Group decision-making algorithm with sine trigonometric r,s,t-spherical fuzzy aggregation operators and their application.

r, s, t-spherical fuzzy (r, s, t-SPF) sets provide a robust framework for managing uncertainties in decision-making, surpassing other fuzzy sets in their ability to accommodate diverse uncertainties through the incorporation of flexible parameters r, s, and t. Considering these characteristics, this article explores sine trigonometric laws to enhance the applicability and theoretical foundation for r, s, t-SPF setting. Following these laws, several aggregation operators (AOs) are designed for aggregation of the r, s, t-SPF data. Meanwhile, the desired characteristics and relationships of these operators are studied under sine trigonometric functions. Furthermore, we build a group decision-making algorithm for addressing multiple attribute group decision-making (MAGDM) problems using the developed AOs. To exemplify the applicability of the proposed algorithm, we address a practical example regarding laptop selection. Finally, parameter analysis and a comprehensive comparison with existing operators are conducted to uncover the superiority and validity of the presented AOs.

Utilization of ZnFe2O4-Polyaniline (PANI), ZnFe2O4-Polystyrene (PST), and ZnFe2O4-Polypyrrole (PPy) nanocomposites for removal of Red X-GRL and Direct Sky Blue dyes from wastewater: Equilibrium, kinetic and thermodynamic studies.

In this study, ZnFe2O4-Polyaniline (PANI), ZnFe2O4-Polystyrene (PST), and ZnFe2O4-Polypyrrole (Ppy) nanocomposites were synthesized by the adsorption method and characterized by field emission scanning electron microscopy and Fourier transform infrared spectrometer. Batch adsorption experiments were conducted for removing two types of hazardous dyes Red X-GRL and Direct Sky Blue 51 from an aqueous solution and the effect of pH, adsorbent dosage, contact time, and initial concentration of dyes were investigated. Meanwhile, kinetic, isotherm, and thermodynamic parameters were also determined. The electrolyte and surfactant effect was also tested for the prepared nanocomposites. To test the reusability desorption study was also conducted.

Analysis of Statistically Predicted Rate Constants for Pyrolysis of High-Density Plastic Using R Software.

The surge in plastic waste production has forced researchers to work on practically feasible recovery processes. Pyrolysis is a promising and intriguing option for the recycling of plastic waste. Developing a model that simulates the pyrolysis of high-density polyethylene (HDPE) as the most common polymer is important in determining the impact of operational parameters on system behavior. The type and amount of primary products of pyrolysis, such as oil, gas, and waxes, can be predicted statistically using a multiple linear regression model (MLRM) in R software. To the best of our knowledge, the statistical estimation of kinetic rate constants for pyrolysis of high-density plastic through MLRM analysis using R software has never been reported in the literature. In this study, the temperature-dependent rate constants were fixed experimentally at 420 °C. The rate constants with differences of 0.02, 0.03, and 0.04 from empirically set values were analyzed for pyrolysis of HDPE using MLRM in R software. The added variable plots, scatter plots, and 3D plots demonstrated a good correlation between the dependent and predictor variables. The possible changes in the final products were also analyzed by applying a second-order differential equation solver (SODES) in MATLAB version R2020a. The outcomes of experimentally fixed-rate constants revealed an oil yield of 73% to 74%. The oil yield increased to 78% with a difference of 0.03 from the experimentally fixed rate constants, but light wax, heavy wax, and carbon black decreased. The increased oil and gas yield with reduced byproducts verifies the high significance of the conducted statistical analysis. The statistically predicted kinetic rate constants can be used to enhance the oil yield at an industrial scale.

Non-Thermal Plasma Reduction of Ag+ Ions into Silver Nanoparticles in Open Atmosphere under Statistically Optimized Conditions for Biological and Photocatalytic Applications.

An environmentally friendly non-thermal DC plasma reduction route was adopted to reduce Ag+ ions at the plasma−liquid interface into silver nanoparticles (AgNPs) under statistically optimized conditions for biological and photocatalytic applications. The efficiency and reactivity of AgNPs were improved by statistically optimizing the reaction parameters with a Box−Behnken Design (BBD). The size of the AgNPs was chosen as a statistical response parameter, while the concentration of the stabilizer, the concentration of the silver salt, and the plasma reaction time were chosen as independent factors. The optimized parameters for the plasma production of AgNPs were estimated using a response surface methodology and a significant model p < 0.05. The AgNPs, prepared under optimized conditions, were characterized and then tested for their antibacterial, antioxidant, and photocatalytic potentials. The optimal conditions for these three activities were 3 mM of stabilizing agent, 5 mM of AgNO3, and 30 min of reaction time. Having particles size of 19 to 37 nm under optimized conditions, the AgNPs revealed a 82.3% degradation of methyl orange dye under UV light irradiation. The antibacterial response of the optimized AgNPs against S. aureus and E. coli strains revealed inhabitation zones of 15 mm and 12 mm, respectively, which demonstrate an antioxidant activity of 81.2%.

Crank Nicholson scheme to examine the fractional-order unsteady nanofluid flow of free convection of viscous fluids.

Fractional fluid models are usually difficult to solve analytically due to complicated mathematical calculations. This difficulty in considering fractional model further increases when one considers nth order chemical reaction. Therefore, in this work an incompressible nanofluid flow as well as the benefits of free convection across an isothermal vertical sheet is examined numerically. An nth order chemical reaction is considered in the chemical species model. The specified velocity (wall's) is time-based, and its motion is translational into mathematical form. The fractional differential equations are used to express the governing flow equations (FDEs). The non-dimensional controlling system is given appropriate transformations. A Crank Nicholson method is used to find solutions for temperature, solute concentration, and velocity. Variation in concentration, velocity, and temperature profiles is produced as a result of changes in discussed parameters for both Ag-based and Cu-based nanofluid values. Water is taken as base fluid. The fractional-order time evaluation has opened the new gateways to study the problem into a new direction and it also increased the choices due to the extended version. It records the hidden figures of the problem between the defined domain of the time evaluation. The suggested technique has good accuracy, dependability, effectiveness and it also cover the better physics of the problem specially with concepts of fractional calculus.

Vibration frequency analysis of three-layered cylinder shaped shell with effect of FGM central layer thickness.

In this research, vibration frequency analysis of three layered functionally graded material (FGM) cylinder-shaped shell is studied with FGM central layer and the internal and external layers are of homogenous material. Strain and curvature-displacement relations are taken from Sander's shell theory. The shell frequency equation is obtained by employing the Rayleigh Ritz method. Influence on natural frequencies (NFs) is observed for various thickness of the middle layer. The characteristics beam functions are used to estimate the dependence of axial modal. Results are obtained for thickness to radius ratios and length to radius ratios for different edge conditions. The validity of this method is checked for numerous results in the open literature.