A focused review of ANN-based models for Predicting Absorption Maxima (λmax) of Dyes

The rapidly increasing demand for energy and the consequent depletion of non-renewable energy sources pose significant challenges. Seeking alternatives, renewable sources like solar cells come into focus. Nevertheless, their limited efficiency hinders practical application and motivates researchers to develop more efficient solar cells. Through an examination of effectiveness, design viability, and fabrication costs, Dye-Sensitized Solar Cells (DSSC) emerge as superior to other photovoltaic solar cells. In particular the dye component is crucial for how well the DSSC works as it absorbs light from the sun.The paper investigates the topic related to forecasting the absorption maxima (λmax) of dyes and presents an overview of the proposals in the literature that use neural networks to forecast it. In addition, it discusses the main challenges related to this relevant topic, evidencing the need to address these challenges.