Search Results (5)

Hip joint collapse is a very common health problem. Many cases need a joint replacement, so nano-polymeric composites are an ideal alternative solution. Due to its mechanical properties and wear resistance, HDPE might be considered a suitable alternative to frictional materials. The current research focuses on using hybrid nanofiller TiO₂ NPs and nano-graphene with various loading compositions to evaluate the best loading amount. The compressive strength, modules of elasticity, and hardness were examined via experiments. The COF and wear resistance were evaluated via a pin-on-disk tribometer. The worn surfaces were analyzed based on 3D topography and SEM images. The HDPE samples with various compositions of 0.5%, 1.0%, 1.5%, and 2.0 wt.% filling content of TiO₂ NPs and Gr (with a ratio of 1:1) were analyzed. Results revealed that hybrid nanofiller with a composition of 1.5 wt.% exhibits superior mechanical properties compared to other filling compositions. Moreover, the COF and wear rate decreased by 27.5% and 36.3%, respectively. Full article

Aiming to develop more robust, mechanically advanced, Fused Filament Fabrication (FFF) materials, High-Density Polyethylene (HDPE) nanocomposites were developed in the current research work. Titanium Dioxide (TiO₂) was selected as filler to be incorporated into the HDPE matrix in concentration steps of 0.5, 2.5, 5, and 10 wt.%. 3D printing nanocomposite filaments were extruded in ~1.75 mm diameter and used to 3D print and test tensile and flexion specimens according to international standards. Reported results indicate that the filler contributes to increasing the mechanical strength of the virgin HDPE at certain filler and filler type concentrations; with the highest values reported to be 37.8% higher in tensile strength with HDPE/TiO₂ 10 wt.%. Morphological and thermal characterization was performed utilizing Scanning Electron Microscopy (SEM), Raman, Thermogravimetric Analysis (TGA), and Differential Scanning Calorimetry (DSC), while the results were correlated with the available literature. Full article

The selection of nanofillers and compatibilizing agents, and their size and concentration, are always considered to be crucial in the design of durable nanobiocomposites with maximized mechanical properties (i.e., fracture strength (FS), yield strength (YS), Young’s modulus (YM), etc). Therefore, the statistical optimization of the key design factors has become extremely important to minimize the experimental runs and the cost involved. In this study, both statistical (i.e., analysis of variance (ANOVA) and response surface methodology (RSM)) and machine learning techniques (i.e., artificial intelligence-based techniques (i.e., artificial neural network (ANN) and genetic algorithm (GA)) were used to optimize the concentrations of nanofillers and compatibilizing agents of the injection-molded HDPE nanocomposites. Initially, through ANOVA, the concentrations of TiO₂ and cellulose nanocrystals (CNCs) and their combinations were found to be the major factors in improving the durability of the HDPE nanocomposites. Further, the data were modeled and predicted using RSM, ANN, and their combination with a genetic algorithm (i.e., RSM-GA and ANN-GA). Later, to minimize the risk of local optimization, an ANN-GA hybrid technique was implemented in this study to optimize multiple responses, to develop the nonlinear relationship between the factors (i.e., the concentration of TiO₂ and CNCs) and responses (i.e., FS, YS, and YM), with minimum error and with regression values above 95%. Full article

In recent years, the development and use of polymeric nanocomposites in creating advanced materials has expanded exponentially. A substantial amount of research has been done in order to design polymeric nanocomposites in a safe and efficient manner. In the present study, the impact of processing parameters, such as, barrel temperature, and residence time on the mechanical and thermal properties of high density polyethylene (HDPE)-TiO₂ nanocomposites were investigated. Additionally, scanning electron microscopy and X-ray diffraction spectroscopy were used to analyze the dispersion, location, and phase morphology of TiO₂ on the HDPE matrix. Mechanical tests revealed that tensile strength of the fabricated HDPE-TiO₂ nanocomposites ranged between 22.53 and 26.30 MPa, while the Young’s modulus showed a consistent increase as the barrel temperature increased from 150 °C to 300 °C. Moreover, the thermal stability decreased as the barrel temperature increased. Full article

The current study presents an investigation on the optimization of injection molding parameters of HDPE/TiO₂ nanocomposites using grey relational analysis with the Taguchi method. Four control factors, including filler concentration (i.e., TiO₂), barrel temperature, residence time and holding time, were chosen at three different levels of each. Mechanical properties, such as yield strength, Young’s modulus and elongation, were selected as the performance targets. Nine experimental runs were carried out based on the Taguchi L₉ orthogonal array, and the data were processed according to the grey relational steps. The optimal process parameters were found based on the average responses of the grey relational grades, and the ideal operating conditions were found to be a filler concentration of 5 wt % TiO₂, a barrel temperature of 225 °C, a residence time of 30 min and a holding time of 20 s. Moreover, analysis of variance (ANOVA) has also been applied to identify the most significant factor, and the percentage of TiO₂ nanoparticles was found to have the most significant effect on the properties of the HDPE/TiO₂ nanocomposites fabricated through the injection molding process. Full article