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This study aims at evaluating the properties of cotton fabric after nanofinishing using zinc oxide and silicon dioxide nanoparticles along with dimethylol dihydroxyethylene urea (DMDHEU).

DMDHEU recipes was optimized by Box-Behnken Design before using it with nanoparticles. These nanoparticles were synthesized by sol gel technique and applied to the fabric by pad-dry-cure method. The treated samples were evaluated for functional properties such as self-cleaning, antibacterial and ultraviolet (UV) protection properties.

Due to the use of DMDHEU, crease recovery property was obtained. The results showed good antibacterial property against S-aureus (gram positive) bacteria and E-coli (gram negative). UV protection property of combined nano-finished samples showed good results, as they showed very low transmission of UV-irradiation when exposed to UV-rays compared to single nanoparticle finished samples. Self-cleaning property of finished cotton was found to be good even after five washing cycles.

In this study, nanofinishing of cotton fabric with zinc oxide and silicon dioxide nanoparticles along with DMDHEU was studied to achieve promising functional properties with long durability of nanofinishing not studied earlier.

The purpose of this paper is to investigate the entropy optimization in magnetohydrodynamic hybrid nanomaterials flows toward a stretchable surface. The energy expression is modeled subject to dissipation, heat generation/absorption and Joule heating. Here silicon dioxide (SiO₂) and molybdenum disulfide (MoS₂) as nanoparticles and propylene glycol (C₃H₈O₂) as base fluid, respectively. Furthermore, the authors discussed the comparative study of molybdenum disulfide and silicon dioxide diluted in propylene glycol. The total entropy optimization rate is computed through implementation of the second law of thermodynamics.

The nonlinear partial differential system is reduced to an ordinary one through implementation of transformation. Newton built-in shooting method is used for computational results for the given system. Influences of various flow variables on the temperature, Bejan number, velocity, concentration and entropy generation rate are examined graphically for both nanoparticles (SiO₂ and MoS₂). Gradients of velocity and temperature are computed numerically for various physical parameters. Also, take the comparison between the present and previously published results in tabulated form.

For higher estimation of ϕ both temperature and velocity are enhanced. Entropy optimization and Bejan number have the opposite outcome for viscosity parameter. Temperature and velocity have opposite behaviors for larger values of magnetic parameter. Molybdenum disulfide (MoS₂) is more efficient than silicon dioxide (SiO₂).

No such work is yet published in the literature.

This paper aims to study the fluid flow and heat transfer within the Casson nanofluid confined between disk and cone both rotating with distinct velocities. For a comprehensive investigation, two distinct nano-size particles, namely, silicon dioxide and silicon carbide, are submerged in ethanol taken as the base fluid.

This paper explores the disk and cone contraption mostly encountered for viscosity measurement in various industrial applications such as lubrication industry, hydraulic brakes, pharmaceutical industry, petroleum and gas industry and chemical industry.

It is worth mentioning here that the radially varying temperature profile at the disk surface is taken into the account. The effect of prominent emerging parameters on velocity fields and temperature distribution are studied graphically, while bar graphs are drawn to examine the physical quantities of industrial interest such as surface drag force and heat transfer rate at disk and cone.

To the best of the authors’ knowledge, no study in literature exists that discusses the thermal enhancement of nano-fluidic transport confined between disk and cone both rotating with distinct angular velocities with heat transfer.

The purpose of this study is to investigate the presence of silicon dioxide (SiO₂) nanoparticles in o-toluidine monomer as a reactant and ammonium persulfate as an oxidant to obtain the poly(o-toluidine) (POT)/SiO₂ nanocomposites by oxidative polymerization method.

Fourier transformation infrared spectroscopy, X-ray diffraction and field emission scanning electron microscopy were used to characterize the structural properties of the composite. POT/SiO₂ nanocomposites were mixed with acrylic resin through a solution mixing method and the composites were coated onto the surface of mild steel. Electrochemical measurements were used to determine the corrosion protection efficiency (P.E.%) of polymer composite coatings using 3.5% NaCl solution as corrosion environment.

The results obtained reveals that the POT/SiO₂/acrylic resin composite coatings have got higher corrosion P.E.% than that of POT/acrylic resin coatings.

The formation of uniformly passive layer in the POT/SiO₂ composite was used to enhance the P.E.% on mild steel surface. The POT/SiO₂/acrylic resin nanocomposites showed effective anticorrosive behavior on mild steel in 3.5% NaCl solution.

Optimisation of grinding processes involves enhancing the surface quality and reducing the cost of manufacturing through reduction of power consumptions. Recent research works have indicated the minimum quantity lubrication (MQL) system is used to achieve near dry machining of alloys and hard materials. This study aims to provide an experimental analysis of the grinding process during machining of aluminium alloy (Al6061-T6). MQL nanofluid was used as the lubricant for the grinding operations. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality was studied. Adaptive neuro-fuzzy inference system (ANFIS) prediction modelling was used to predict the specific normal force, specific tangential force and surface quality, the ANFIS models were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further study shows that both the specific grinding forces and surface roughness are inversely proportional to the nanofluid concentration. Also, the depth of cut and table feed rate were found to have a directly proportional relationship with both the grinding forces and surface roughness. Moreover, higher MQL air pressure was found to offer better delivery of the atomised nanofluid into the grinding region.

Grinding experiments were performed using MQL nanofluid as the lubricant. The lubricant was formed by suspending silicon dioxide nanoparticles in canola vegetable oil. The effect of input parameters (i.e. nanoparticle concentration, depth of cut, air pressure and feed rate) on the grinding forces and surface quality has been studied.

The grinding process parameters were optimised using Taguchi S/N ratio analysis, whereas the prediction of the response parameters was done using ANFIS modelling technique. The developed ANFIS models for predicting the specific normal force, specific tangential force and surface quality were found to have prediction accuracies of 97.4, 96.6 and 98.5 per cent, respectively. Further findings show that both the specific grinding forces and surface roughness are inversely proportional to the percentage of nanoparticle concentration in the lubricant. Also, the depth of cut and table feed rate were found to exhibit a direct proportional relationship with both the grinding forces and surface roughness, while high MQL air pressure was observed to offer more efficient delivery of the atomised nanofluid into the grinding region.

The work can applied into manufacturing industries to prevent unnecessary trials and material wastages.

The purpose of this study is to develop an artificial intelligent model for predicting the outcomes of MQL grinding of the aluminium alloy material using ANFIS modelling technique.

The article focuses on the magnetohydrodynamic (MHD) convective flow of MoS₂-SiO₂ /ethylene glycol (EG) hybrid nanofluid. The effectiveness of Hall current, periodically heating wall and shape factor of nanoparticles on the magnetized flow of hybrid nanocomposite molybdenum disulfide- silicon dioxide (MoS₂-SiO₂) suspended in ethylene glycol (EG) in a vertical rotating channel under the influence of strong magnetic dipole (Hall effect) and thermal radiation is assessed. One of the channel walls has an oscillatory temperature gradient. Four different shapes (i.e. brick, cylinder, platelet and blade) of nanoparticles disseminated in base fluid (EG) are considered for simulation of the flow.

The analytical solution of governing equations has been presented. Influences of emerging physical parameters on the velocity and temperature profiles, the shear stresses and the rate of heat transfer are pointed out and discussed via graphs and tables.

The analysis revealed that Hall parameter has suppressing behavior on the velocity profiles within the rotating channel. The impact of nanoparticle shape factor advances the temperature characteristics significantly in the rotating channel. Brick-shape nanoparticles put up relatively low-temperature distribution in the rotating channel. The Hall parameter reduces the amplitudes of the shear stresses at the channel wall. However, the radiation parameter enhances the amplitude of the rate of heat transfer at the channel wall.

The important technical advantage of hybrid composition of nanoparticles as a drug carrier is its stability, high thermal conductivity, high load carrying capacity, etc. The proposed model may be beneficial in biomedical engineering, automobile parts, mineral and cleaning oils manufacturing, rubber and plastic industries.

To the best of our knowledge, there is little or no report on the aspects of assessment of the effectiveness of Hall current and nanoparticle shape factor on an MHD flow and heat transfer of an electrically conducting MoS₂-SiO₂/EG ethylene glycol-based hybrid nanofluid confined in a vertical channel with periodically varying wall temperature subject to a rotating frame. The present work furnishes a robust benchmark for the dynamics of nanofluids.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.

The purpose of this paper, an experimental study, is to investigate the optimal machining parameters for turning of nickel-based superalloy Inconel 718 under eco-friendly nanofluid minimum quantity lubrication (NMQL) environment to minimize cutting tool flank wear (Vb) and machined surface roughness (Ra).

The central composite rotatable design approach under response surface methodology (RSM) is adopted to prepare a design of experiments plan for conducting turning experiments.

The optimum value of input turning parameters: cutting speed (A), feed rate (B) and depth of cut (C) is found as 79.88 m/min, 0.1 mm/rev and 0.2 mm, respectively, with optimal output response parameters: Vb = 138.633 µm and Ra = 0.462 µm at the desirability level of 0.766. Feed rate: B and cutting speed: A2 are the leading model variables affecting Vb, with a percentage contribution rate of 12.06% and 43.69%, respectively, while cutting speed: A and feed rate: B are the significant factors for Ra, having a percentage contribution of 38.25% and 18.03%, respectively. Results of validation experiments confirm that the error between RSM predicted and experimental observed values for Vb and Ra is 3.28% and 3.75%, respectively, which is less than 5%, thus validating that the formed RSM models have a high degree of conformity with the obtained experimental results.

The outcomes of this research can be used as a reference machining database for various metal cutting industries to establish eco-friendly NMQL practices during the turning of superalloy Inconel 718 to enhance cutting tool performance and machined surface integrity.

No study has been communicated till now on the turning of Inconel 718 under NMQL conditions using olive oil blended with multi-walled carbon nanotubes-based nanofluid.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0317/

Far infrared radiation (FIR) has been shown to have physiological effects when used as a treatment modality for certain medical conditions. Athletic apparel are currently commercially available that are constructed with fabrics that purportedly emit FIR. If apparel with this technology are capable of inducing positive physiological effects, then there may be important implications when worn by an athlete during exercise. The purpose of this study is to examine whether FIR apparel has an effect on oxygen consumption during exercise at submaximal intensities. Twelve male cyclists have completed submaximal incremental cycling tests. Each subject is tested on 4 separate days, twice while wearing a full body Control garment, and twice while wearing a similar garment made out of FIR fabric. Throughout each cycling test, the volume of oxygen uptake is monitored by using a breathing mask and metabolic analysis cart. At lower cycling intensities, the subjects consume statistically significantly less oxygen when wearing the FIR apparel compared to the Control garment, despite performing the same amount of mechanical work. Additional research is required to determine the implication of this effect for a training or competing athlete; however, the results indicate that this apparel technology does elicit a physiological effect.