Comparative Evaluation of Al/Chlorophyll Device Under Varying Irradiance Intensity: Machine Learning Modeling Vs. Experimental Data

Abstract

This study investigated the effect of chlorophyll, a natural photosynthetic pigment, on solar cell characteristic parameters. Chlorophyll thin film layers were analyzed using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The current-voltage (I-V) characteristics of an Al/p-Si/chlorophyll/Al structure were investigated to understand the device's behavior under different light intensities. The fill factor (FF) and efficiency values (eta), which are the characteristic parameters of the solar cell, were calculated from the current values predicted by machine learning (ML) models using the voltage values of the Al/p-Si/chlorophyll/Al devices produced and the results obtained were compared. The results demonstrate the light intensity-dependent electrical response of the Al/p-Si/chlorophyll/Al structure and provide valuable insights for further developments in organic photodetectors and solar cell technology.