Ammar H. Elsheikh

TL;DR: An attempt has been made to scrutinize the applications of artificial neural network (ANN) as an intelligent system-based method for optimizing and the prediction of different solar energy devices’ performance.

TL;DR: In this article, the authors investigated the recent advances in the nanofluids' applications in solar energy systems, i.e., solar collectors, photovoltaic/thermal (PV/T) systems, solar thermoelectric devices, solar water heaters, solar-geothermal combined cooling heating and power system (CCHP), evaporative cooling for greenhouses, and water desalination.

TL;DR: In this article, the use of graphite and copper oxide micro-flakes with different concentrations, different basin water depths, and different film cooling flow rates is experimentally investigated in an attempt to improve the performance of solar still.

TL;DR: In this article, a review of thin film-based solar steam generation (SG) devices with respect to their physical mechanisms, fabrication methods, structure, advantages, and disadvantages is presented.

TL;DR: A new productivity prediction model of active solar still was developed depending on improving the performance of the traditional artificial neural networks using Harris Hawks Optimizer, which had the best accuracy in predicting the solar still yield compared with the real experimental results.