The Organic Rankine Cycle (ORC) is an electricity generation system that uses organic fluid instead of water in the low temperature range. The Organic Rankine cycle using zeotropic working fluids has wide application potential. In this study, data mining (DM) model is used for performance analysis of organic Rankine cycle (ORC) using zeotropik working fluids R417A and R422D. Various DM models, including Linear Regression (LR), Multi-Layer Perceptron (MLP), M5 Rules, M5 Model Tree, Random Committee (RC), and Decision Tree (DT) models are used. The MLP model emerged as the most effective approach for predicting the thermal efficiency of both R417A and R422D. The MLP’s predicted results closely matched the actual results obtained from the thermodynamic model using Genetron software. The Root Mean Square Error (RMSE) for the thermal efficiency was exceptionally low, at 0.0002 for R417A and 0.0003 for R422D. Additionally, the R-squared (R²) values for thermal efficiency were very high, reaching 0.9999 for R417A and R422D. The findings demonstrate the effectiveness of the DM model for complex tasks like estimating ORC thermal efficiency. This approach empowers engineers with the ability to predict thermal efficiency in organic Rankine systems with high accuracy, speed, and ease.

An investigation is conducted into how radiation affects the non-Newtonian second-grade fluid in double-diffusive convection over a stretching sheet. When fluid is flowing through a porous material, the Lorentz force and viscous dissipation are also taken into account. The flow equations are coupled partial differential equations that can be solved by MATLAB’s built-in bvp4c algorithm after being transformed into ODEs using appropriate similarity transformations. Utilizing graphs and tables, the impact of a flow parameter on a fluid is displayed. On velocity, temperature, and concentration profiles, the effects of the magnetic field, Eckert number, and Schmidt number have been visually represented. Calculate their inaccuracy by comparing the Nusselt number and Sherwood number values to those from earlier investigations.

Recent research efforts have increasingly concentrated on creating innovative biomaterials to improve bone tissue engineering techniques. Among these, hybrid nanomaterials stand out as a promising category of biomaterials. In this study, we present a straightforward, cost-efficient, and optimized hydrothermal synthesis method to produce high-purity Ta-doped potassium titanate nanofibers. Morphological characterizations revealed that Ta-doping maintained the native crystal structure of potassium titanate, highlighting its exciting potential in bone tissue engineering.

Broad-spectrum antibiotics, such as tetracyclines, are used to treat and manage a range of infectious disorders. Since the kidneys are the primary organs responsible for excreting tetracyclines, clinicians should refrain from prescribing them to patients who have renal failure. Tetracyclines are one of the clinical waste products of today. One of the biggest problems in the field of pollution of the environment today is the persistence of different pharmaceutical residues, drug residues, pesticides, and metal ion species of the new-generation pollutants in surfaces and groundwater. In the present work, carboxymethyl cellulose (CMC)-CuO nanoparticles (CMC-CuO NPs) were synthesized using CuO NPs within different amounts of CMC (0.5, 1.0, 1.5 and 2.0 g) at 85 °C. The synthesized nanoparticles were characterized by XRD, FT IR, SEM, and TG-DTA analysis. According to XRD and SEM, the crystallize size and morphology influenced the dosage of CMC. FT-IR analysis confines the layer of CMC to the CuO nanoparticle surface. TG-DTA results indicated that the CMC content of CMC-CuO NPs was between the range of 69% and 75% by weight. The effects of some parameters such as initial concentration, pH, adsorbent dosage, and contact time on the adsorption of tetracycline from aqueous model solutions on CMC-CuO NPs were investigated with batch studies. It was found that the removal of tetracycline was obtained about 80% with optimized parameters of 10 mg/L concentration, 180 min contact time, 5 pH, and 0.3 g/25 mL dose. The synthesized CMC-CuO NPs nanocomposite may be a promising material for the removal of tetracycline in environmental pollution and toxicology.

The work is devoted to the numerical solution of the initial boundary value problem for the heat equation with a fractional Riesz derivative. Explicit and implicit difference schemes are constructed that approximate the boundary value problem for the heat equation with a fractional Riesz derivative with respect to the coordinate. In the case of an explicit difference scheme, a condition is obtained for the time step at which the difference scheme converges. For an implicit difference scheme, a theorem on unconditional convergence is proved. An example of a numerical calculation using an implicit difference scheme is given. It has been established that when passing to a fractional derivative, the process of heat propagation slows down.