Optimization of photoanode on dye-sensitized solar cell structure using k-nearest neighbor method

Abstract Dye-sensitized solar cells (DSSC) have recently gained significant attention in a number of markets and are recognized as better option for energy generation than conventional ones, providing clean, sustainable, renewable green energy. Several studies focused on photoanode optimization using machine learning. Photoanode produces performance results the form Voc Isc, which then used model training validation data. The highest predictive were obtained A3+A2 (TiO 2 18NR-T TiO R/SP). layers combinations prepared according to performed was carried out with an efficiency 2.630%.