Flow Mass Transfer Research Articles

Effect of Suction/Injection on Unsteady MHD Natural Convection Flow of Heat Mass Transfer in Porous Channel in the Presence of Soret Term

This research paper explores the effect of suction/injection on unsteady MHD natural convection flow of heat mass transfer in porous channel in the presence of Soret term. The governing partial differential equations are converted to non- dimensional forms and solved numerically by using unconditionally stable and convergent implicit finite difference method. A parametric study illustrating the influence of various physical parameters is performed. It is reported that the velocity profile increases as Soret term, Grashof number, Solutal Grashof number and Porous parameters values increase, while Magnetic field parameter decreases the velocity profile. The temperature profile rises by the influence in increasing values of Variable Thermal Conductivity and decreases by increasing values of Prandtl number and Radiation parameters. While concentration profile increase by the increasing values of Soret term and Chemical reaction. The dependence of the skin friction coefficient, rate of heat transfer and mass transfer on these parameter has been discussed.

Heat and mass transfer analysis of s-PTT nanofluid in microchannels under combined electroosmotic and pressure-driven flows with wall slip using the homotopy perturbation method

The heat and mass transfer of the electroosmotic flow in microchannel transporting viscoelastic nanofluid is investigated considering Brownian motion of nanoparticles and slip boundary conditions. The simplified Phan-Thien-Tanner model is employed to describe the rheological behavior of fluid and the nonlinear Navier model with non-zero slip critical shear stress is considered at walls. The governing nonlinear momentum, mass, and heat transfer equations are solved using the Homotopy Perturbation Method. The study reveals that increasing the fluid elasticity, nanoparticle concentration, and size significantly enhances the flow rate, heat and mass transfer. Additionally, elasticity and Reynolds number decrease the friction factor. Reducing the double-layer thickness and increasing the Reynolds number lead to higher flow rates and fluid velocities. Notably, the findings emphasize the critical role of the slip conditions on the Sherwood and Nusselt numbers.

Influence of non-linear thermal radiation on the dynamics of homogeneous and heterogeneous chemical reactions between the cone and the disk

Abstract Purpose The current work presents a theoretical framework to boost heat transmission in a ternary hybrid nanofluid with homogeneous and heterogeneous reactions in the conical gap between the cone and disk apparatus. Furthermore, the impacts of non-linear thermal radiation on the ternary hybrid nanofluid composed of white graphene, diamond, and titanium dioxide dispersed in water are analyzed. Originality/value The combination of cone and disk systems is crucial for designing efficient heat exchange devices in the field of biomedical science for various purposes. For instance, in medical devices, the cone–disk apparatus is used to study the flow and heat transfer characteristics for better design and functionality. Hence, a sincere attempt has been made to study the impact of homogeneous and heterogeneous reactions on the nanofluid flow between the cone and disk in the presence of non-linear thermal radiation. Design/methodology/approach The mathematical model’s governing equations are partial differential equations (PDEs) which are then transformed into non-linear ordinary differential equations through appropriate similarity transformations. These transformed resultant equations are approximated by the Runge–Kutta–Fehlberg fourth/fifth order (RKF45) technique. The influence of essential aspects on the flow field, heat, and mass transfer rates was analyzed using a graphical representation. Findings The interesting part of this research is to discuss the power of parameters in three cases, namely, (1) rotating cone/disk, (2) rotating cone/stationary disk, and (3) stationary cone/rotating disk. Furthermore, the thermal variation of the fluid is analyzed by an artificial neural network with the help of the Levenberg–Marquardt backpropagation algorithm. The regression analysis, mean square error, and error histogram of the neural network are analyzed using this algorithm. From the graph, it is perceived that the flow field climbed up significantly with an increase in the values of radiation parameters in all cases. Also, it is noticed that temperature upsurges significantly by upward values of solid volume fraction of the nanoparticles ( ϕ \phi ).

Solute Transport in a Multi-Channel Karst System with Immobile Zones: An Example of Downtown Salado Spring Complex, Salado, Texas

To investigate the influence of flow rate increment on the solute transport parameter of immobile zones in a karst system, a dye tracer test was conducted in the Downtown Salado Spring Complex (DSSC) comprising three springs: Big Boiling, Anderson, and Doc Benedict springs. The Multiflow two-region nonequilibrium model (2RNE) was used to simulate the breakthrough curve (BTC) of the springs, and changes in the solute transport parameters in response to flow rate increment were observed. The simulation result showed that the 2RNE model was capable of reproducing the BTC of all the DSSC springs, with an R-squared value greater than 0.9 in all flow rate increment scenarios. The research demonstrates that a positive correlation will exist between the flow rate and solute transport parameter of the immobile zones if the tracer transport to the spring is truly influenced by immobile zones. In contrast, a negative correlation will exist between the flow rate and mass transfer coefficient if the immobile zone has less influence. Overall, the research provides insights into contaminant movement in karst by documenting how tracers are retained in the immobile fluid zone.

Study on the mechanism of vacuum carbothermal reduction of Ca3(PO4)2 enhanced by SiO2

Vacuum carbothermal reduction mechanism of Ca3(PO4)2 with addition SiO2 was studied by combining FactSage 8.1 thermodynamic theoretical calculations with experiments. The theoretical calculations showed that adding SiO2 effectively reduced the initial reaction temperature. The experimental results showed that the addition of SiO2 significantly improved weight loss and volatilization rates of phosphorus. Ca2SiO4 and CaSiO3 were generated during the reaction. When the SiO2/CaO ratio was 1.25 at 1300 °C, the reduction effect of Ca3(PO4)2 and the volatilization rate of phosphorus was optimal, with a volatilization rate of 91.98 %. Excessive SiO2 led to insufficient contact between the reactants and reducing agent C, thereby hindering the reaction. Simultaneously, a large amount of liquid phase was produced, which deteriorated the kinetic conditions of gas diffusion and affected the reaction. In the reduction process, Ca3(PO4)2 reacted with reducing agent C to generate CaO, then reacted with external SiO2 to generate low melting point CaSiO3, which wrapped the unreacted core. With an increase in the low melting point CaSiO3, the mass transfer in the reaction changed from diffusion mass transfer to flow mass transfer, which promoted the inward diffusion of reducing agent C to contact the unreacted core until the reduction reaction was completed.

Heat and mass transfer in MHD flow of SWCNT and graphene nanoparticles suspension in Casson fluid

AbstractThe exceptional mechanical properties of carbon nanotubes (CNTs) and graphene nanoparticles, particularly their high aspect ratio and flexibility, position them as highly promising materials for the next generation of armor technology. Their incorporation into protective wear, such as bullet‐proof vests, offers the potential for significant improvements in both performance and cost efficiency. By replacing traditional materials with CNTs and graphene, the durability and maintenance of these protective devices could be substantially enhanced, leading to more effective and sustainable solutions for personal safety. This study focuses on the complex phenomena of heat and mass transport within a suspension of CNTs and graphene nanoparticles dispersed in a Casson fluid, particularly under the influence of an applied magnetic field. The analysis begins by reformulating the governing equations using similarity variables to transform them into a dimensionless form to simplify the problem. The resulting dimensionless equations are then solved using the three‐stage Lobatto IIIa finite difference method, a robust numerical technique well‐suited for solving boundary value problems in fluid dynamics. The results of this investigation highlight a significant 78.41% reduction in skin friction when compared with traditional CNT‐water nanofluid systems. This considerable decrease in skin friction not only reveals the superior performance of the CNT‐graphene nanofluid suspension but also opens up new possibilities for the design and development of advanced protective materials. These findings contribute to the growing body of knowledge on nanofluid applications and offer valuable insights for future research in the field of advanced armor technology.

Entropy generation of Williamson hydromagnetic non-linear radiative nanofluid flow near a stagnation point over a porous stretching sheet

Purpose This study aims to analyze the multi-slip effects of entropy generation in steady non-linear magnetohydrodynamics thermal radiation with Williamson nanofluid flow across a porous stretched sheet near a stagnation point. Also, the qualities of viscous dissipation, Cattaneo–Christove heat flux and Arrhenius activation energy are taken into account. Thermophoresis, Brownian motion and Joule heating are also considered. Design/methodology/approach The Navier–Stokes equation, the thermal energy equation and the Solutal concentration equations are the governing mathematical equations that describe the flow and heat and mass transfer phenomena for fluid domains. By using the proper similarity transformations, a set of ordinary differential equationss are retrieved from boundary flow equations. The classical Runge–Kutta fifth-order algorithm along with the shooting technique is implemented to solve the obtained first order differential equations. Findings The study concludes that the temperature distribution boosting for thermal radiation, magnetic field and Eckert number where as the velocity and entropy generation escalate for the Williamson parameter, diffusion parameter and Brinkman number. The skin-friction and heat and mass transfer rate increases with the fluid injection. In addition, tabulated values of friction drag and rate of heat and mass transfer for various values of constraints are provided. Originality/value The comparison of the present results is carried out with the published results and noted a good agreement.

Soret and dufour impacts on radiative power-law fluid flow via continuously stretchable surface with varying viscosity and thermal conductivity

The intricate dynamics of mixed convective thermic and species transport in a power-law flowing fluid through a continuously stretched surface are investigated. The uniqueness of this study lies in the consideration of fluid variable thermic conductivity and viscosity, which introduces a higher degree of realism into the analysis. The transformation of similarity is used to transform the fundamental governing equations, and after that, the set of equations is processed numerically utilizing a non-similarity local approach. Furthermore, the effects of Soret and Dufour represent the cross-diffusion phenomena, accounting for the energy exchange with the surroundings. These factors collectively influence the stretching surface’s gradient velocity, affecting the thermal and species concentration rates. The findings offer a comprehensive understanding of these complex interactions, paving the way for optimizing thermic and species transport processes in various industrial applications. This study, therefore, holds significant potential for enhancing efficiency and performance in relevant industrial sectors. The main terms are the combinations of Dufour and Soret numbers that significantly impact the flow rate profile and mass transfer field. The coupled study of the nonlinear velocity, energy distribution and chemical mixture variance made the study more impactful in practicality. Skin friction variation shows limited impact with variations in the Soret number. The enhanced thermal gradient results in improved non-similarity parameters, yet it demonstrates a decrease with an increase in variable thermal diffusivity. There is a decrease in the temperature gradient as the buoyancy term reduces, while an increase is observed with changes in the Prandtl number. Similarly, the Nusselt number experiences a comparable impact due to changes in the Soret number.

A computational study of Eyring‐Powell fluid model over a rotating cone with magnetic field and joule heating effect

AbstractIn this research, we investigate mixed convection transport of mass and heat transfer in the unsteady boundary layer flow of the Eyring‐Powell fluid around a rotating cone in the presence of Brownian and thermophoresis effects. Rotating cones are widely used in conical diffusers, medical devices, Aerospace Engineering and a variety of rheometric and viscosimetry applications. Specifically, we focus on the flow of the Eyring‐Powell fluid around the cone in the presence of magnetohydrodynamics and nanofluid. The modeled momentum, energy, and concentration equations of the problem are transformed into nonlinear dimensionless, nonlinear ordinary equations by utilizing the similarity variables. These nonlinear coupled ordinary differential equations are solved numerically via Bvp4c, and the outcomes for important physical parameters on momentum, energy, and concentration equations are presented graphically. The computational outcomes of physical parameters for skin friction coefficient, local Nusselt number, and Sherwood are also presented in tabular form.

Consequences of thermal conductivity and thermal density on heat and mass transfer in the nanofluid boundary layer flow toward a stretching sheet in the presence of a magnetic field

The term “thermal conductance” is used to describe a material’s ability to transport or conduct heat. Materials with high thermal conductivity are employed as heating elements, while those with poor thermal conductivity are used for insulation purposes. It is known that the thermal conductivity of pure metals decreases as temperature increases. In this study, the primary focus is on the physical assessment of thermal conductivity, entropy, and the improvement rate of thermal density in a magnetic nanofluid. To achieve this, nonlinear partial differential equations are transformed into ordinary differential equations. These equations are further solved using a computational method known as the Keller box technique. Various flow parameters, such as the Eckert number, density parameter, magnetic-force parameter, thermophoretic number, buoyancy number, and Prandtl parameter, are examined for their impact on velocity, temperature distribution, and concentration distribution. For the asymptotic results, the appropriate range of parameters, such as 1.0 ≤ ξ ≤ 5.0, 0.0 ≤ n ≤ 0.9, 0.1 ≤ Ec ≤ 2.0, 0.7 ≤ Pr ≤ 7.0, 0.1 ≤ Nt ≤ 0.5, and 0.1 ≤ Nb ≤ 0.9, is utilized. The key findings of this study are related to the assessment of heat transfer in a magnetic nanofluid considering thermal conductivity, entropy generation, and temperature density. It is observed that the temperature distribution increases as entropy generation increases. From a physical perspective, thermal conductivity acts as a facilitating factor in enhancing heat transfer. The study concludes by emphasizing the consistency achieved through a comparison of the latest findings with previously reported analyses.

Multilayer deep-learning intelligent computing for the numerical analysis of unsteady heat and mass transfer in MHD Carreau Nanofluid model

The objective of this article is to investigate the mechanism of unsteady heat and mass transfer (HMT) in a magnetohydrodynamics Carreau nanofluid flow (MHD-CNFF). To accomplish this, we utilized a novel artificial intelligence-based (AI) method, deep learning predictive technique combined with Levenberg-Marquardt scheme (DLPT-LMS). The similarity transformation is applied to convert the partial differential equations (PDEs) into a set of non-linear ordinary differential equations (ODEs). We numerically solved these resulting ODEs using the Adam numerical approach in sophisticated “Mathematica” software. The influence of Brownian motion parameter, thermophoresis parameters, Prandtl number, Lewis number, and mass transfer parameters on the temperature, velocity, and concentration profile is analyzed using a synthetic dataset. This evaluation is conducted across different variation of MHD-CNFF by leveraging DLPT-LMS. The absolute error (AE) across various iteration of MHD-CNFF demonstrated a progressive drop, indicating the accuracy of DLPT-LMS. The outcomes of this investigation revealed that the AE ranged from 10-3 to 10-8 which shows a minimum error between actual and predicted value. Additionally, the MSE confirmed the accuracy of proposed DLPT-LMS in predicting the behavior of velocity, temperature, and concentration profiles, with lower values showing better predictions. The model accuracy was reinforced by performance results, including regression analysis and error histograms. Error values gradually decreased during training, validation, and testing phases, exhibiting a robust convergence and indicating the highly reliability of AI-based algorithm for investigating intricate fluid dynamics in MHD-CNFF systems.

Multi-physics coupling numerical simulation of variable porosity in reactive melt infiltration process

Abstract The hypersonic craft necessitates significant advancements in thermal shielding to safeguard against the extreme aero-thermal environments encountered during flight at hypersonic speeds in near space or upon reentry from space. Carbon fiber-reinforced ceramic matrix composites (FRCMCs) have attracted increasingly interesting attention as advanced structural materials for application in thermal protection. The reactive melt infiltration (RMI) process is preferred for the preparation of FRCMCs because of its low cost and short processing time. However, the RMI process includes the complex interplay of melt flow, reaction dynamics, and thermal fields, with existing models failing to accurately predict these processes due to their uncoupled nature and neglect of pore structure changes. This study introduces a coupled model that integrates mass transfer flow, chemical reaction, and heat transfer, incorporating variable pore structures to more accurately evaluate the RMI process. This approach allows for a comprehensive assessment of internal pressure, temperature, and porosity changes during silicon infiltration into porous media, marking an improvement over the previous model. The model has been validated for use in predicting the exotherm of RMI processes. In conclusion, this coupled model presents a promising avenue for enhancing the fabrication of FRCMCs, either considering the melt infiltration from multiple locations in the RMI process or adjusting the pore structure at the infiltration location to larger pores.

Heat and mass transfer in tri‐layer ependymal ciliary transport with diverse viscosity

AbstractSpecialized cilia known as ependymal cilia help the cerebrospinal fluid, which is important for nutrient delivery and waste elimination, to circulate in the brain. Many species rely on cilia and flagella for fluid movement and motility. Cilia and flagella, for instance, produce propulsive forces that allow unicellular creatures like Paramecium and Euglena to move through their surroundings. Ciliary transport plays a role in the flow of egg cells, or oocytes, via the fallopian tubes in the female reproductive system. The transfer of the egg towards the uterus is facilitated by the synchronized wave‐like motion produced by the cilia lining the fallopian tubes. Like this, ciliary transport in men aids in the passage of sperm cells via the epididymis. Many scientists and researchers are studying the mechanics of cilia motion and the properties of the viscoelastic fluid layer to develop new treatments and applications in biomedical engineering and for some diseases. Motivated by a wide range of biological applications, the objective of this study is to investigate the heat and mass transfer flow of tri‐layered Newtonian fluids flowing with the help of ciliary beating in a Cartesian coordinate. The fluid is incompressible, and fluid layers are not intermixed. The fluid flow with heat and mass transfer is first modelled in wave and then transmuted into fixed. Solutions for temperature profile, velocity distribution, stresses and concentration distribution are obtained. The influence of incipient parameters is displayed with graphs and plotted with the computational software MATHEMATICA 13.0 in the results section. The key findings obtained from graphs show that the maximum magnitude for temperature and velocity is achieved in the middle layer of fluid whereas in the outer layer concentration profile is maximum. It is predicted that this approach will make an essential contribution to the progress and enhancement of various types of drug delivery systems in the biomedical industry and biomechanics.

Molten pool macroscopic thermodynamic analysis during selective laser melting of AlSi10Mg: Simulations and experiments

In this study, the three-dimensional (3D) finite element model of COMSOL Multiphysics was used to simulate the thermodynamic behavior of the AlSi10Mg molten pool (MP) during selective laser melting (SLM), and the results were verified by multiple groups of single-track SLM experiments. The simulations take into account numerous thermophysical phenomena such as fluid flow, heat conduction, heat radiation, and fluid mass transfer. The influence of laser power, scanning speed, and other process parameters on temperature, shape, and size of MP was investigated. The simulated results and the experimental validation show that the model predictions are highly consistent with the measured data for most sets laser parameters, especially the MP width of 142 μm vs. 145 μm, depth of 53 μm vs. 56 μm at a laser power of 250 W and a scanning speed of 1000 mm/s, which confirms the reliability and accuracy of the model. Furthermore, the model innovatively forecasts the critical parameters for solidification in MP and delves into the intricate relationship between the position in MP and key parameters such as temperature gradient, cooling rate, and solidification rate. The model's versatility ensures its applicability to SLM simulation processes across diverse alloys and varying parameters. This research not only enhances our comprehension of SLM but also establishes a scientific foundation for optimizing processes, controlling microstructures, and enhancing material performance.

Integrated neural network based simulation of thermo solutal radiative double-diffusive convection of ternary hybrid nanofluid flow in an inclined annulus with thermophoretic particle deposition

Numerical simulation of magnetohydrodynamic radiative double-diffusive convective heat and mass transfer of a ternary hybrid nanofluid with thermophoretic particle deposition in an inclined annulus is studied. Both sides of cylinders are preserved at uniform temperatures, while the remaining sides are thermally insulated. The coupled nonlinear partial differential equations are solved using a finite difference approach. The detailed computational results of heat and mass transfer rate, temperature, concentration and flow fields are presented and discussed for a distinct range of significant physical parameters. The results demonstrated that increasing the angle of the inclination factor increases fluid flow. In light of buoyancy, when the annular cavity is set downward, the enhanced shear velocity is transported upwards, where it reaches its optimal temperature. The higher temperature difference leads to augmented dynamic fluid motion, particularly in the radial direction, as the system seeks to balance the thermal energy through convective transfer. The Brownian motion parameter has abrupt mobility of nanoparticles in liquid, which promotes particle collisions with liquid molecules, yielding kinetic energy. Increased values of thermophoretic parameters augment the thermophoresis force. Thermophoretic particle deposition increases the concentration of nanoparticles in an annulus due to the migration of particles from hot to cold regions under the influence of temperature gradient. The heat and mass transfer characteristics of ternary hybrid nanofluid are forecasted through an artificial neural network-based Levenberg–Marquardt backpropagated algorithm. The built model shows the heat and mass transfer rate root mean squared values through the Levenberg–Marquardt algorithm as one and mean squared error values as 1e-07 and 1e-08 respectively.

Numerical investigation of the effects of variable fluid properties on cilia-driven flow of tangent hyperbolic fluid in a channel with heat and mass transfer: A new approach to microfluidic pumps

Heat, mass transfer, and non-Newtonian fluid flow processes have gained significant interest in various industrial applications due to their substantial significance in the fields of technology, engineering, and science. The aforementioned processes hold significance in the context of polymer solutions, porous industrial materials, ceramic processing, oil recovery, and fluid beds. This study aims to investigate the impact of temperature-dependent viscosity and thermal conductivity on the cilia-driven flow of tangent hyperbolic fluid with mass and heat transfer. The objectives include analyzing how these variable properties affect the velocity, temperature, and concentration profiles within the fluid flow, thereby providing insights into potential applications in bioenergy systems and enhancing the understanding of non-Newtonian fluid dynamics. Viscous dissipation has been taken into consideration. Firstly, governing nonlinear coupled equations are solved in a fixed frame, and then the results are tracked in the wave frame. MATHEMATICA's NDSolve command is utilized to graphically discuss the findings for several different flow parameters. Analytically stated, solving a problem with such a coupled and nonlinear system is tough. The effect of new parameters is discussed on velocity and temperature profile and graphically shown. It has been observed that the thermal conductivity is improved at moderately low temperatures, whereas the opposite pattern is seen at comparatively high temperatures. On the other hand, the temperature distribution demonstrates a behaviour consistent with lowering as the number of heat Bolus increases. The findings that were provided offer beneficial insight into bioenergy systems and serve as a helpful benchmark for both experimental and extra-progressive computational Multiphysics models.

Flow characteristics and mass transfer performance of phosphoric acid extraction in a T-type central plug-in microreactor

In recent years, the demand for phosphoric acid, a key raw material for lithium iron phosphate batteries, has surged. However, current phosphoric acid extraction equipment faces challenges such as low mass transfer efficiency and difficulty in phase separation, leading to reduced production efficiency, bulky equipment, and scaling issues. To address these problems, this study introduces a T-type central plug-in microreactor (TCPM) designed to enhance mass transfer efficiency and facilitate rapid phase separation. The extraction of phosphoric acid from the water phase to the organic phase (volume ratio of tributyl phosphate to kerosene is 4:1) was chosen as the experimental system. We investigated the effects of various parameters on liquid-liquid flow and mass transfer characteristics in the TCPM. Visualization techniques identified slug and parallel flow as the primary liquid-liquid flow patterns within the TCPM. Notably, the central plug-in promotes the formation of parallel flow, improving phase separation compared to conventional T-type microreactors. The volume mass transfer coefficient of the TCPM ranges from 0.023 to 0.074 s-1, and the optimal phosphoric acid extraction efficiency and volume mass transfer coefficient can reach up to 90.5% and 0.074 s-1, respectively, outperforming conventional T-type microreactors. Predictive model for extraction efficiency was developed, showing deviations within 10%. These findings demonstrate the TCPM's potential as an efficient phosphoric acid extraction device with rapid phase separation, holding significant promise for liquid-liquid extraction applications.

Heat and Mass Transfer in MHD Flow of a Nanofluid through a Porous Medium over a Stretching Sheet with Chemical Reaction

Heat and Mass Transfer in MHD Flow of a Nanofluid through a Porous Medium over a Stretching Sheet with Chemical Reaction

MHD Stefan Flow of Casson Nanofluid Complete a Porous Medium in The Presence of Chemical Reaction with The Effect of Thompson as Well as Troian Slip Over a Plate in the Company of Radiation

In this work, we report the effects of Thompson, Troian slip, and Stefan blowing on the magnetohydrodynamic (MHD) Cassonnanofluid behavior via a porous media while a chemical reaction is taking place. We also examine the effects of radiation parameters, Joel heat, and velocity distribution using a two-phase model for nanofluids. Similarity transformations may be used to convert the primary Partial Differential Equations (PDEs) into Ordinary Differential Equations (ODEs). MATLAB Shooting and Runge-Kutta algorithms may be used to solve nonlinear equations. The variations in non-dimensional parameters show the effects on mass transfer, heat, and fluid flow properties. It is shown that the skin friction coefficient falls as the Stefan blowing parameter S increases. As the values of the Thompson and Troian slip parameters increase, the fluid concentration decreases. With an increase in Nt, Nb, and k, the fluid's heat rises but its concentration falls. The results of this analysis provide several enticing aspects that are going to give merits for further study of the problems.

Computation of soret effect in sisko nanofluid flow over a stretching sheet encompassing chemical reaction and viscous dissipation

This article examines the characteristics of mass and heat transfer in Sisko fluid flow. The consideration is given to continuous, two-dimensional movement of Sisko fluid exhibiting incompressible and viscous characteristics. The fluid flows over a stretching sheet encompassing chemical reaction and subjected to the soret effect and viscous dissipation. The arising set of interconnected PDEs is converted to nonlinear ODEs using similarity transformations. This study reveals that an increase in the Soret number induces an upward shift in the concentration profile across the flow region. Also, an increase in the Sisko fluid parameter gives rise in the skin-friction coefficient. Following the calculations, the results for the heat, mass transfer rate and skin-friction coefficient, are compiled and presented in a tabulated form. A systematic discussion of similarity solutions in comparison with established findings not only validates the accuracy of the numerical results but also underlines the reliability and robustness of the methodology applied in this study.