Experimental Investigations on Dry Sliding Wear Behavior of Kevlar and Natural Fiber-Reinforced Hybrid Composites through an RSM–GRA Hybrid Approach

The present work aimed to investigate the dry sliding wear behaviors of hybrid polymer matrix composites made up of Kevlar, bamboo, palm, and Aloe vera as reinforcement materials of varying stacking sequences, along with epoxy as the matrix material. Three combinations of composite laminates with different stacking sequences such as AB, BC, and CA were fabricated by a vacuum-assisted compression molding process. The influence of composite laminates fabricated through various stacking sequences and dry sliding wear test variables such as load, sliding distance, and sliding velocity on the specific wear rate and co-efficient of friction were investigated. Experiments were designed and statistical validation was performed through response surface methodology-based D-optimal design and analysis of variance. The optimization was performed using grey relational analysis (GRA) to identify the optimal parameters to enhance the wear resistance of hybrid polymer composites under dry sliding conditions. The optimal parameters, such as composite combinations of CA, a load of 5 N, a sliding velocity of 3 m/s, and a sliding distance of 1500 m, were obtained. Furthermore, the morphologies of worn-out surfaces were investigated using SEM analysis

Intelligent Modeling and Multi-Response Optimization of AWJC on Fiber Intermetallic Laminates through a Hybrid ANFIS-Salp Swarm Algorithm

The attainment of intricate part profiles for composite laminates for end-use applications is one of the tedious tasks carried out through conventional machining processes. Therefore, the present work emphasized hybrid intelligent modeling and multi-response optimization of abrasive waterjet cutting (AWJC) of a novel fiber intermetallic laminate (FIL) fabricated through carbon/aramid fiber, reinforced with varying wt% of reduced graphene oxide (r-GO) filled epoxy resin and Nitinol shape memory alloy as the skin material. The AWJC experiments were performed by varying the wt% of r-GO (0, 1, and 2%), traverse speed (400, 500, and 600 mm/min), waterjet pressure (200, 250, and 300 MPa), and stand-off distance (2, 3, and 4 mm) as the input parameters, whereas kerf taper (Kt) and surface roughness (Ra) were considered as the quality responses. A hybrid approach of a parametric optimized adaptive neuro-fuzzy inference system (ANFIS) was adopted through three different metaheuristic algorithms such as particle swarm optimization, moth flame optimization, and dragonfly optimization. The prediction efficiency of the ANFIS network has been found to be significantly improved through the moth flame optimization algorithms in terms of minimized prediction errors, such as mean absolute percentage error and root mean square error. Further, multi-response optimization has been performed for optimized ANFIS response models through the salp swarm optimization (SSO) algorithm to identify the optimal AWJC parameters. The optimal set of parameters, such as 1.004 wt% of r-GO, 600 mm/min of traverse speed, 214 MPa of waterjet pressure, and 4 mm of stand-off distance, were obtained for improved quality characteristics. Moreover, the confirmation experiment results show that an average prediction error of 3.38% for Kt and 3.77% for Ra, respectively, were obtained for SSO, which demonstrates the prediction capability of the proposed optimization algorithm

Biogenic Preparation, Characterization, and Biomedical Applications of Chitosan Functionalized Iron Oxide Nanocomposite

Chitosan (CS) functionalization over nanomaterials has gained more attention in the biomedical field due to their biocompatibility, biodegradability, and enhanced properties. In the present study, CS functionalized iron (II) oxide nanocomposite (CS/FeO NC) was prepared using Sida acuta leaf extract by a facile and eco-friendly green chemistry route. Phyto-compounds of S. acuta leaf were used as a reductant to prepare CS/FeO NC. The existence of CS and FeO crystalline peaks in CS/FeO NC was confirmed by XRD. FE-SEM analysis revealed that the prepared CS/FeO NC were spherical with a 10–100 nm average size. FTIR analyzed the existence of CS and metal-oxygen bands in the prepared NC. The CS/FeO NC showed the potential bactericidal activity against E. coli, B. subtilis, and S. aureus pathogens. Further, CS/FeO NC also exhibited the dose-dependent anti-proliferative property against human lung cancer cells (A549). Thus, the obtained outcomes revealed that the prepared CS/FeO NC could be a promising candidate in the biomedical sector to inhibit the growth of bacterial pathogens and lung cancer cells

Enhancing the surface quality of FDM processed flapping-wing micro mechanism assembly through RSM-TOPSIS hybrid approach

Improving surface quality attributes is a critical task in the production of micro-sized near-net-shaped components for end-use applications using additive manufacturing techniques. In the present study, we investigated the effect of fused deposition modeling (FDM) process parameters such as layer thickness, part orientation, raster width and raster angle on the surface quality characteristics of as-fabricated test specimens in order to develop the assembly of a flapping wing micro mechanism. Through a Box–Behnken design, a suitable experimental strategy was developed, and test specimens were manufactured. The performance of the experiments was statistically assessed using multi-response analysis of variance (ANOVA). The microstructures of the test specimens produced with various processing parameters were examined using a scanning electron microscope to identify micro surface flaws under various processing conditions. Furthermore, the optimal FDM parameters for improved surface quality attributes such as Ra, Rz and Rq were obtained using a statistical optimization technique known as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).MOST補正完畢CH

Enhancing the Surface Quality of FDM Processed Flapping Wing Micro Mechanism Assembly through RSM–TOPSIS Hybrid Approach

Improving surface quality attributes is a critical task in the production of micro-sized near-net-shaped components for end-use applications using additive manufacturing techniques. In the present study, we investigated the effect of fused deposition modeling (FDM) process parameters such as layer thickness, part orientation, raster width and raster angle on the surface quality characteristics of as-fabricated test specimens in order to develop the assembly of a flapping wing micro mechanism. Through a Box–Behnken design, a suitable experimental strategy was developed, and test specimens were manufactured. The performance of the experiments was statistically assessed using multi-response analysis of variance (ANOVA). The microstructures of the test specimens produced with various processing parameters were examined using a scanning electron microscope to identify micro surface flaws under various processing conditions. Furthermore, the optimal FDM parameters for improved surface quality attributes such as Ra, Rz and Rq were obtained using a statistical optimization technique known as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)

Multi-Response Optimization of Abrasive Waterjet Cutting on r-GO-Reinforced Fibre Intermetallic Laminates through Moth–Flame Optimization Algorithm

Laminated metal-composite structures, also known as fibre metal laminates (FMLs), have emerged as prominent engineering materials in various industries, particularly in the domains of aircraft and automobile manufacturing. These materials are sought after due to their enhanced impact and fatigue resistance capabilities. The machining of FMLs plays a crucial role in achieving near-net shapes for the purpose of joining and assembling components. Delamination is a prevalent issue encountered during the process of conventional machining, thus rendering FMLs are challenging materials to machine. This study aims to investigate the cutting process of novel fibre intermetallic laminates (FILs) using the abrasive water jet (AWJ) cutting technique. The FILs consists of carbon and aramid fibers that are adhesively bonded with a resin matrix filled with reduced graphene oxide (r-GO) nano fillers. Moreover, these laminates contain embedded Nitinol shape memory alloy sheets as the skin materials. Specifically, the study aims to investigate the impact of different factors, such as the addition of reduced graphene oxide (r-GO) in the laminates (ranging from 0 to 2 wt%), traverse speed (ranging from 400 to 600 mm/min), waterjet pressure (ranging from 200 to 300 MPa), and nozzle height (ranging from 2 to 4 mm), on the material removal rate (MRR), delamination factor (FD), and kerf deviation (KD). ANOVA was used in the statistical analysis to determine the most influential parameters and their effects on the selected responses. The optimal AWJC parameters are determined using a metaheuristic-based moth–flame optimization (MFO) algorithm in order to enhance cut quality. The efficacy of MFO is subsequently compared with similar well-established metaheuristics such as the genetic algorithm, particle swarm algorithm, dragonfly algorithm, and grey-wolf algorithm. MFO was found to outperform in terms of several performance indices, including rapid divergence, diversity, spacing, and hypervolume values, among the algorithms compared

Facile Synthesis and Characterization of Chitosan Functionalized Silver Nanoparticles for Antibacterial and Anti-Lung Cancer Applications

In the treatment of bacterial contamination, the problem of multi-drug resistance is becoming an increasingly pressing concern. Nanotechnology advancements enable the preparation of metal nanoparticles that can be assembled into complex systems to control bacterial and tumor cell growth. The current work investigates the green production of chitosan functionalized silver nanoparticles (CS/Ag NPs) using Sida acuta and their inhibition efficacy against bacterial pathogens and lung cancer cells (A549). Initially, a brown color formation confirmed the synthesis, and the chemical nature of the synthesized NPs were examined by UV-vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS), and transmission electron microscopy (TEM). FTIR demonstrated the occurrence of CS and S. acuta functional groups in the synthesized CS/Ag NPs. The electron microscopy study exhibited CS/Ag NPs with a spherical morphology and size ranges of 6–45 nm, while XRD analysis demonstrated the crystallinity of Ag NPs. Further, the bacterial inhibition property of CS/Ag NPs was examined against K. pneumoniae and S. aureus, which showed clear inhibition zones at different concentrations. In addition, the antibacterial properties were further confirmed by a fluorescent AO/EtBr staining technique. Furthermore, prepared CS/Ag NPs exhibited a potential anti-cancer character against a human lung cancer cell line (A549). In conclusion, our findings revealed that the produced CS/Ag NPs could be used as an excellent inhibitory material in industrial and clinical sectors