Comprehensive Assessment of Perovskite Solar Cell Efficiency Through Holistic Edge Detection Analysis of Crystallographic Grain Size

Abstract

Perovskite solar cells (PSCs) offer substantial potential to achieve remarkable energy conversion efficiency. However, the presence of grain boundaries poses a significant challenge, introducing non-radiative recombination pathways that can reduce overall performance. This manuscript presents a comprehensive investigation into the microstructure of PSCs with a focus on grain boundaries. The analysis involves preprocessing scanning electron microscope images to enhance quality, utilizing Holistic Nested Edge Detection for efficient grain boundary identification, followed by grain segmentation and size measurement. The study ensures data diversity by collecting grain size information from numerous scanning electron microscope images, offering automated analysis for consistency and repeatability. Furthermore, this study employs linear regression analysis to quantitatively assess the relationship between grain size and photovoltaic parameters. This leads to the development of a mathematical model that predicts efficiency based on factors such as the Voltage-Current relationship and others.