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The hybrid nanofluid flow due to a rotating disk has numerous applications, including centrifugal pumps, paper production, polymers dying, air filtration systems, automobile cooling and solar collectors. This study aims to investigate the convective heat transport and magnetohydrodynamics (MHD) hybrid nanofluid flow past a stretchable rotating surface using the Yamada-Ota and Xue models with the impacts of heat generation and thermal radiation.

The carbon nanotubes such as single-wall carbon nanotubes and multi-wall carbon nanotubes are suspended in a base fluid like water to make the hybrid nanofluid. The problem’s governing partial differential equations are transformed into a system of ordinary differential equations using similarity transformations. Then, the numerical solutions are found with a bvp4c function in MATLAB software. The impacts of pertinent parameters on the flow and temperature fields are depicted in tables and graphs.

Two solution branches are discovered in a certain range of unsteadiness parameters. The fluid temperature and the rate of heat transport are enhanced when the thermal radiation and heat generation effects are increased. The Yamada-Ota model has a higher temperature than the Xue model. Furthermore, it is observed that only the first solution remains stable when the stability analysis is implemented.

To the best of the authors’ knowledge, the results stated are original and new with the investigation of MHD hybrid nanofluid flow with convective heat transfer using the extended version of Yamada-Ota and Xue models. Moreover, the novelty of the present study is improved by taking the impacts of heat generation and thermal radiation.

This study aims to optimize heat transfer efficiency and minimize friction factor and entropy generation in hybrid nanofluid flows through porous media. By incorporating factors such as melting effect, buoyancy, viscous dissipation and no-slip velocity on a stretchable surface, the aim is to enhance overall performance. Additionally, sensitivity analysis using response surface methodology is used to evaluate the influence of key parameters on response functions.

After deriving suitable Lie-group transformations, the modeled equations are solved numerically using the “spectral local linearization method.” This approach is validated through rigorous numerical comparisons and error estimations, demonstrating strong alignment with prior studies.

The findings reveal that higher Darcy numbers and melting parameters are associated with decreased entropy (35.86% and 35.93%, respectively) and shear stress, increased heat transmission (16.4% and 30.41%, respectively) in hybrid nanofluids. Moreover, response surface methodology uses key factors, concerning the Nusselt number and shear stress as response variables in a quadratic model. Notably, the model exhibits exceptional accuracy with $R^2$ values of 99.99% for the Nusselt number and 100.00% for skin friction. Additionally, optimization results demonstrate a notable sensitivity to the key parameters.

Lubrication is a vital method to minimize friction and wear in the automobile sector, contributing significantly to energy efficiency, environmental conservation and carbon reduction. The incorporation of nickel and manganese zinc ferrites into SAE 20 W-40 motor oil lubricants, as defined by the Society of Automotive Engineers, significantly improves their performance, particularly in terms of tribological attributes.

This work stands out for its focus on applications such as hybrid electromagnetic fuel cells and nano-magnetic material processing. While these applications are gaining interest, there is still a research gap regarding the effects of melting on heat transfer in a NiZnFe_2O_4-MnZnFe_2O_4/20W40 motor oil hybrid nanofluid over a stretchable surface, necessitating a thorough investigation that includes both numerical simulations and statistical analysis.

The purpose of this study is to assess a novel method for creating tangible three-dimensional (3D) morphologies (scaled models) of neuronal reconstructions and to evaluate its cost-effectiveness, accessibility and applicability through a classroom survey. The study addresses the challenge of accurately representing intricate and diverse dendritic structures of neurons in scaled models for educational purposes.

The method involves converting neuronal reconstructions from the NeuromorphoVis repository into 3D-printable mold files. An operator prints these molds using a consumer-grade desktop 3D printer with water-soluble polyvinyl alcohol filament. The molds are then filled with casting materials like polyurethane or silicone rubber, before the mold is dissolved. We tested our method on various neuron morphologies, assessing the method’s effectiveness, labor, processing times and costs. Additionally, university biology students compared our 3D-printed neuron models with commercially produced counterparts through a survey, evaluating them based on their direct experience with both models.

An operator can produce a neuron morphology’s initial 3D replica in about an hour of labor, excluding a one- to three-day curing period, while subsequent copies require around 30 min each. Our method provides an affordable approach to crafting tangible 3D neuron representations, presenting a viable alternative to direct 3D printing with varied material options ensuring both flexibility and durability. The created models accurately replicate the fidelity and intricacy of original computer aided design (CAD) files, making them ideal for tactile use in neuroscience education.

The development of data processing and cost-effective casting method for this application is novel. Compared to a previous study, this method leverages lower-cost fused filament fabrication 3D printing to create accurate physical 3D representations of neurons. By using readily available materials and a consumer-grade 3D printer, the research addresses the high cost associated with alternative direct 3D printing techniques to produce such intricate and robust models. Furthermore, the paper demonstrates the practicality of these 3D neuron models for educational purposes, making a valuable contribution to the field of neuroscience education.

This study aims to enhance heat transfer efficiency while minimizing friction factor and entropy generation in the flow of Nickel zinc ferrite (NiZnFe₂O₄) nanoparticles suspended in multigrade 20W-40 motor oil (as specified by the Society of Automotive Engineers). The investigation focuses on the effects of the melting process, nonspherical particle shapes, thermal dispersion and viscous dissipation on the nanofluid flow.

The fundamental governing equations are transformed into a set of similarity equations using Lie group transformations. The resulting set of equations is numerically solved using the spectral local linearization method. Additionally, sensitivity analysis using response surface methodology (RSM) is conducted to evaluate the influence of key parameters on response function.

Higher dispersion reduces entropy production. Needle-shaped particles significantly enhance heat transfer by 27.65% with melting and reduce entropy generation by 45.32%. Increasing the Darcy number results in a reduction of friction by 16.06%, lower entropy by 31.72% and an increase in heat transfer by 17.26%. The Nusselt number is highly sensitive to thermal dispersion across melting and varying volume fraction parameters.

This study addresses a significant research gap by exploring the combined effects of melting, particle shapes and thermal dispersion on nanofluid flow, which has not been thoroughly investigated before. The focus on practical applications such as fuel cells, material processing, biomedicine and various cooling systems underscores its relevance to sectors such as nuclear reactors, tumor treatments and manufacturing. The incorporation of RSM for friction factor analysis introduces a unique dimension to the research, offering novel insights into optimizing nanofluid performance under diverse conditions.

Normal-weight obesity (NWO), characterized by normal body mass index (BMI) but excess body fat, is a potential contributor to chronic diseases. This study aims to assess the relationship between this phenomenon and some metabolic factors in a population of Iranian employees.

This cross-sectional study was conducted on Iranian employees from the baseline data of Employees Health Cohort Study, Shiraz, Iran. Anthropometric measures, including weight, height, waist circumference and percentage of body fat, were obtained from the cohort database. The participants were divided into three groups: healthy, normal-weight obese and overweight/obese. Metabolic variables including blood pressure, fasting blood sugar, lipid profile, liver function enzymes and metabolic syndrome were assessed in relation to the study groups.

A total of 985 participants aged 25–64 years were included. Males with NWO had significantly higher alanine aminotransferase (ALT) levels compared to the healthy group in the fully adjusted model. Also, high-density lipoprotein (HDL) was significantly lower among females with overweight/obesity than healthy group when adjusted for age and energy intake. Furthermore, after adjusting for age and energy intake, both genders in the overweight/obese group showed significantly elevated systolic and diastolic blood pressure, while this was not observed for the NWO group. Lastly, metabolic syndrome was more prevalent in NWO as well as overweight/obesity.

These findings further encourage identification of excess body fat, even in normal-weight individuals, to prevent chronic metabolic diseases. Special attention should be paid to subgroups with sedentary occupations, as they may be at increased risk for NWO-related health issues.

Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To track changes in mass deposition, the effect of particle thermophoresis is therefore seen in a mixed convective flow of Williamson hybrid nanofluids upon a stretching/shrinking sheet.

The PDEs are transformed into ordinary differential equations (ODEs) using the similarity technique and then the bvp4c solver is employed for the altered transformed equations. The main factors influencing the heat, mass and flow profiles are displayed graphically.

The findings imply that the larger effects of the thermophoretic parameter cause the mass transfer rate to drop for both solutions. In addition, the suggested hybrid nanoparticles significantly increase the heat transfer rate in both outcomes. Hybrid nanoparticles work well for producing the most energy possible. They are essential in causing the flow to accelerate at a high pace.

The consistent results of this analysis have the potential to boost the competence of thermal energy systems.

It has not yet been attempted to incorporate hybrid nanofluids and thermophoretic particle deposition impact across a vertical stretching/shrinking sheet subject to double-diffusive mixed convection flow in a Williamson model. The numerical method has been validated by comparing the generated numerical results with the published work.

This study aims to explore entropy evaluation in the bi-directional flow of Casson hybrid nanofluids within a stagnated domain, a topic of significant importance for optimizing thermal systems. The aim is to investigate the behavior of unsteady, magnetized and laminar flow using a parametric model based on the thermo-physical properties of alumina and copper nanoparticles.

The research uses boundary layer approximations and the Keller-box method to solve the derived ordinary differential equations, ensuring numerical accuracy through convergence and stability analysis. A comparison benchmark has been used to authenticate the accuracy of the numerical outcomes.

Results indicate that increasing the Casson fluid parameter (ranging from 0.1 to 1.0) reduces velocity, the Bejan number decreases with higher bidirectional flow parameter (ranging from 0.1 to 0.9) and the Nusselt number increases with higher nanoparticle concentrations (ranging from 1% to 4%).

This study has limitations, including the assumption of laminar flow and the neglect of possible turbulent effects, which could be significant in practical applications.

The findings offer insights for optimizing thermal management systems, particularly in industries where precise control of heat transfer is crucial. The Keller-box simulation method proves to be effective in accurately predicting the behavior of such complex systems, and the entropy evaluation aids in assessing thermodynamic irreversibilities, which can enhance the efficiency of engineering designs.

These findings provide valuable insights into the thermal management of hybrid nanofluid systems, marking a novel contribution to the field.

This investigation delves into the rationale behind the preferential applicability of the non-Newtonian nanofluid model over alternative frameworks, particularly those incorporating porous medium considerations. The study focuses on analyzing the mass and heat transfer characteristics inherent in the Williamson nanofluid’s non-Newtonian flow over a stretched sheet, accounting for influences such as chemical reactions, viscous dissipation, magnetic field and slip velocity. Emphasis is placed on scenarios where the properties of the Williamson nanofluid, including thermal conductivity and viscosity, exhibit temperature-dependent variations.

Following the use of the OHAM approach, an analytical resolution to the proposed issue is provided. The findings are elucidated through the construction of graphical representations, illustrating the impact of diverse physical parameters on temperature, velocity and concentration profiles.

Remarkably, it is discerned that the magnetic field, viscous dissipation phenomena and slip velocity assumption significantly influence the heat and mass transmission processes. Numerical and theoretical outcomes exhibit a noteworthy level of qualitative concurrence, underscoring the robustness and reliability of the non-Newtonian nanofluid model in capturing the intricacies of the studied phenomena.

Available studies show that no work on the Williamson model is conducted by considering viscous dissipation and the MHD effect past over an exponentially stretched porous sheet. This contribution fills this gap.

This paper aims to assess the efficiency of emulsified essential oils in glycerol as eco-friendly antimicrobial and plasticized agents added to the biopolymer of gelatin for lining historical oil paintings on canvases.

Cedar oil, cinnamon oil and their mixtures were emulsified in glycerol and incorporated into gelatin adhesive as green biocides and plasticizers. Physical, biological, chemical and mechanical tests were conducted on experimental mock-ups to assess the gelatin-based adhesive formulations for the reinforcement of canvas supports. Scanning electron microscope, colorimetric measurements, antimicrobial activity test, attenuated total reflection-Fourier transform infrared spectroscopy, tensile strength and elongation tests were carried out on the mock-ups before and after the artificial aging.

The formulations of gelatin-based adhesive with cinnamon and cinnamon-cedar mixture emulsified in glycerol proved their efficiency on the antimicrobial activity test, chemically delaying the decomposition of gelatin and accordingly providing compatible mechanical properties. Gelatin-based adhesive with emulsified cinnamon oil showed a slight yellowing that was quite improved with the mixture of the cinnamon-cedar-based adhesive formulation.

This study promotes a green approach to lining historical oil paintings by developing green formulations from bio-based origins that minimize the shrinkage and microbial infection of gelatin for lining paintings.

Inspired by the high-friction performance of the soft toe pads of tree frogs, this study aims to investigate the effect of elastic deformation on the lubrication properties of squeezing films inside soft tribocontacts with microstructured surface under wet conditions.

A one-dimensional hydrodynamic extrusion model was used to study the film lubrication characteristics of conformal contact. The lubrication characteristics of the extruded film, including load-carrying capacity, liquid flow and surface elastic deformation, were obtained through the simultaneously iterative solution of the fluid-governing and deformation equations.

The results show that the hydrodynamic pressure is approximating parabolically and symmetrically distributed in the contact area, and the peak value appears in the center of the extrusion surface. Elastic deformation increases the thickness of the liquid film, weakens the bearing capacity and homogenizes the liquid flow rate of inside soft friction contact. The magnitude of this effect greatly increases as the initial liquid film thickness decreases. Moreover, the elastic deformation directly affects the average film thickness of the extrusion contact. Narrow and shallow microchannels are found to result in a more prominent elastic deformation on the microstructured soft surface.

These results present a design for soft tribocontacts suitable for submerged or wet environments involving high friction, such as wiper blades, in situ flexible electrons and underwater robots.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0049/