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Evolutionary algorithms are a large class of optimization techniques inspired by the ideas of natural selection, and can be employed to address challenging problems. These algorithms iteratively evolve populations using crossover, which combines genetic information from two parent solutions, and mutation, which adds random changes. This iterative process tends to produce effective solutions. Inspired by this, the current study presents the results of thermal variation on the surface of a wetted wavy fin using a genetic algorithm in the context of parameter estimation for artificial neural network models. The physical features of convective and radiative heat transfer during wet surface conditions are also considered to develop the model. The highly nonlinear governing ordinary differential equation of the proposed fin problem is transmuted into a dimensionless equation. The graphical outcomes of the aspects of the thermal profile are demonstrated for specific non-dimensional variables. The primary observation of the current study is a decrease in temperature profile with a rise in wet parameters and convective-conductive parameters. The implemented genetic algorithm offers a powerful optimization technique that can effectively tune the parameters of the artificial neural network, leading to an enhanced predictive accuracy and convergence with the numerically obtained solution. [ABSTRACT FROM AUTHOR]

In many studies published in recent years, corrosion scientists proved that various drug molecules can exhibit high inhibition performance against the corrosion of metal surfaces and alloys. This study presents the adsorption behaviour and inhibition mechanism of Omeprazole and Tinidazole on steel surface in gas phase and aqueous acidic conditions using quantum chemical calculations and molecular dynamics simulations. Well-known quantum chemical parameters such as EHOMO, ELUMO, energy gaps, dipole moment, global hardness, softness, electrophilicity, electrodonating power, electroaccepting power and the fraction of electron transfer, were calculated to understand the corrosion inhibition properties and interactions with the steel surface of the studied molecules. Fukui indices analysis was performed to identify the local reactivities of the molecules. Additionally, Monte Carlo simulations were used to determine the optimal adsorption configuration of the inhibitors onto a Fe (1 1 0) surface. The study's findings provide valuable insights into preventing corrosion of steel surfaces in aqueous acidic environments. The theoretical data obtained was evaluated in terms of Maximum Hardness, Minimum Polarizability and Minimum Electrophilicity Principles. [ABSTRACT FROM AUTHOR]

Single‐phase BiVO4 (BV) powder was synthesized successfully at 600°C within 4 h duration through the mechanochemical high energy ball milling method, and the combined photocatalytic and piezocatalytic activity was studied to exhibit piezo‐photocatalytic efficiency. Monoclinic BV phase existence in the synthesized powder was affirmed through Raman spectroscopy and the X‐ray diffraction techniques. The scanning electron microscopy affirmed the irregular‐shaped BV powder in the synthesized powders. X‐ray photoelectron spectroscopy affirmed the existence of various oxidation states of the elements V, Bi, and O in BV powders. The piezocatalytic and photocatalytic methylene blue (MB) dye degradation efficiency using BV powdered sample was observed to be 28% and 60%, respectively, within 240 min. The piezo‐photocatalytic MB dye degradation using BV powdered sample was observed to be 81% within 240 min. Effect of dye concentration on kinetic rate constant was also studied. [ABSTRACT FROM AUTHOR]

Crystallizationof calcium sulfate dihydrate (CaSO4·2H2O, gypsum) in sodium chloride solutions has been studied inthe presence of magnesium ion. It was shown that Mg2+hasan inhibiting effect on the two stages of precipitation: nucleationand growth. Kinetic results were explained on the basis of the strongeffect of magnesium ions on gypsum solubility. In the studied rangeof the ionic strength (IS), it was found that in the presence of NaClthe solubility increase stops beyond IS = 0.31 mol·L–1whereas it continues to rise in the presence of MgCl2. X-ray diffraction analyses showed that magnesium ions act by substitutingthe calcium ones or by insertion in the defects of the gypsum crystallattice. [ABSTRACT FROM AUTHOR]

The present research focuses on the significance of thermophoretic particle deposition on a ZnO-SAE50 nanolubricant flow in a stretchable/shrinkable convergent/divergent channel in the presence of an applied magnetic field and nonlinear heat radiation. A parameter in the governing differential equations and wall boundary conditions defines the physical mechanism of the model. The Galerkin finite element method, combined with similarity transformation, is adopted to solve the governing equations. The Levenberg-Marquardt backpropagating algorithm of an artificial neural network model forecasts heat and mass transfer properties. The results reveal that by stretching/shrinking the walls enough, the classical flow and heat properties are significantly affected. The stretching of the convergent or divergent channel is observed to increase the velocity profiles, whilst shrinking results in backflow regions. In terms of the temperature field, stretching causes more heat to be produced in the flow; nevertheless, the thermal layer is decreased and cooling is attained by channel shrinkage, which may have important technical implications., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Non-Newtonian fluids have unique heat transfer properties compared to Newtonian fluids. The present study examines the flow of a Maxwell nanofluid across a rotating rough disk under the effect of a magnetic field. Furthermore, the Cattaneo-Christov heat flux model is adopted to explore heat transport features. In addition, a comparison of fluid flow without and with aggregation is performed. Using similarity variables, the governing partial differential equations are transformed into a system of ordinary differential equations, and this system is then solved by employing the Runge-Kutta Fehlberg fourth-fifth order method to obtain the numerical solution. Graphical depictions are used to examine the notable effects of various parameters on velocity and thermal profiles. The results reveal that an increase in the value of Deborah number decreases the velocity profile. An increase in the thermal relaxation time parameter decreases the thermal profile. An artificial neural network is employed to calculate the rate of heat transfer and surface drag force. The R values for skin friction and Nusselt number were computed. The results demonstrate that artificial neural networks accurately predicted skin friction and Nusselt number values., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)