature. The % error between the predicted and experimental grey relational grades at the optimum-level combination is 1.83%. The Monte Carlo simulation data distribution plots show that the ranges of experimental mass density and hardness values are consistent with estimated simulated model values. Further, a regression equation has also been developed to establish the predictive model for the grey relational grade. The model analysis shows that the predictive model is adequate for evaluating grey relational grades. Therefore, this study confirms that the proposed approach can be a useful tool for improving materials’ performance.

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