Enhancing the trustworthiness of chaos and synchronization of chaotic satellite model: a practice of discrete fractional-order approaches.

Accurate development of satellite maneuvers necessitates a broad orbital dynamical system and efficient nonlinear control techniques. For achieving the intended formation, a framework of a discrete fractional difference satellite model is constructed by the use of commensurate and non-commensurate orders for the control and synchronization of fractional-order chaotic satellite system. The efficacy of the suggested framework is evaluated employing a numerical simulation of the concerning dynamic systems of motion while taking into account multiple considerations such as Lyapunov exponent research, phase images and bifurcation schematics. With the aid of discrete nabla operators, we monitor the qualitative behavioural patterns of satellite systems in order to provide justification for the structure's chaos. We acquire the fixed points of the proposed trajectory. At each fixed point, we calculate the eigenvalue of the satellite system's Jacobian matrix and check for zones of instability. The outcomes exhibit a wide range of multifaceted behaviours resulting from the interaction with various fractional-orders in the offered system. Additionally, the sample entropy evaluation is employed in the research to determine complexities and endorse the existence of chaos. To maintain stability and synchronize the system, nonlinear controllers are additionally provided. The study highlights the technique's vulnerability to fractional-order factors, resulting in exclusive, changing trends and equilibrium frameworks. Because of its diverse and convoluted behaviour, the satellite chaotic model is an intriguing and crucial subject for research.

Complex adaptive learning cortical neural network systems for solving time-fractional difference equations with bursting and mixed-mode oscillation behaviours.

Complex networks have been programmed to mimic the input and output functions in multiple biophysical algorithms of cortical neurons at spiking resolution. Prior research has demonstrated that the ineffectual features of membranes can be taken into account by discrete fractional commensurate, non-commensurate and variable-order patterns, which may generate multiple kinds of memory-dependent behaviour. Firing structures involving regular resonator chattering, fast, chaotic spiking and chaotic bursts play important roles in cortical nerve cell insights and execution. Yet, it is unclear how extensively the behaviour of discrete fractional-order excited mechanisms can modify firing cell attributes. It is illustrated that the discrete fractional behaviour of the Izhikevich neuron framework can generate an assortment of resonances for cortical activity via the aforesaid scheme. We analyze the bifurcation using fragmenting periodic solutions to demonstrate the evolution of periods in the framework's behaviour. We investigate various bursting trends both conceptually and computationally with the fractional difference equation. Additionally, the consequences of an excitable and inhibited Izhikevich neuron network (INN) utilizing a regulated factor set exhibit distinctive dynamic actions depending on fractional exponents regulating over extended exchanges. Ultimately, dynamic controllers for stabilizing and synchronizing the suggested framework are shown. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a discrete fractional-order activated nerve cell framework incorporating a Caputo-type fractional difference operator can be used to investigate the impacts of complex interactions on the surge-empowering capabilities noticed within our findings. The relevance of this expansion is based on the model's structure as well as the commensurate and incommensurate fractional-orders, which take kernel and inherited characteristics into account. We begin by providing data regarding the fluctuations in electronic operations using the fractional exponent. We investigate two-dimensional Morris-Lecar neuronal cell frameworks via spiked and saturated attributes, as well as mixed-mode oscillations and mixed-mode bursting oscillations of a decoupled fractional-order neuronal cell. The investigation proceeds by using a three-dimensional slow-fast Morris-Lecar simulation within the fractional context. The proposed method determines a method for describing multiple parallels within fractional and integer-order behaviour. We examine distinctive attribute environments where inactive status develops in detached neural networks using stability and bifurcation assessment. We demonstrate features that are in accordance with the analysis's findings. The Erdös-Rényi connection of asynchronization transformed neural networks (periodic and actionable) is subsequently assembled and paired via membranes that are under pressure. It is capable of generating multifaceted launching processes in which dormant neural networks begin to come under scrutiny. Additionally, we demonstrated that boosting connections can cause classification synchronization, allowing network devices to activate in conjunction in the future. We construct a reduced-order simulation constructed around clustering synchronisation that may represent the operations that comprise the whole system. Our findings indicate the influence of fractional-order is dependent on connections between neurons and the system's stored evidence. Moreover, the processes capture the consequences of fractional derivatives on surge regularity modification and enhance delays that happen across numerous time frames in neural processing.

Deterministic-stochastic analysis of fractional differential equations malnutrition model with random perturbations and crossover effects.

To boost the handful of nutrient-dense individuals in the societal structure, adequate health care documentation and comprehension are permitted. This will strengthen and optimize the well-being of the community, particularly the girls and women of the community that are welcoming the new generation. In this article, we extensively explored a deterministic-stochastic malnutrition model involving nonlinear perturbation via piecewise fractional operators techniques. This novel concept leads us to analyze and predict the process from the beginning to the end of the well-being growth, as it offers the possibility to observe many behaviors from cross over to stochastic processes. Moreover, the piecewise differential operators, which can be constructed with operators such as classical, Caputo, Caputo-Fabrizio, Atangana-Baleanu and stochastic derivative. The threshold parameter is developed and the role of malnutrition in society is examined. Through a rigorous analysis, we first demonstrated that the stochastic model's solution is positive and global. Then, using appropriate stochastic Lyapunov candidates, we examined whether the stochastic system acknowledges a unique ergodic stationary distribution. The objective of this investigation is to design a nutritional deficiency in pregnant women using a piecewise fractional differential equation scheme. We examined multiple options and outlined numerical methods of coping with problems. To exemplify the effectiveness of the suggested concept, graphical conclusions, including chaotic and random perturbation patterns, are supplied. Consequently, fractional calculus' innovative aspects provide more powerful and flexible layouts, enabling us to more effectively adapt to the system dynamics tendencies of real-world representations. This has opened new doors to readers in different disciplines and enabled them to capture different behaviors at different time intervals.

Entropy structural characterization of zeolites BCT and DFT with bond-wise scaled comparison.

Entropy of a connected network is a quantitative measure from information theory that has triggered a plethora of research domains in molecular chemistry, biological sciences and computer programming due to its inherent capacity to explore the structural characteristics of complex molecular frameworks that have low structural symmetry as well as high diversity. The analysis of the structural order is greatly simplified through the topological indices based graph entropy metrics, which are then utilized to predict the structural features of molecular frameworks. This predictability has not only revolutionized the study of zeolitic frameworks but has also given rise to new generations of frameworks. We make a comparative study of two versatile framework topologies namely zeolites BCT and DFT, which have been widely utilized to create a new generation of frameworks known as metal organic frameworks. We discuss bond-additive topological indices and compute entropy measure descriptors for zeolites BCT and DFT using degree and degree-sum parameters. In addition, we perform bond-wise scaled comparative analysis between BCT and DFT which shows that zeolite BCT has greater entropy values compared to zeolite DFT.

Predictive dynamical modeling and stability of the equilibria in a discrete fractional difference COVID-19 epidemic model.

The SARSCoV-2 virus, also known as the coronavirus-2, is the consequence of COVID-19, a severe acute respiratory syndrome. Droplets from an infectious individual are how the pathogen is transmitted from one individual to another and occasionally, these particles can contain toxic textures that could also serve as an entry point for the pathogen. We formed a discrete fractional-order COVID-19 framework for this investigation using information and inferences from Thailand. To combat the illnesses, the region has implemented mandatory vaccination, interpersonal stratification and mask distribution programs. As a result, we divided the vulnerable people into two groups: those who support the initiatives and those who do not take the influence regulations seriously. We analyze endemic problems and common data while demonstrating the threshold evolution defined by the fundamental reproductive quantity R 0 . Employing the mean general interval, we have evaluated the configuration value systems in our framework. Such a framework has been shown to be adaptable to changing pathogen populations over time. The Picard Lindelöf technique is applied to determine the existence-uniqueness of the solution for the proposed scheme. In light of the relationship between the R 0 and the consistency of the fixed points in this framework, several theoretical conclusions are made. Numerous numerical simulations are conducted to validate the outcome.

MHD Flow of a Newtonian Fluid in Symmetric Channel with ABC Fractional Model Containing Hybrid Nanoparticles.

INTRODUCTION: The nanofluid is the novelty of nanotechnology to overcome the difficulties of heat transfer in several manufacturing and engineering areas. Fractional calculus has many applications in nearly all fields of science and engineering, which include electrochemistry, dispersion and viscoelasticity. OBJECTIVES: This paper focused on the heat transfer of a hybrid nanofluid in two vertical parallel plates and presented a comparison between fractional operators. METHODS: In this paper, the fractional viscous fluid model is considered along with physical initial and boundary conditions for the movement occurrences. The analytical solutions have been obtained via the Laplace transform method for the concentration, temperature and velocity fields. After that, we have presented a comparison between Atangana-Baleanu (ABC), Caputo (C) and Caputo-Fabrizio (CF) fractional operators. RESULTS: The comparison of different base fluids (Water, kerosene, Engine Oil) is discussed graphically with respect to temperature and velocity. The results show that due to the high thermal conductivity of water, temperature and velocity are high. While engine oil has maximum viscosity than water and kerosene, thus temperature and velocity are very low. However, due to the improvement in the thermal conductivity with the enrichment of hybrid nanoparticles, the temperature increased, and since the viscosity also increased, the velocity got reduced. CONCLUSION: Atangana-Baleanu (ABC) fractional operator provided better memory effect of concentration, temperature and velocity fields than Caputo (C) and Caputo-Fabrizio (CF). Temperature and velocity of water with hybridized nanoparticles were high in comparison to kerosene and engine oil.

Optimal Homotopic Exploration of Features of Cattaneo-Christov Model in Second Grade Nanofluid Flow via Darcy-Forchheimer Medium Subject to Viscous Dissipation and Thermal Radiation.

INTRODUCTION: In this article, Optimal Homotopy Analysis Method (oHAM) is used for the exploration of the features of the Cattaneo-Christov model in viscous and chemically reactive nanofluid flow through a porous medium with stretching velocity at the solid/sheet surface and free stream velocity at the free surface. METHODS: The two important aspects, Brownian motion and Thermophoresis, are considered. Thermal radiation is also included in the present model. Based on the heat and mass flux, the Cattaneo- Christov model is implemented on the Temperature and Concentration distributions. The governing Partial Differential Equations (PDEs) are converted into Ordinary Differential Equations (ODEs) using similarity transformations. The results are achieved using the optimal homotopy analysis method (oHAM). The optimal convergence and residual errors have been calculated to preserve the validity of the model. RESULTS: The results are plotted graphically to see the variations in three main profiles. i.e. momentum, temperature and concentration profile. CONCLUSION: The outcomes indicate that skin friction enhances due to the implementation of the Darcy medium. It is also noted that the relaxation time parameter results in enhancement of the temperature distribution. Thermal radiation enhances the temperature distribution and so is the case with skin friction.

Mathematical modeling and optimal control of the COVID-19 dynamics.

We are considering a new COVID-19 model with an optimal control analysis when vaccination is present. Firstly, we formulate the vaccine-free model and present the associated mathematical results involved. Stability results for R 0 < 1 are shown. In addition, we frame the model with the vaccination class. We look at the mathematical results with the details of the vaccine model. Additionally, we are considering setting controls to minimize infection spread and control. We consider four different controls, such as prevention, vaccination control, rapid screening of people in the exposed category, and people who are identified as infected without screening. Using the suggested controls, we develop an optimal control model and derive mathematical results from it. In addition, the mathematical model with control and without control is resolved by the forward-backward Runge-Kutta method and presents the results graphically. The results obtained through optimal control suggest that controls can be useful for minimizing infected individuals and improving population health.

Application of water based drilling clay-nanoparticles in heat transfer of fractional Maxwell fluid over an infinite flat surface.

In the present paper, unsteady free convection flow of Maxwell fluid containing clay-nanoparticles is investigated. These particles are hanging in water, engine oil and kerosene. The values for nanofluids based on the Maxwell-Garnett and Brinkman models for effective thermal conductivity and viscosity are calculated numerically. The integer order governing equations are being extended to the novel non-integer order fractional derivative. Analytical solutions of temperature and velocity for Maxwell fluid are build using Laplace transform technique and expressed in such a way that they clearly satisfied the boundary conditions. To see the impact of different flow parameters on the velocity, we have drawn some graphs. As a result, we have seen that the fractional model is superior in narrate the decay property of field variables. Some limiting solutions are obtained and compared with the latest existing literature. Moreover, significant results can be observed for clay nanoparticles with different base fluids.

Automated image classification of chest X-rays of COVID-19 using deep transfer learning.

INTRODUCTION: In December 2019, the city of Wuhan, located in the Hubei province of China became the epicentre of an outbreak of a pandemic called COVID-19 by the World Health Organisation. The detection of this virus by rRTPCR (Real-Time Reverse Transcription-Polymerase Chain Reaction) tests reported high false negative rate. The manifestations of CXR (Chest X-Ray) images contained salient features of the virus. The objective of this paper is to establish the application of an early automated screening model that uses low computational power coupled with raw radiology images to assist the physicians and radiologists in the early detection and isolation of potential positive COVID-19 patients, to stop the rapid spread of the virus in vulnerable countries with limited hospital capacities and low doctor to patient ratio in order to prevent the escalating death rates. MATERIALS AND METHODS: Our database consists of 447 and 447 CXR images of COVID-19 and Nofindings respectively, a total of 894 CXR images. They were then divided into 4 parts namely training, validation, testing and local/Aligarh dataset. The 4th (local/Aligarh) folder of the dataset was created to retest the diagnostics efficacy of our model on a developing nation such as India (Images from J.N.M.C., Aligarh, Uttar Pradesh, India). We used an Artificial Intelligence technique called CNN (Convolutional Neural Network). The architecture based on CNN used was MobileNet. MobileNet makes it faster than the ordinary convolutional model, while substantially decreasing the computational cost. RESULTS: The experimental results of our model show an accuracy of 96.33%. The F1-score is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The false negative (FN) value, for the validation dataset is 6 (Fig. 3.6), for the testing dataset is 0 (Fig. 3.7) and that for the local/Aligarh dataset is 2 . The recall/sensitivity of the classifier is 93% and 96% for the 1st testing and 2nd testing (local/Aligarh) datasets (Tables 3.3 and 3.4). The recall/sensitivity for the detection of specifically COVID-19 (+) for the testing dataset is 88% and for the locally acquired dataset from India is 100%. The False Negative Rate (FNR) is 12% for the testing dataset and 0% for the locally acquired dataset (local/Aligarh). The execution time for the model to predict the input images and classify them is less than 0.1 s. DISCUSSION AND CONCLUSION: The false negative rate is much lower than the standard rRT-PCR tests and even 0% on the locally acquired dataset. This suggests that the established model with end-to-end structure and deep learning technique can be employed to assist radiologists in validating their initial screenings of Chest X-Ray images of COVID-19 in developed and developing nations. Further research is needed to test the model to make it more robust, employ it on multiclass classification and also try sensitise it to identify new strains of COVID-19. This model might help cultivate tele-radiology.

Multiple slips impact in the MHD hybrid nanofluid flow with Cattaneo-Christov heat flux and autocatalytic chemical reaction.

The present study deliberates the nanofluid flow containing multi and single-walled carbon nanotubes submerged into Ethylene glycol in a Darcy-Forchheimer permeable media over a stretching cylinder with multiple slips. The innovation of the envisaged mathematical model is enriched by considering the impacts of non-uniform source/sink and modified Fourier law in the energy equation and autocatalytic chemical reaction in the concentration equation. Entropy optimization analysis of the mathematical model is also performed in the present problem. Pertinent transformations procedure is implemented for the conversion of the non-linear system to the ordinary differential equations. The succor of the Shooting technique combined with the bvp4c MATLAB software is utilized for the solution of a highly nonlinear system of equations. The impacts of the leading parameters versus engaged fields are inspected through graphical sketches. The outcomes show that a strong magnetic field strengthens the temperature profile and decays the velocity profile. Also, the fluid velocity is lessened for growing estimates of the parameter of slip. Additionally, it is detected that entropy number augmented for higher thermal relaxation parameter and Reynolds number. To substantiate the existing mathematical model, a comparison table is also added. An excellent correlation is achieved here.

Impact of autocatalytic chemical reaction in an Ostwald-de-Waele nanofluid flow past a rotating disk with heterogeneous catalysis.

The nanofluids owing to their alluring attributes like enhanced thermal conductivity and better heat transfer characteristics have a vast variety of applications ranging from space technology to nuclear reactors etc. The present study highlights the Ostwald-de-Waele nanofluid flow past a rotating disk of variable thickness in a porous medium with a melting heat transfer phenomenon. The surface catalyzed reaction is added to the homogeneous-heterogeneous reaction that triggers the rate of the chemical reaction. The added feature of the variable thermal conductivity and the viscosity instead of their constant values also boosts the novelty of the undertaken problem. The modeled problem is erected in the form of a system of partial differential equations. Engaging similarity transformation, the set of ordinary differential equations are obtained. The coupled equations are numerically solved by using the bvp4c built-in MATLAB function. The drag coefficient and Nusselt number are plotted for arising parameters. The results revealed that increasing surface catalyzed parameter causes a decline in thermal profile more efficiently. Further, the power-law index is more influential than the variable thickness disk index. The numerical results show that variations in dimensionless thickness coefficient do not make any effect. However, increasing power-law index causing an upsurge in radial, axial, tangential, velocities, and thermal profile.

Primary malignant melanoma of the esophagogastric junction: A case report.

RATIONALE: Most gastrointestinal melanomas are metastatic from an oculocutaneous primary lesion; however, primary gastrointestinal melanomas have been found in all levels of the gastrointestinal tract. We present the case of Primary malignant melanoma of the esophagus and discuss the diagnostic methods, differentiation from metastatic lesions and treatment options. PATIENT CONCERNS: A 78-year-old male patient presented with fresh blood vomiting and tarry stools for 1 day. DIAGNOSES: Esophagogastroduodenoscopy of this patient revealed a tumor ∼4 cm in size at the cardia side of the esophagogastric junction with dark-red and gray pigmentation. Immunohistochemical stains of the biopsy specimens were positive for S-100 and HMB-45, which are specific markers of melanoma. INTERVENTIONS: Laparotomy with proximal gastrectomy was performed by the surgeon. Histological examination of the surgical specimen revealed the tumor arose from the distal esophagus with invasion of the proximal stomach. Primary malignant melanoma of the esophagus was diagnosed after a full skin and ophthalmic examination and positron emission tomography, which revealed no lesions elsewhere in the body. OUTCOMES: No tumor recurrence was noted at the 1-year follow-up. LESSONS: Primary malignant melanoma of the esophagus is an extremely rare but highly aggressive tumor. The special pattern of pigmentation should be recognized while performing endoscopy. Early detection and radical resection of the tumor are critical to ensure favorable outcomes.

Assessment of economic, thermal and hydraulic performances a corrugated helical heat exchanger filled with non-Newtonian nanofluid.

Improved heat transfer efficiency with considering economic analysis in heating systems is an interesting topic for researchers and scientists in recent years. This research investigates the heat transfer rate (HTR) and flow of non-Newtonian water-Carboxyl methyl cellulose (CMC) based Al2O3 nanofluid in a helical heat exchanger equipped with common and novel turbulators using two-phase model. The requirements for dimensions and cost reduction and also energy saving in thermal systems are the main goal of this study. According to gained results usage of corrugated channel in helical heat exchanger has a considerable influence on thermal and hydraulic performance evaluation criteria (THPEC) index of helical heat exchanger and can improve the THPEC index. Thus, Re = 5000 is obtained as an optimum value, in which the maximum THPEC value is achieved. As it is found in this paper, in case of using novel heat exchanger instead of the basic smooth system, the thermal properties (by considering Nusselt number) increases about 210%, the hydraulic performance (friction factor) reduces about 28%, performance evaluation criteria index increases about 57% and the material consumption (in case of similar THPEC) decreases about 31%. In another word, with considering economic analysis for the basic and novel system which has same efficiencies, the novel one has lower length and consequently 31% lower material.

Heatline visualization of MHD natural convection heat transfer of nanofluid in a prismatic enclosure.

Temperature transfer by virtue of natural convection for visualizing heat transport characteristics through heatline method within a prismatic cavity filled with Cu-H2O nanofluid considering two different temperature boundary conditions is performed numerically. Two top inclined walls are warmed-up at low temperature whilst the bottom wall is heated two different heated conditions such as uniform temperature condition and linear temperature condition. Two vertical walls are insulated. Finite element technique of Galerkin weighted residual form is employed for solving nonlinear partial differential equations for numerical calculation. Heatlines, isotherm contours, streamline contours, and Nusselt number are employed for displaying numerical simulated results for the model parameters entitled nanoparticles volume fraction, Hartmann number and Rayleigh number. The outcomes indicate that heat transfer rate has a significant impact on thermal boundary condition and shape of the nanoparticles. The temperature transfer value enhances significantly for higher Rayleigh number as well as nanoparticles volume fraction. Hartmann number has a positive impact on fluid flow and temperature transport. The characteristics of heat transport using heatlines method are also performed for predicting the better energy transform compared to isotherm contours. In addition, different types of nanofluids are also employed to examine the best heat transport performance.

A novel fractional mathematical model of COVID-19 epidemic considering quarantine and latent time.

In this paper, we investigate the fractional epidemic mathematical model and dynamics of COVID-19. The Wuhan city of China is considered as the origin of the corona virus. The novel corona virus is continuously spread its range of effectiveness in nearly all corners of the world. Here we analyze that under what parameters and conditions it is possible to slow the speed of spreading of corona virus. We formulate a transmission dynamical model where it is assumed that some portion of the people generates the infections, which is affected by the quarantine and latent time. We study the effect of various parameters of corona virus through the fractional mathematical model. The Laguerre collocation technique is used to deal with the concerned mathematical model numerically. In order to deal with the dynamics of the novel corona virus we collect the experimental data from 15th-21st April, 2020 of Maharashtra state, India. We analyze the effect of various parameters on the numerical solutions by graphical comparison for fractional order as well as integer order. The pictorial presentation of the variation of different parameters used in model are depicted for upper and lower solution both.

Nonlinear radiative Maxwell nanofluid flow in a Darcy-Forchheimer permeable media over a stretching cylinder with chemical reaction and bioconvection.

Studies accentuating nanomaterials suspensions and flow traits in the view of their applications are the focus of the present study. Especially, the usage of such materials in biomedical rheological models has achieved great importance. The nanofluids' role is essential in the cooling of small electronic gizmos like microchips and akin devices. Having such exciting and practical applications of nanofluids our goal is to scrutinize the Maxwell MHD nanofluid flow over an extended cylinder with nonlinear thermal radiation amalgamated with chemical reaction in a Darcy-Forchheimer spongy media. The presence of gyrotactic microorganisms is engaged to stabilize the nanoparticles in the fluid. The partial slip condition is considered at the boundary of the stretching cylinder. The Buongiorno nanofluid model is betrothed with impacts of the Brownian motion and thermophoresis. The analysis of entropy generation is also added to the problem. The highly nonlinear system is tackled numerically is addressed by the bvp4c built-in function of the MATLAB procedure. The outcomes of the prominent parameters versus embroiled profiles are portrayed and conversed deeming their physical significance. It is perceived that fluid temperature is augmented for large estimates of the radiation and Darcy parameters. Moreover, it is noticed that the magnetic and wall roughness parameters lower the fluid velocity. To corroborate the presented results, a comparison of the current study with a previously published paper is also executed. An outstanding correlation in this regard is attained.

Analyzing the impact of induced magnetic flux and Fourier's and Fick's theories on the Carreau-Yasuda nanofluid flow.

The current study analyzes the effects of modified Fourier and Fick's theories on the Carreau-Yasuda nanofluid flow over a stretched surface accompanying activation energy with binary chemical reaction. Mechanism of heat transfer is observed in the occurrence of heat source/sink and Newtonian heating. The induced magnetic field is incorporated to boost the electric conductivity of nanofluid. The formulation of the model consists of nonlinear coupled partial differential equations that are transmuted into coupled ordinary differential equations with high nonlinearity by applying boundary layer approximation. The numerical solution of this coupled system is carried out by implementing the MATLAB solver bvp4c package. Also, to verify the accuracy of the numerical scheme grid-free analysis for the Nusselt number is presented. The influence of different parameters, for example, reciprocal magnetic Prandtl number, stretching ratio parameter, Brownian motion, thermophoresis, and Schmidt number on the physical quantities like velocity, temperature distribution, and concentration distribution are addressed with graphs. The Skin friction coefficient and local Nusselt number for different parameters are estimated through Tables. The analysis shows that the concentration of nanoparticles increases on increasing the chemical reaction with activation energy and also Brownian motion efficiency and thermophoresis parameter increases the nanoparticle concentration. Opposite behavior of velocity profile and the Skin friction coefficient is observed for increasing the stretching ratio parameter. In order to validate the present results, a comparison with previously published results is presented. Also, Factors of thermal and solutal relaxation time effectively contribute to optimizing the process of stretchable surface chilling, which is important in many industrial applications.