Enhancing photovoltaic efficiency and sustainability: the role of ion beam technology and AI integration

Abstract

Renewable and sustainable energy is in high demand to meet global energy requirements, with photovoltaic systems at the forefront, accounting for 96.2% of global power generation. However, despite their crucial role, photovoltaic systems face efficiency challenges, influenced by various factors and inherent limitations defined by the Shockley–Queisser (SQ) limit, a material-specific constraint. This review highlights how ion beam technology can be employed in fabrication and defect induction to alter the recombination rate, leading to the optimization of transport properties. Furthermore, traditional methods and emerging approaches for re-innovation towards effective fabrication techniques in the semiconductor industry have been explored to improve the manufacturing process. Experimental case studies of silicon solar cell fabrication, SRIM/TRIM simulations, and modifications in transport properties of cells after swift heavy ion (SHI) irradiation and various structural characterization techniques, like X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), etc., are discussed critically. Moreover, for transport and electrical properties, the Hall effect, deep-level transient spectroscopy (DLTS) for defect analysis, and I–V characteristics of implanted and irradiated cells are examined. Hence, for future perspectives, these novel approaches hold the potential to revolutionize fabrication techniques using artificial intelligence-machine learning (AI-ML), driving advancements in efficiency and paving the way for next-generation innovations in semiconductor and photovoltaic systems.