Nanofluid Heat Research Articles

The lie group analysis method for heat transfer in steady boundary layer flow field of nanofluid

In order to reveal the mechanism of the abnormal movement (Brownian motion enhances thermal scattering) of nanoparticles on the fluid enhanced heat transfer, the two-phase model was used to study the abnormal convection and diffusion of viscous nanofluids in the flat boundary layer of porous medium. Firstly, for the two-dimensional steady boundary layer stagnation point flow of incompressible Newtonian-nanofluids, the nonlinear governing equations of the flow field and temperature field of nanofluids are established from the Oberbeck-Boussinesq approximate equations. Secondly, the modern Lie group analysis method is introduced, we give the Lie symmetry determining equation of the flow field partial differential equations and the characteristics of the solutions. Further, using the relationship between the Lie symmetries and the conserved quantities, the conservation vector form of the flow field and the group invariant solution are derived in detail, and the reduced order model of the nanofluid flat boundary layer is obtained. Finally, the correctness of the analytical results obtained by the Lie group method was verified for different values of the flow parameter Prandtl. Research has shown that the Lie group method can be used to analytically solve the velocity and temperature distribution functions of abnormal motion of nanoparticles. The fluid temperature increases with the increase of the volume fraction parameter of nanoparticles, but decreases with the increase of the Prandtl value of the base fluid, and decreases with the increase of the plate stretching speed. The Lie group analysis method in this paper provides reference value for numerical simulation solutions of various heat and mass transfer in nanofluids.

Heat and Mass Transfer of Boundary Layer Jeffrey Ternary Hybrid Nanofluid Flow Over Porous Wedge With Surface‐Catalysed Chemical Reactions: An ANFIS Model

The current study employs machine learning (ML) techniques to investigate the heat and mass transport of Jeffrey ternary hybrid nanofluid (THNF). Various influential factors, including magnetic field, thermal radiation, viscous dissipation, activation energy, thermophoresis, Brownian motion and surface‐catalysed chemical reactions, are considered in the analysis. The porous moving wedge supports and influences the flow pattern. For thermal enhancement, three different nanoparticles, namely, Ag (silver), CuO (copper oxide) and SWCNT (single − walled carbon nanotubes), diluted in the regular fluid (blood). Initially, the mathematically modelled partial differential equations (PDEs) are solved numerically by the help of the shooting method. The suitable nondimensional similarity transformations are implied to convert the dimensional PDEs to nondimensional ordinary differential equations (ODEs). The reduced dimensionless nonlinear coupled ODEs are solved using ode‐45 in MATLAB. The impact of φAg, φCuO, φSWCNT in Cfx, Nux, Shx, is displayed in cone plots. It is found that, on increasing φAg, φCuO, φSWCNT, the heat transfer and mass transfer rate gets enhanced in THNF than the hybrid nanofluid (HNF) and nanofluid (NF). The influence of nondimensional parameters over f″(0), θ′(0), ϕ′(0), G′(0) and H′(0) is displayed in 3D contour plots for THNF and HNF. The radiation parameter (R), Brownian motion parameter (Nb), thermophoresis parameter (Nt) and volume fraction parameters φAg, φCuO, φSWCNT boost the energy transfer rate. Finally, the obtained numerical results are split into training and validation datasets that are used in designing the adaptive neuro‐fuzzy inference system (ANFIS) ML model. Five different ANFIS models are developed with the help of nondimensional parameters affecting f″(0), θ′(0), ϕ′(0), G′(0) and H′(0) to predict the physical quantities of dragging force (Cfx), energy transfer rate (Nux), the rate of mass transport (Shx) and mass fluxes for chemical species and , respectively. The training and checking errors attained the convergence less than 2 × 10−4 and 0.2, respectively, for all the five factors. The present ANFIS models have good balance between fitting the training data and generalising to new data, which can make accurate predictions irrespective of variations. The numerical and predicted ANFIS f″(0), θ′(0), ϕ′(0), G′(0) and H′(0) for training data, checking data and results are demonstrated in regression plots. From regression plots, we can observe that the Pearson correlation coefficient attains the positive correlation with R value closer to one. Hence, the developed ANFIS model shows the minimal error in predictions with high degree of accuracy of forecast in THNF flow.

Numerical simulation of the oscillating thin plate impact on nanofluids flow in channel

The present numerical study aims to present the effect of a titled oscillating thin plate with different inclination angles on the Al2O3-water nanofluid flow and heat transfer performance. The subsequent work establishes methods for forming fluid-structure interactions by the impact of Al2O3-water nanofluid at 0.1-1.0 vol. % volume fraction upon the thin plate using COMSOL Multiphysics 5.4. The turbulent model is solved using the (k-?) model, and the flow assembly around the thin plate obstacle has been confirmed at the Reynolds number of Re=4?104. It exemplifies how Nanofluid flow interaction can distort structures. The turbulent, two-dimensional, stationary, and incompressible flow around an oscillating thin plate with inclined angles with upstream and downstream mounted inside a horizontal channel was studied. The numerical study includes an investigation of the effect of five inclination angles of the thin plate (30, 60, 90, 120, and 150?) on the pressure, velocity, and temperature contours of the Al2O3-water nanofluid. Also, the study presented the drag profile and left a force on the thin plate caused by the fluid flow. The results showed that a titled oscillating thin plate inside the flow direction increases pressure drop, von Mises deformation stress, x-displacement and drag force fields, and the Nusselt number. Where the pressure increased from 2.61?103 to 6.21?103 pa, the von Mises stress increased from 4.43?106 to 1.78?107 N/m, and the X-displacement increased from 1.6 to 5.5 mm when increasing the plate angle from 30 to 90?.

Numerical analysis of mixed convection and Thomson-Troian slip effects on ternary nanofluid flow and heat transfer over a stretching sheet with porous media: Darcy-Forchheimer model

The present study unveils research that examines the laminar motion of water-infused nanofluid comprised of nanoparticles of TiO2 (titanium dioxide), Ag (silver), and Cu (copper) over a stretching sheet. The flow undergoes a novel slip condition based on Thomson and Troian to model complex fluid behavior near solid walls and incorporate the Darcy-Forchheimer model to comprehensively analyze the influence of a porous medium on flow behavior. Moreover, a heat source/sink and radiation are included to ensure the outcome of the energy equation will resemble most actual-world applications. Partial differential equations (PDEs) of higher order, originally used to describe the system are then reformulated into higher-order non-linear ordinary differential equations (ODEs) by taking symmetry variables that are chosen thoughtfully. The resulting boundary layer equations are then turned into a set of ODEs by implementing relevant similarity transformations, which can be solved using the M ATLAB function bvp4c. Through graphs, the variations in the velocity, Nusselt number, temperature, and skin friction coefficient were displayed. The outcome showed that the incorporation of silver nanoparticles (0.01–0.03) enhanced the skin friction coefficient by ≈ 1.68 % and the Nusselt number reduced up to ≈ 5 %. The Forchheimer number also reported a 6.5% enhancement and 1.5% reduction in the skin friction coefficient and the Nusselt number, respectively. The velocity slip parameter γ1 correlates with an upswing in temperature and skin friction coefficient for the ternary nanofluid while observing a decline in the velocity and Nusselt number.

INFLUENCE OF LORENTZ FORCES ON FORCED CONVECTION OF NANOFLUID IN A POROUS ENCLOSURE

The evaluation of the nanofluid heat transfer inside the enclosure is done via a theoretical approach. This study illustrates the change of Nusselt number of nanofluid inside the enclosure with porous media in the existence of a homogeny magnetic field. The change of significant factors of the magnetic field, Rayleigh number, and nanofluid characteristics (m) on thermal characteristics has been fully investigated. Obtained data indicate that increasing the Rayleigh number has changed the impacts of the magnetic field on the heat transfer and nanofluid streamline. Moreover, the heat transfer is improved by the increasing of Ra and m factors at constant Ha = 7.5. Heat transfer enhancement is achieved at a specific m factor by increasing Ra and decreasing the Hartmann number.

Numeričko ispitivanje prenosa toplote prirodnom konvekcijom korišćenjem nanofluida TiO₂/Al₂O₃-voda

Recently, nanofluids have been used as an alternative in several industries to improve the heat transfer process. This paper focuses on the numerical modeling of the performance of the natural convection process through TiO₂/Al₂O₃-water nanofluids in a square cavity containing a heated block. The lattice Boltzmann method is used in this study to present the nanofluid heat transfer enhancement. Results are presented in terms of streamlines, isothermal contours, and Nusselt number profiles. The findings demonstrate that by raising the Rayleigh number and solid nanoparticle concentration, the average Nusselt number increases, and they reveal that the heated block enormously affects the flow structure and heat transfer. It is also demonstrated that the type of nanoparticles significantly impacts the natural convection heat transfer.

Comparative analysis of CFD and ANFIS for predicting heat transfer enhancement in water-Fe2O3 nanofluids across various flow regions

Models for enhancement of heat transfer in nanofluids made wide use of adaptive neural fuzzy inference system (ANFIS) and the multi-phase mixture model in recent years. These models originate from two separate but complementary branches of engineering: computational mechanics and machine intelligence. Not only have prior studies used only a small subset of nanofluid and flow parameters in their analyses, but no one has ever compared the two methods to determine which one is more applicable to certain flow regimes to forecast how much heat transfer development nanofluids will exhibit. The purpose of this study was to compare the accuracy of two methods ? CFD and ANFIS in predicting the heat transfer improvement of water-Fe2O3 nanofluid for variety of nanofluid formations and flow characteristics, and recommend the method that would be most useful in predicting this enhancement for each flow regime. While ANFIS consistently outperforms the mixture models in prediction of nanofluid heat transfer enhancement, the latter can sometimes produce results that differ greatly from experimental correlation; however, for nanofluid configurations, the mixture model?s predictions can be dependable (with 1% error).

Innovative simulation of Al2O3 nanofluid heat transfer using advanced machine learning methods

In both turbulent and laminar pipe flows, we were able to accurately forecast the beginning range of the convective thermal transferring coefficients of Al2O3 magnetized nanofluids using machine learning approaches. The simulations utilized two machine learning techniques: radial basis function-backpropagation (RB) and multiple linear regression analysis. First, we used multiple linear regression analysis to fit the polynomial equation. Afterwards, grid search cross-validation was employed to determine the optimal RB model with six hidden layer neurons. To evaluate the RB model, we compared numerical patterns of the parameters used to measure accuracy. The regression coefficient and mean square error were the most commonly utilized parameters in Reynolds number mass percentage simulations, R2. In the case of a laminar flow, these numbers were found to be 0.99994 and 0.34, respectively. Additionally, the results for laminar flow conditions using Reynolds number-magnetic field strength simplification were ideal, with an mean square error of 3.85 and an R2 value of 0.99993. By comparing the predicted values with the experimental results visually using 3-D smoothed surface plots, we were able to further prove that the model was valid and accurate. These revolutionary findings could spark new developments and encourage substantial improvements in nanotechnology and machine intelligence. These findings are an important asset for driving future research and development, which in turn makes significant contributions to the ever-expanding frontiers of these innovative fields.

Nanofluid Heat Transfer in Irregular 3D Surfaces under Magnetohydrodynamics and Multi-Slip Effects

Nanofluid Heat Transfer in Irregular 3D Surfaces under Magnetohydrodynamics and Multi-Slip Effects

Heat and Mass Transfer Analysis of an unsteady Non-Newtonian Magnetohydrodynamic Fluid Flow (Semi-Analytical Solution)

In the presence of a time-dependent chemical reaction, this work investigates unsteady squeezing Casson nanofluid flow and heat transfer between two parallel plates under the influence of a uniform magnetic field. Considering the effects of viscosity dissipation, heat generation from friction resulting from flow shear, Brownian motion, Joule heating, and thermodiffusion. The problem's nonlinear differential equations are solved using the Runge–Kutta (RK-4) technique and the Homotopy Perturbation technique. The excellent accuracy of the results is evident since they have been compared with other results from earlier research. In the form of graphs and tables, flow behavior under the many physical factors that are modified is also covered and well described. This work has shown that, by normalizing flow behavior, magnetic fields may be utilized to manage a variety of flows. Additionally, it is demonstrated that in every situation, the effects of positive and negative squeeze numbers on heat and mass transfer flow are opposite. Moreover, the thermophoresis parameter decreases as the concentration field increases. However, when the Brownian motion parameter is increased, the concentration profile gets better. Additionally, several other significant factors were examined. The results of this study can facilitate quicker and easier research and assist engineers.

ANSYS Simulation of Enhanced Heat Transfer in Compact Pipes Using Al2O3-Water Nanofluids

Al2O3-Water nanofluids have become popular for their significantly higher heat transfer rates, which are related to their increased thermal conductivity. These fluids are particularly useful in tiny pipelines, especially in situations where effective thermal control is required. Because of this, they are particularly beneficial to sectors like aerospace and automotive, where the need for lightweight and compact heat exchanger designs is crucial. This research investigates several input factors, such as temperature and velocity, using ANSYS Fluent. The investigation's initial temperature was 290 K, and the pipe's entry velocity was 3.78×10-1 m/s. At 2.98×102 K, the exit temperature stabilized. However, a clear inverse link between the temperature at the pipe's output side and the velocity at its entrance side was found. This unique development served as the main focus of our investigation on how to optimize heat flow and thermal conductivity inside the pipe. We used a two-phase approach, incorporating the nanofluid phases phi-0 and phi-4, to increase our comprehension. This methodological decision departs from traditional research, which frequently uses simulations in a single phase. Our new method was inspired by the necessity for a more thorough investigation. The results of this study demonstrate the effectiveness of the two-phase method, showing a significant rise in heat flow and thermal conductivity when compared to traditional one-phase simulations used in earlier research. This emphasizes how our approach was original and significant, bringing fresh perspectives to the field of nanofluid heat transfer research.

Review on nanofluid preparation, stability analysis, and heat enhancement by nanofluids in pipe with passive elements

Heat enhancement applications such as heat exchangers, heating, ventilation, and air-conditioning systems, nuclear and chemical plants, etc., help to increase the thermal rating and performance of the system in addition to decreasing the cost, and size of the system. The heat exchanger design is very complex compared to other designing procedures, which requires proper heat transfer value and consideration of pressure drop, performance of the system, reliability, and durability of the system. The major drawback of the conventional fluid is its low thermal conductivity, which creates a negative impact on heat transfer, the nanofluids need to overcome this limitation. This paper reviews the preparation of nanofluid, stability analysis of nanoparticles, typical nanoparticles, and base fluids in heat transfer augmentation. Passive element heat enhancement techniques like twisted tapes showed positive results in laminar flow compared to turbulent flow, and ribs on the geometry, conical nozzles, and rings are better for turbulent flows than laminar flows. This article highlighted the main gaps and challenges for future research.

Heat Transfer Enhancement of Convective Casson Nanofluid Flow by CNTs over Exponentially Accelerated Plate

Carbon nanotubes (CNTs) nanofluids are gaining increased popularity among researchers due to their outstanding thermal properties, leading to numerous promising industrial applications. Analytical solutions discovered in the study of CNTs nanofluids, combined with a Casson-type fluid model, are extremely limited. Therefore, a study on the heat transfer analysis of an unsteady and incompressible Casson carbon nanofluid flow is conducted. Human blood-based single-walled carbon nanotubes (SWCNTs) and human blood-based multi-walled carbon nanotubes (MWCNTs) are considered as nanofluids that move beyond an exponentially accelerated vertical plate. A set of dimensional momentum and energy equations, along with their initial and exponentially accelerated boundary conditions, is employed to represent the problem. The transformation of these equations to the dimensionless expression is achieved by using suitable dimensionless variables. The resulting equations are then tackled using Laplace transformation to acquire the analytical solution for temperature and velocity. Figures and tables are produced for a further analysis of temperature and velocity characteristics. The study shows that an increase in nanoparticle volume fraction enhances nanofluid flow and heat transmission, proving highly beneficial for cancer treatment. However, the flow is retarded due to the increment of Casson parameter values, while an enhancement is observed with a superior accelerating parameter.

Convective heat transport and entropy generation in butterfly-shaped magneto-nanofluidic systems with bottom heating and top cooling

PurposeThe purpose of this study is to carry out a comprehensive analysis of magneto-hydrodynamics (MHD), nanofluidic flow dynamics and heat transfer as well as thermodynamic irreversibility, within a novel butterfly-shaped cavity. Gaining a thorough understanding of these phenomena will help to facilitate the design and optimization of thermal systems with complex geometries under magnetic fields in diverse applications.Design/methodology/approachTo achieve the objective, the finite element method is used to solve the governing equations of the problem. The effects of various controlling parameters such as butterfly-shaped triangle vertex angle (T), Rayleigh number (Ra), Hartmann number (Ha) and magnetic field inclination angle (γ ) on the hydrothermal performance are analyzed meticulously. By investigating the effects of these parameters, the authors contribute to the existing knowledge by shedding light on their influence on heat and fluid transport within butterfly-shaped cavities.FindingsThe major findings of this study reveal that the geometrical shape significantly alters fluid motion, heat transfer and irreversibility production. Maximum heat transfer, as well as entropy generation, occurs when the Rayleigh number reaches its maximum, the Hartmann number is minimized and the angle of the magnetic field is set to 30° or 150°, while the butterfly wings angle or vertex angle is kept at a maximum of 120°. The intensity of the magnetic field significantly controls the heat flow dynamics, with higher magnetic field strength causing a reduction in the flow strength as well as heat transfer. This configuration optimizes the heat transfer characteristics in the system.Research limitations/implicationsFurther research can be expanded on this study by examining thermal performance under different curvature effects, orientations, boundary conditions and additional factors. This can be accomplished through numerical simulations or experimental investigations under various multiphysical scenarios.Practical implicationsThe geometric configurations explored in this research have practical applications in various engineering fields, including heat exchangers, crystallization processes, microelectronic devices, energy storage systems, mixing processes, food processing, air-conditioning, filtration and more.Originality/valueThis study brings value by exploring a novel geometric configuration comprising the nanofluidic flow, and MHD effect, providing insights and potential innovations in the field of thermal fluid dynamics. The findings contribute a lot toward maximizing thermal performance in diverse fields of applications. The comparison of different hydrothermal behavior and thermodynamic entropy production under the varying geometric configuration adds novelty to this study.

Bulk Heating and Surface Evaporation of Nanofluids under Solar Radiation

Bulk Heating and Surface Evaporation of Nanofluids under Solar Radiation

Experimental study on enhanced nanofluid heat transfer limit and wetting predicted model in the microgroove under electric field

The coupled effect of nanofluid and electric field contributes better heat transfer on the microgroove heat sink that has considerable prospects for addressing the heat dissipation of mobile devices. However, the wettability and the electric field enhanced heat transfer limit (EHL) of microgroove at high heat flux are still unknown. Thus, the wettability and EHL of Al2O3-water nanofluid in the vertical microgroove under electric field and the capillary wetting length prediction model were experimentally studied and developed. Accordingly, the maximum enhancement of electric field on nanofluids with optimal concentration would be reached at high heat flux, which is 1.6 times than that on pure water and it presents the wall temperature difference of 20.1 °C. Moreover, drying up phenomenon occurs at high nanofluid concentrations can be retarded by increasing the voltage. The increase of electric field reduces the clogging of nanoparticles to avoid the drying up phenomenon in microgrooves, which has greatly promoted heat transfer and reduced the wall temperature. The increase of electric field reduces the clogging of nanoparticles, and the replenished working fluid can retard the drying up. Besides, the prediction model of capillary wetting length agrees well with the experimental value.

Impact of Flow, Heat and Mass Transfer of Newtonian and Non-Newtonian Nanofluids Flow over a Non-Darcy Stretching Sheet in the Context of Fuel Applications

The study of flow, heat, and mass transfer of Newtonian and non-Newtonian nanofluid over porous media holds paramount significance in the context of fuel industries, contributing to enhanced efficiency, reduced emissions, and sustainable energy production. This investigation provides a concise overview of the critical role played by porous media in various aspects of the fuel sector. In the oil and gas industry, porous reservoir formations exhibit complex fluid dynamics characterized by non-Darcy flow, influencing recovery rates of hydrocarbons. Understanding the relationship between flow, heat, and mass transfer within these porous reservoirs is essential for reservoir engineers and fuels the quest for maximizing resource extraction. The Sisko nanofluid model is one of the most sought-after mathematical model which prophesies the interesting features of Newtonian and non-Newtonian (dilatant and Pseudoplastic nature) fluids. In contemporary years, a new class of non-Newtonian fluids with nanoparticle suspensions are gaining popularity as it is beneficial in enhancing thermal efficiency in several applications such as warming/cooling of home appliances and micro-electronics etc. However, the modeling on this class of non-Newtonian fluids is limited. In light of above, this work predicts the stream, heat and mass transmission behavior of nanofluids using Sisko fluid model. Stretching sheet with porous medium has been used for this study with addition with magnetic field, thermal radiation, Brownian motion and thermophoresis. The non-linearity issues in this fluid flow are addressed in the prevailing work using suitable similarity transformations. The non-linear dimensional coupled P.D.E are converted into nonlinear dimensionless coupled O.D.E. These equations are solved using MATLAB by implementing four-stage Lobatto IIIa formula. The impacts of copious physical parameters of flow, energy and mass transfer insights are discussed. From the outcomes of current work, it is perceived that increasing the perviousness of the porous medium reduces the fluid mobility. Further, for increased values of Prandtl number the heat transfer coefficient increases ensuing in more heat transfer. Flow, heat, and mass transfer over porous media are integral to fuel industries, influencing resource extraction, energy conversion, and product quality

Magnetohydrodynamic thermal convection in constraint-based recto-triangular cavities with CuO-water nanofluid and differential bottom-top heating

The current research explores the thermal convection of magnetohydrodynamic flow in modified and constraint-based recto-triangular thermal systems (upper part rectangular and lower part triangular) filled with copper-oxide water nanofluid. The external uniform magnetic field is applied horizontally, while the magnetic field angle γ is varied systematically. The volume/area of thermal system cavities is maintained the same while their bottom triangular portions are adjusted considering various vertex angles (Θ) of 90–270°. The cooling and heating arrangements are provided for the same lengths using the top wall and the central portion of the bottom wall, respectively. The finite element method is used to discretize and solve the dimensionless governing transport equations. The thermal and flow analyses are conducted on the backdrop of constraint-based thermal systems for varying pertinent parameters like the Rayleigh number (Ra = 103–105), Hartmann number (Ha = 0–70), magnetic field angle (γ = 0–90°) and vertex angle (Θ = 90–270°). It is revealed that the flow structure becomes more complex and asymmetric in nature at high Ra and Ha. Furthermore, the average Nu is an increasing function of Ra and Θ, whereas it is a decreasing function of Ha. The entropy plots are also generated to study the entropy generation due to magnetohydrodynamic, viscous dissipation, and thermal effects that together constitute the total entropy of the system. The constraint-based system analysis could be very helpful for the design and identification of the most efficient system for the utilized same working fluid (volume).

Enhancing solar heater performance: A comprehensive study on hybrid nanofluids and angled-rib turbulators for improved heat transfer and reduced irreversibility

This research investigates the performance of hybrid nanofluids in solar heating systems, focusing on heat transfer effectiveness and thermodynamic irreversibility. Solar energy is widely favored for its eco-friendly nature, but traditional operating fluids in solar heaters lack sufficient thermal conductivity. To address this issue, modified fluids called nanofluids have been developed. This study proposes a novel approach that combines nanofluids and turbulators to evaluate solar system performance. ANSYS FLUENT 18.0 solver is employed, utilizing the iterative time advancement technique for solving the set of equations. Entropy generation analysis is employed as a promising methodology. Aluminum-oxide nanoparticles are examined for their impact on heat transfer, pressure drop, and entropy generation in a rib channel at Re= 20,000. To enhance heat transfer, the effects of angled-ribs are assessed using the thermal enhancement factor, which considers heat transfer rate and friction factor. Results indicate that triangular-shaped ribs exhibit superior thermal performance. Furthermore, the study investigates the influence of nanofluid volume fraction and heat flux distribution on Nusselt number, pressure drop, thermal performance factor, and entropy generation. Increasing the nanofluid fraction enhances the Nusselt number, pressure drop, and performance evaluation criterion (PEC). Based on the results of a quantitative analysis, it can be concluded that 4% nanoparticle volume fraction results in an increase of 4.6%, 11.63%, and 18.5% in Nusselt number in triangular and rectangular channels without teeth and with teeth, respectively. Additionally, a positive heat flux gradient improves heat transfer and reduces entropy generation, suggesting that adjusting the boundary condition can enhance energy and exergy efficiency. Overall, this study demonstrates the benefits of entropy generation analysis for assessing thermal systems and implementing hybrid nanofluids with turbulators in solar heating, contributing valuable insights to sustainable energy technologies.

Investigation of dissipation phenomenon of non-Newtonian nanofluid due to a horizontal stretching rough sheet through a Darcy porous medium

Recent advancements in thermal engineering have led to the development of stable thermal properties and practical applications for nanofluid flow. Consequently, this study aims to explore the heat and mass transfer characteristics of a non-Newtonian Maxwell nanofluid when it comes into contact with a stretched surface containing porous features that allow for fluid suction velocity. Additionally, the research takes into account how the Soret and Dufour effects impact the processes of heat and mass transfer. A less-explored aspect of research in this field relates to the velocity slip boundary conditions when nanofluids with changing viscosity are involved. Additionally, the model employed in this study illustrates the influence of both viscous dissipation and variable thermal conductivity on the processes of heat and mass transfer. The mathematical flow model is described by nonlinear partial differential equations, which are subsequently transformed into non-dimensional ordinary differential equations. The resulting system is then solved numerically using the shooting method. This study visually examines the impact of physical variables on temperature, flow characteristics, and concentration patterns. Furthermore, it provides graphical representations of estimated values for the skin friction coefficient, Sherwood numbers, and local Nusselt numbers, which are also organized in tables for analysis. In conclusion, by comparing our data with previous results, we confirm the accuracy and reliability of the proposed method. A significant discovery is that the nanofluid velocity decreases as the Maxwell, porous, and slip velocity parameters are increased. Furthermore, the nanofluid concentration rises when the thermophoresis and viscosity parameters increase.