AI-Driven Optimization of Pulsed DC Sputtering for Enhanced Indium Tin Oxide Films - Hamdan, Hamdan; Cahyadi, Hadi; Vaher, Kristina; Ratih, Arista (International Transactions on Artificial Intelligence, 2025)
The performance of heterojunction silicon solar cells strongly depends on the quality of the Transparent Conductive Oxide (TCO) layer, particularly Indium Tin Oxide (ITO), which governs both lateral charge transport and optical coupling. Despite its industrial relevance, achieving low-resistivity and high transmittance ITO at low thermal budgets remains a manufacturing challenge. This study aims to identify and optimize the key pulsed DC magnetron sputtering parameters that govern the structural, electrical, and optical properties of ultra-thin ITO films suitable for heterojunction applications. A systematic experimental approach was implemented by varying discharge power, oxygen partial pressure, deposition temperature, and post-deposition annealing conditions using an inline industrial sputtering system. The results show that moderate discharge power, controlled oxygen incorporation, and substrate temperatures around 180 ◦C significantly enhance film densification and electron transport. Under the optimized parameter set, the ITO films achieved low resistivity in the range of (4.6–5)×10−4 Ω·cm and visible-light transmittance above 90%, while annealing at 160 ◦C further reduced defect density and stabilized electrical per- formance. These findings demonstrate that high-quality ITO can be produced within the thermal constraints of heterojunction silicon technologies and provide a robust foundation for integration into automated or AI-assisted sputtering control frameworks. Overall, this work supports the development of scalable, energy-efficient, and industrially viable fabrication routes for next-generation photovoltaic devices.