The focus of this study is on the development and performance evaluation of sustainable Curauá/Areca hybrid fibre composites reinforced with epoxy and treated with alkali (NaOH) and nano-SiO₂. This work aims to enhance the mechanical and tribological efficiency of natural fibre composites through surface modification and nanoparticle incorporation, addressing the need for eco-friendly alternatives to synthetic composites. Optimization of the Curauá:Areca fibre ratio, NaOH treatment duration, nano-SiO₂ content, and applied load (for wear) was carried out using the Response Surface Methodology (RSM) for the mechanical and tribological processing parameters. Tensile and flexural strengths improved with higher Curauá fraction, while Areca-rich laminates displayed greater impact toughness. NaOH treatment increased fibre-matrix adhesion and was responsible for higher strength, less fibre pull-out, and reduced matrix porosity. Performance improved notably with nano-SiO₂ at intermediate loadings (~ 3-4 wt%), but decreased at higher loadings due to agglomeration. Tribological properties were best at 67% Curauá, 24 h NaOH treatment, ~ 3.75 wt% SiO₂, and 10 N load, with reduced wear rate and coefficient of friction attributed to the improved Curauá content, NaOH treatment, and optimum nano-SiO₂ dispersion. SEM analysis confirmed the results, illustrating enhanced fibre-matrix bonding, reduced fibre pull-out, and smoother wear surfaces in the treated, Curauá-rich composites. Under optimized conditions, RSM predictions were consistent with the experimental findings: tensile strength of 61.2 MPa, flexural strength of 76.3 MPa, impact strength of 20.2 kJ/m², minimum wear rate of 0.0011 mm3/Nm, and a coefficient of friction of 0.27. The novelty of this study lies in integrating alkali treatment and nano-SiO₂ reinforcement in Curauá/Areca hybrid composites to achieve superior strength and wear resistance, demonstrating a sustainable route for high-performing bio-composites.

This study aims to explore hybrid aluminium alloy composites specifically for automotive and aerospace applications. Here, we design and fabricate AA6061-Marble dust particulate (0 to 6 @ 1.5 wt.

Selecting the most suitable high-performance polymer for a printed circuit board (PCB) substrate with low coefficient of thermal expansion (CTE), superior thermal stability, dielectric properties, and cost-effectiveness is challenging. In the present work, a hybrid multi-criteria decision-making technique was used to select optimal PCB substrate materials for modern electronic systems. Polyether ketone (PEK) reinforced with fly ash particles (PEK/FA) composites were prepared and evaluated for their physical, electrical, thermal, and mechanical properties. In addition to prepared PEK-FA composites, other high-performance polymer composites reported in the literature and conventional material (FR 4) were evaluated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to rank the alternative materials. Seven decision-making criteria, such as coefficient of thermal expansion, thermal conductivity, dielectric constant, dissipation factors, thermal degradation temperature, density, hardness, and cost, were considered for the study. The relative weights of criteria were calculated using the Criteria Importance Through Inter-Criteria Correlation (CRITIC) method. The results indicated that cost (23%) and electrical properties (18%) are the most influential criteria, followed by thermal properties and density. The TOPSIS method suggests that the PEK/FA composite reinforced with 30 wt.% FA is the most suitable material, with a performance score of 0.811, while the PEEK/AlN composite is the least suitable, with a performance score of 0.401, for modern PCB applications. The sensitivity analysis was conducted to assess the consistency of the ranking order. It is observed that the ranking order of materials is quite similar, especially among the top three in each case.

High-performance carbonaceous nanofiller (MWCNT) reinforced epoxy nanocomposites at different compositions were synthesized using the ultrasonication dual mixing method. The static and dynamic mechanical properties of the nanocomposites were examined. At 0.8 wt.% of nanofiller, the epoxy nanocomposite greatly improved in tensile strength by about 22.1% and Young's modulus by about 18.5%. The dynamic mechanical analysis showed a significant improvement in the storage modulus of about 19.1% and glass transition temperature of about 15.1% of the epoxy nanocomposite. This improvement may be attributed to the formation of an effective interface between the epoxy and MWCNT. The static and dynamic mechanical properties of the epoxy matrix were significantly improved as a result of the homogenous dispersion of carbonaceous filler in the epoxy matrix.

Nitinol reinforcement in aluminium matrix composites enhances strength through stress-induced phase transformation and enables self-healing. This enhanced durability makes it ideal for structural, automotive, aerospace, naval, and defense applications. This study experimentally and theoretically investigates Nitinol fiber-reinforced Al5083 MMC, fabricated using a rotating mold vacuum furnace. The influence of Nitinol wire size and weight fraction on the composite’s performance was investigated. A significant improvement was observed in the mechanical and thermal behaviour of the composite. Yield strength increased from 232 to 306 MPa, while ultimate tensile strength rose from 315 to 395 MPa. The elastic modulus increased from 72 to 96 GPa, whereas percentage elongation decreased from 21.63 to 11.54

This research study investigates physical, mechanical, and sliding wear characteristics of SiC (0–15 wt.

This research work reports on the mechanical and sliding wear performance analysis of vacuum-cast AA7075-Co (0–2 wt

In this investigation, aluminum alloy (AA7075) composites reinforced with titanium (Ti) particulates (0–2.0 wt.

In most of the manufacturing industries, the selection of optimal material among the finite available alternatives becomes more difficult with the more required performance criteria to satisfy certain objectives. In such scenarios, Multi-Criteria-Decision-Making (MCDM) techniques, such as hybrid AHP (Analytical hierarchy process) - TOPSIS (Technique for Order Preferences by Similarity to Ideal Solution) and others assist in quantitative decision-making by accounting for qualitative human judgments. The present work illustrates the application of a hybrid AHP-TOPSIS technique to the ranking of alloy composites. The properties defining data such as physical, mechanical, thermal, thermo-mechanical, etc. are weighted using the AHP technique; thereafter, relative weights are used to rank the alloy composite compositions by the TOPSIS method. The compositions comprise the AA2024 alloy as the matrix phase and the reinforcing phase consists of silicon carbide, silicon nitride and graphite particulates. The ranking analysis orders are consistent with subjective analysis. Dans la plupart des industries manufacturieres, la selection du materiau optimal parmi les choix disponibles limites devient plus difficile avec l'augmentation du nombre de criteres de performance requis pour satisfaire certains objectifs. Dans de tels scenarios, les techniques de prise de decision multicriteres (MCDM) telles que l'hybride AHP (processus de hierarchie analytique) - TOPSIS (technique de preference de commande par similarite avec la solution ideale) et d'autres aident a la prise de decision quantitative en tenant compte des jugements humains qualitatifs. Le travail courant illustre l'application d'une technique hybride AHP - TOPSIS au classement d'alliages composites. Les proprietes definissant les donnees telles que physiques, mecaniques, thermiques, thermomecaniques, etc. sont ponderees a l'aide de la technique AHP, par la suite, les poids relatifs sont utilises pour classer les compositions composites de l'alliage avec la methode TOPSIS. Les compositions comprennent l'alliage AA2024 comme phase de matrice et une phase de renforcement constituee de particules de carbure de silicium, de nitrure de silicium et de graphite. Les ordres d'analyse du classement s'averent coherents avec l'analyse subjective.

This investigation assesses the mechanical characterization and dry sliding wear performance of ZA-27-SiC-Gr alloy composites. The novelty lies in (i) design of ZA27-SiC (0, 1, 3, 5 wt%)-Gr (0, 1, 3, 5 wt%) alloy composite formulations; (ii) fabrication of ZA-27-SiC-Gr alloy composites using high vacuum casting process following industrial standard; (iii) according to ASTM standards, the specimen of each alloy composite was evaluated for its physical, mechanical, and dry sliding wear behavior using Multi-Specimen Dry Sliding Wear Tribometer; (iv) sliding wear parameter optimization analysis was carried out using Taguchi methodology; and (v) worn surface micrographs were examined for comprehending the wear mechanisms in charge of the wear of such alloy composites. The 5 wt% reinforcement exhibits improved overall physical and mechanical characteristics as well as sliding wear performance. The results of the AHP-TOPSIS study were found to be consistent with the composition ranking based on objective analysis. Thus, decision-making tools like AHP-TOPSIS could help material engineers choose materials in challenging situations.

This research investigates the physical, mechanical, thermal, thermomechanical and dry sliding wear performance of marble dust particulates (0–20 wt.% @ step of 5%) and lapinus fiber (10 wt.% constant) reinforced polyamide 66 polymer composites, resulting in five hybrid polymer composite namely PLM-0, PLM-5, PLM-10, PLM-15 and PLM-20, respectively. A twin screw extruder and injection molding machine were used for the fabrication. Taguchi's method and ANOVA tools are used to optimize and determine the significant order of the input parameters for the sliding wear process, followed by surface morphology investigations. Finally, the hybrid AHP-R ranking method was applied to rank the compositions on their merits. It is observed that PLM-10 hybrid polymer composites have shown relative overall optimized performance. It shows the lowest density of 1.21 g/cc, voids content of 6.47%, water absorption of 4.51% and a specific wear rate of 1.03 × 10 −3 mm 3 /Nm. In comparison, it shows the highest tensile strength of 112.64 MPa, flexural strength of 150.40 MPa, Rockwell hardness of 60.40 HRM, fracture toughness of 4.27 MPa√m, impact strength of 1.96 J, thermal conductivity of 0.98 W/mK and storage modulus of 1824.29 MPa. Finally, these subjective findings were found to be in tune with the findings of the hybrid AHP-R method.

This research work investigates the physical, mechanical, thermal, thermo-mechanical, and dry sliding wear characteristics of hybrid flyash particulates (F-class; 0 – 20 wt.% at the step of 5%)–basalt fibres (chopped; fixed 10 wt.%) reinforced polyamide 66 polymer composites fabricated using the twin screw extruder and injection moulding machine. Taguchi's design of experiment optimization approach is used for parameter optimization of the dry sliding wear process, followed by analysis of variance analysis. Further, the hybrid AHP-R method is used for ranking optimization based on the performance metrics. It is observed that the composition having 15 wt.% flyash particulates optimizes overall performance metrics, hence recommended for industrial parts fabrications. It has an experimental density of 1.23 g/cc, voids content of 5.93%, water absorption of 4.21%, tensile strength of 110.73 MPa, flexural strength of 146.72 MPa, Rockwell hardness of 62.44 HRM, fracture toughness of 4.17 MPa√m, impact strength of 2.06 J, the thermal conductivity of 1.24 W/mK, and specific wear rate of 7.55 × 10 −4 mm 3 /Nm. The overall subjective ranking of the hybrid polymer composites attunes with the objective ranking by the hybrid AHP-R method.

This research investigates physical, mechanical, and sliding wear assessment of chromium (0–2 wt

In this research work, hybrid polyamide 66–basalt fiber (10 wt%)–marble dust particulates (0–20 wt% with a variation of 5%) polymeric composites were designed and prepared through the injection molding method. Each composition sample was analyzed for its physical, mechanical, and thermal behavior. The Taguchi methodology was adopted to design experimental runs of dry sliding wear and for input operating parameter optimization, along with analysis of variance. Using a scanning electron microscope, worn-out surface micrograph examinations were carried out to comprehend wear mechanisms across the surface. Furthermore, a decision-making tool such as a hybrid Analytic Hierarchy Process – R method (hybrid AHP-R method) was applied to determine the ranking of the composites based on performance measures. The composition having polyamide 66 supplemented with 15 wt% marble dust particulate and 10 wt% basalt fiber tends to optimize overall performance measures. It shows voids content of 5.80%, water absorption of 2.54%, tensile strength of 117 MPa, flexural strength of 154 MPa, impact strength of 2.8 J, Rockwell hardness of 64 HRM, thermal conductivity of 1.11 W/mK, fracture toughness of 4.7 MPa√m, and specific wear rate of 7.05 × 10 −4 mm 3 /Nm, respectively. Thus, it optimizes overall performance measures along with steady-state dry sliding wear behavior, which is in tune with the ranking results obtained by the hybrid AHP-R method.

This research work examines the physical, mechanical, thermal, thermo-mechanical, and dry sliding wear performance of hybrid waste flyash particulates (F-class; 0-20 wt% @ step of 5%) – Lapinus fibres (fixed 10 wt%) reinforced Polyamide 66 polymer composites fabricated using the twin screw extruder and injection moulding machine. This follows worn surface morphology to understand the prevailing wear mechanisms responsible for surface damage during sliding. Optimization of control parameters and identification of their order of significance in the dry sliding wear process is performed using Taguchi’s design of experiments and analysis of variance (ANOVA). Further, ranking optimization of the hybrid composite specimens based on their performance metrics is analysed using the hybrid AHP-R method. It has been observed that the hybrid composite specimens having 10 wt% flyash particulates optimize the overall performance metrics; therefore, it may be recommended to fabricate parts or components for industrial usage. It tends to have an experimental density of 1.18 g/cc, voids content of 7.11%, water absorption of 3.87%, tensile strength of 105.95 MPa, flexural strength of 144.86 MPa, Rockwell hardness of 58.12 HRM, fracture toughness of 4.11 MPa√m, Impact strength of 1.86 J, thermal conductivity of 1.08 W/mK, and specific wear rate of 1.12 × 10 −3 mm 3 /Nm. This observation was attuned to the ranking analysis using the hybrid AHP-R method.

In this chapter, the sliding wearSliding wear and mechanicalMechanical performancePerformance of Gr -ZA-27 alloyZA-27 alloy compositesAlloy composites are investigated following ASTM standards. Taguchi methodologyTaguchi methodology is used in designing sliding wearSliding wear experiments, and the same methodology is used for parametric optimizationOptimization. In order to comprehend the associated wear mechanismsWear mechanisms responsible for surface damageSurface damage, surface micrograph studies employing scanning electron microscopy (SEMScanning electron microscopy (SEM)) are conducted. Furthermore, the rank of designed compositions is evaluated using Preference Selection Index (PSIPreference Selection Index (PSI)), and decision-making technique. The physicalPhysical and mechanicalMechanical characteristicsCharacteristics of alloy compositesAlloy composites with reinforcementReinforcement are found to be improved, including voidVoid content (1.33–2.50), hardnessHardness (107–171 HV), compressive strengthCompressive strength (406–496 MPa), flexural strengthFlexural strength (300–490 MPa), tensile strengthTensile strength (290–428 MPa), impact strengthImpact strength (22.76–64 J), and sliding wear performanceSliding wear performance. It is found that the AGr-6 alloy compositeAGr-6 alloy composite showed to optimize the overall physicalPhysical, mechanicalMechanical, and sliding wear performanceSliding wear performance. The evaluation of performancePerformance data using the PSIPreference Selection Index (PSI) and decision-making tool reveals that the order of material composition that optimizes the required performancePerformance is AGr-6 > AGr-4 > AGr-2 > AGr-0. As both decisions are attuned, decision-making technologies like PSIPreference Selection Index (PSI) can be applied to these challenges of material selection.