COMPUTATIONAL DESIGN AND PERFORMANCE OPTIMIZATION OF RB₂NAALI₆-BASED DOUBLE PEROVSKITE SOLAR CELLS

Abstract

The increasing demand for efficient, stable, and environmentally sustainable photovoltaic technologies has intensified research into lead-free double perovskite materials for next-generation solar cells. However, optimizing the structural, electronic, and optoelectronic properties of these materials remains a significant challenge. This study investigates the computational design and performance optimization of Rb₂NaAlI₆-based double perovskite solar cells, with particular emphasis on their suitability for high-performance photovoltaic applications. Density functional theory (DFT)-based computational approaches are employed to examine structural stability, electronic band structure, density of states, optical absorption, and photovoltaic characteristics. The analysis focuses on identifying material properties that influence light harvesting, charge generation, carrier transport, and overall solar-cell performance. The computational framework considers structural geometry optimization followed by electronic and optical calculations and device-level optimization. The results indicate that the Rb₂NaAlI₆ composition possesses characteristics that warrant investigation as a lead-free absorber, particularly because iodide-based double perovskites can provide favorable visible-to-near-infrared optical responses. The study further demonstrates that compositional engineering, defect control, interface optimization, and appropriate charge-transport layers are critical for translating favorable bulk properties into practical photovoltaic efficiency. The findings contribute to the computational screening of environmentally preferable double perovskites and provide a theoretical framework for future experimental validation and device fabrication.