In the present study, deep eutectic solvent (DES) was prepared by combining choline chloride and glycerol and is used as a green alternative extraction media of detrimental organic solvents. The DES and aqueous methanol were used for the ultrasound-assisted extraction (UAE) of bioactive compounds from Mentha arvensis, which have remarkable medicinal values. The optimization of extraction parameters during phytochemical evaluation was done by response surface methodology. The extraction yield obtained with DES was significantly higher than that achieved using aqueous methanol. The total phenolic contents (TPCs) 117 mg GAE/g, total flavonoids contents (TFCs), 80 mg QE/g and 2, 2-diphenyl-1- picrylhydrazyl (DPPH) radical inhibition 94% was obtained using DES. The antimicrobial activities of extracts were evaluated against S. aureus, E. coli (bacterial strains), F. solani and A. niger (fungal strains) by well diffusion method. The extracts were characterized using LC-MS and showed that chrysin, p-coumaric acid, naringenin, scopoletin, phenylpyruvic acid, pinocembrin, hesperidin, carnosic acid and caffeic acid were the main bioactive components of Mentha arvensis. The DES has shown considerable high extraction yield, which ultimately relates to the higher TPCs, TFCs and DPPH assay compared to aqueous methanol. The DES with extensive hydrogen bonding is of vital importance in the perspective of the environment than traditionally used solvents.

This paper studies the roll-coating process of an incompressible viscoelastic fluid, where the roll and the web have equal velocities. The lubrication approximation theory is used to simplify the equations of motion. Solutions for velocity profile, pressure gradient, flow rate per unit width, and shear stress at the roll surface are obtained by using a regular perturbation method. Integrated quantities of engineering interest are also calculated. These include the maximum pressure, separation point, roll/sheet separating force, power transmitted to the fluid by the roll, and coating thickness. It is found that these quantities increase substantially and monotonically as the fluid’s material constant increases.

In this paper, the study of a non-Newtonian material when it is dragged through the narrow region between two co-rotating rolls is carried out. The conservation of mass and momentum equations based on lubrication theory are nondimensionalized and solved for the velocity and pressure fields using the perturbation technique. By considering the influence of the material parameter, the dimensionless leave-off distance in the calendering process is determined. The leave-off distance is expressed in terms of eigen value problem. Quantities of engineering interest like maximum pressure, the roll-separating force, and the power transmitted to the fluid by rolls are calculated. It is observed that the material parameter has great influence on detachment point, velocity, and pressure distribution, which are useful for the calendering process.

This article presents a mathematical model and theoretical analysis of coating of a thin film of non-Newtonian polymers as they travel through a small space between two reverse-rotating rolls. The dimensionless forms of the governing equations are simplified with the help of the lubrication approximation theory (LAT). By using the perturbation technique, the analytical solutions for velocity, flow rate and pressure gradient were obtained. From an engineering point of view, some significant results such as thickness of the coated web, pressure distribution, separation points, separation force and power input were computed numerically. The effect of velocities ratio $k$ and Weissenberg number $We$ on these physical quantities is presented graphically; others are shown in tabular form. It is noted that the involved material parameters provide a mechanism to control the flow rate, pressure distribution, the thickness of coating, separation force and power input. Moreover, the separation point is shifted toward the nip region by increasing velocities ratio $k$.

This article describes the development of a mathematical model of the reverse roll coating of a thin film for an incompressible non-isothermal magnetohydrodynamics $\left(MHD\right)$ viscoplastic fluid as it passes through a small gap between two rolls rotating reversely. The equations of motion required for the fluid added to the web are constructed and simplified using the lubrication approximation theory $\left(LAT\right)$. Analytical results are obtained for the velocity profile, pressure gradient, and temperature distribution. The pressure distributions and flow rate are calculated numerically using the trapezoidal rule and regular false position method, respectively. Some of these results are presented graphically, while others are shown in a tabular form. From the present analysis, it has been observed that the magnitude of pressure distributions increases by increasing the value of the involved parameters. It is worth mentioning that the velocities ratio and Brickman’s number are controlling parameters for the temperature distributions. The results indicate the strong effectiveness of the viscoplastic parameter and velocities ratio for the velocity and pressure distributions. It is also concluded that the coating of Casson material has been remarkably affected by the magnetohydrodynamics effects.

Scientists and researchers widely recognize the effectiveness of artificial intelligence (AI)-based machine learning and intelligent computing solvers, demonstrating qualities such as resilience, robustness, stability, and rapid convergence. One particularly significant and rapidly growing field within AI is artificial neural networks. This research uses a supervised neural network model based on Levenberg–Marquardt backpropagation (LMB-SNNs) to examine the Sisko fluid model for the forward roll coating process (SFM-FRCP). A suitable transformation is applied to the partial differential equations based SFM-FRCP mathematical model, resulting in a set of nonlinear ordinary differential equations. The perturbation method has been used to find the analytical solutions for the velocity profile, pressure gradient, and pressure profile. A dataset for varying the pertinent parameters is generated, and the LMB-SNNs technique has been used to estimate the velocity profile, pressure gradient, and pressure profile behavior during FRCP for numerous scenarios. The numerical solution for SFM-FRCP in different scenarios, such as the validation, training, and testing procedures of LMB-SNNs, is carried out. Moreover, the state transition index, fitness outline, mean square error, histogram error, and regression presentation also endorse the strength and reliability of the solver LMB-SNNs for SFM-FRCP. The comparative analyses and performance studies through outputs of regression drawings, absolute error, and error histograms validate the effectiveness of the suggested solver LMB-SNNs. The method's precision is verified by the closest numerical outputs of both built and dataset values with similar levels 10−11–10−14. Furthermore, it has been observed that as the non-Newtonian parameter increases, the fluid velocity decreases. The research work carried out in this paper is original and fills a gap in the existing research by showing the rheological properties of the Sisko fluid model and the implementation of the LMB-SNNs during the FRCP.