Global warming is a thermodynamic problem. When excess heat is added to the climate system, the land warms more quickly than the oceans due to the land’s reduced heat capacity. The oceans have a greater heat capacity because of their higher specific heat and the heat mixing in the upper layer of the ocean. Thermodynamic Geoengineering (TG) is a global cooling method that, when deployed at scale, would generate 1.6 times the world’s current supply of primary energy and remove carbon dioxide (CO₂) from the atmosphere. The cooling would mirror the ostensible 2008–2013 global warming hiatus. At scale, 31,000 1-gigawatt (GW) ocean thermal energy conversion (OTEC) plants are estimated to be able to: a) displace about 0.8 watts per square meter (W/m²) of average global surface heat from the surface of the ocean to deep water that could be recycled in 226-year cycles, b) produce 31 terawatts (TW) (relative to 2019 global use of 19.2 TW); c) absorb about 4.3 Gt CO₂ per year from the atmosphere by cooling the surface. The estimated cost of these plants is $2.1 trillion per year, or 30 years to ramp up to 31,000 plants, which are replaced as needed thereafter. For example, the cost of world oil consumption in 2019 was $2.3 trillion for 11.6 TW. The cost of the energy generated is estimated at $0.008/KWh.

Paraffin wax is the most common phase change material (PCM) that has been broadly studied, leading to a reliable optimal for thermal energy storage in solar energy applications. The main advantages of paraffin are its high latent heat of fusion and low melting point that appropriate solar thermal energy application. In addition to its accessibility, ease of use, and ability to be stored at room temperature for extended periods of time, Nevertheless, improving its low thermal conductivity is still a big, noticeable challenge in recently published work. In this work, the effect of adding nano-Cu₂O, nano-Al₂O₃ and hybrid nano-Cu₂O-Al₂O₃ (1:1) at different mass concentrations (1, 3, and 5 wt%) on the thermal characteristics of paraffin wax is investigated. The measured results showed that the peak values of thermal conductivity and diffusivity are achieved at a wight concentration of 3% when nano-Cu₂O and nano-Al₂O₃ are added to paraffin wax with significant superiority for nano-Cu₂O. While both of those thermal properties are negatively affected by increasing the concentration beyond this value. The results also showed the excellence of the proposed hybrid nanoparticles compared to nano-Cu₂O and nano-Al₂O₃ as they achieve the highest values of thermal conductivity and diffusivity at a weight concentration of 5.0 wt%.

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.