Optimized solar desalination: integrating nanofluids, TiO2-coated basins, and neural network prediction

Abstract

With increasing global water scarcity, sustainable desalination technologies are becoming essential. This study presents an improved solar still that operates entirely without electricity, offering a low-cost and environmentally friendly solution for freshwater production in remote or off-grid areas. Performance was enhanced by incorporating Al2O3/water nanofluid, a TiO2-coated absorber reservoir, copper fins for improved heat transfer, and a passive solar preheater. These modifications led to a 58 % increase in water yield compared to a conventional solar still (SSU), with a total cost of US$164.65. The levelized cost of water (LCOW) was estimated at US$0.05 per liter, proving more cost-effective than traditional basin stills and reverse osmosis units. Environmental analysis showed that for every unit of emission generated, over 800 were mitigated, with total reductions of 5.96 t (CO2), 35.80 t (SO2), and 137.23 t (NO), due to the exclusive use of solar energy. A predictive artificial neural network (ANN) model was also developed using environmental inputs, achieving high accuracy (R2 = 0.9948). Variable importance was evaluated through the Garson algorithm, supporting further optimization of the system. Overall, the proposed design offers a replicable, economical, and sustainable solution for decentralized desalination, contributing to SDGs 6, 7, 12, and 13. © 2025 International Solar Energy Society