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

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.