AI-Driven Optimization of Pulsed DC Sputtering for Enhanced Indium Tin Oxide Films
DOI:
https://doi.org/10.33050/italic.v4i1.931Keywords:
Indium Tin Oxide, Pulsed DC Magnetron Sputtering, Transparent Conductive Oxides, Heterojunction Silicon Solar Cells, Oxygen Partial PressureAbstract
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.
References
Y. Zheng, H. Xu, Z. Li, L. Li, Y. Yu, P. Jiang, Y. Shi, J. Zhang, Y. Huang, Q. Luo et al., “Artificial intelligence-driven approaches in semiconductor research,” Advanced Materials, p. 2504378, 2025.
M. Murod, S. Anhar, D. Andayani, A. Fitriani, and G. Khanna, “Blockchain based intellectual property management enhancing security and transparency in digital entrepreneurship,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 1, pp. 240–251, 2025.
X. Yang, Y. Shen, L. Zhang, and Y. Li, “Recent advances in the application of magnetron sputtering for lithium metal batteries,” Journal of Materials Chemistry A, vol. 13, no. 39, pp. 33 104–33 135, 2025.
M. R. Anwar and L. D. Sakti, “Integrating artificial intelligence and environmental science for sustainable urban planning,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 5, no. 2, pp. 179–191, 2024.
N. Alfaraj and A. S. Helmy, “Silicon-integrated next-generation plasmonic devices for energy-efficient semiconductor applications,” Advanced Materials Technologies, p. e00389, 2025.
Y. Li, Y. Ding, J. Sun, S. Tan, Y. Li, X. Wang, J. Cai, J. Bai, X. Lv, W. Guo et al., “Design strategies and emerging applications of perovskite-based sensors,” SmartMat, vol. 6, no. 3, p. e70022, 2025.
O. M. Halawa, E. Ahmed, M. M. Abdelrazek, Y. M. Nagy, and O. A. Abdelraouf, “Illuminating the future: Nanophotonics for future green technologies, precision healthcare, and optical computing,” arXiv preprint arXiv:2507.06587, 2025.
L. W. Ming, J. Anderson, F. Hidayat, F. D. Yulian, and N. Septiani, “Ai as a driver of efficiency in waste management and resource recovery,” International Transactions on Artificial Intelligence, vol. 2, no. 2, pp. 128–134, 2024.
G. Yan, H. Tang, Y. Shen, L. Han, and Q. Han, “Ai-generated ammonium ligands for high-efficiency and stable 2d/3d heterojunction perovskite solar cells,” Advanced Materials, p. 2503154, 2025.
A. Kanivia, H. Hilda, A. Adiwijaya, M. F. Fazri, S. Maulana, and M. Hardini, “The impact of information technology support on the use of e-learning systems at university,” International Journal of Cyber and IT Service Management, vol. 4, no. 2, pp. 122–132, 2024.
M. of Energy and R. o. I. Mineral Resources, “Regulation no. 2 of 2024 on rooftop solar power plants connected to the electricity network of public electricity supply business license holders (iuptlu),” Official Gazette of the Republic of Indonesia, 2024, issued 31 January 2024; supersedes MEMR Regulation No. 26/2021. [Online]. Available: https://setkab.go.id/en/
govt-issues-new-rooftop-solar-power-plant-regulation/
A. Maoucha, T. Berghout, F. Djeffal, and H. Ferhati, “Machine learning-assisted investigation of cigs thin-film solar cell degradation using deep learning analysis,” Journal of Physics and Chemistry of Solids, vol. 199, p. 112526, 2025.
D. Robert, F. P. Oganda, A. Sutarman, W. Hidayat, and A. Fitriani, “Machine learning techniques for predicting the success of ai-enabled startups in the digital economy,” CORISINTA, vol. 1, no. 1, pp. 61–69, 2024.
Z. Sun, Q. Kang, J. Li, S. Zhou, L. Fang, X. Xu, S. Wu, Z. Zheng, X. Chen, H. Yan et al., “Evaluating the practical efficiency limit of silicon heterojunction–interdigitated back contact solar cells by creating digital twins of silicon heterojunction solar cells with amorphous silicon and nanocrystalline silicon hole contact layers,” physica status solidi (a), vol. 221, no. 6, p. 2300758, 2024.
A. Williams, C. S. Bangun, and Y. Shino, “The urgency of digital literacy in indonesia on covid-19 pandemic,” Startupreneur Business Digital (SABDA Journal), vol. 1, no. 2, pp. 183–190, 2022.
A. Sumanth, V. Mishra, S. L. Nagendra, M. S. R. Rao, and T. Dixit, “Advancements in p-type wide and ultra-wide bandgap oxide semiconductors for prospective applications,” physica status solidi (RRL) Rapid Research Letters, vol. 19, no. 6, p. 2500017, 2025.
X. Chen, K. Huang, J. Cai, H. Fang, J. Guo, Y. He, Q. Luo, Q. Wang, W. Gao, J. Wang et al., “An artificial memristor synapse by transferring and stacking freestanding single-crystalline srtio3- δ films for neuromorphic computing,” ACS Applied Materials & Interfaces, vol. 17, no. 38, pp. 53 875–53 886, 2025.
D. Hirpara, P. Zala, M. Bhaisare, C. M. Kumar, M. Gupta, M. Kumar, and B. Tripathi, “Investigation of the dependence of fill factor and efficiency on gallium-doped silicon wafer characteristics using unsupervised learning,” Engineering Applications of Artificial Intelligence, vol. 159, p. 111598, 2025.
U. Rahardja, Q. Aini, A. S. Bist, S. Maulana, and S. Millah, “Examining the interplay of technology readiness and behavioural intentions in health detection safe entry station,” JDM (Jurnal Dinamika Manajemen), vol. 15, no. 1, pp. 125–143, 2024.
S. Hosseini and A. Purohith, “Ai-driven photon management: Enhancing efficiency in multi-junction solar cells,” Available at SSRN 5124619, 2024.
T. Hidayat, D. Manongga, Y. Nataliani, S. Wijono, S. Y. Prasetyo, E. Maria, U. Raharja, I. Sembiring et al., “Performance prediction using cross validation (gridsearchcv) for stunting prevalence,” in 2024 IEEE International Conference on Artificial Intelligence and Mechatronics Systems (AIMS). IEEE, 2024, pp. 1–6.
K. K. Dhillon, M. Patyal, S. Bhogal, and N. Gupta, “A review on advanced counter electrode materials for high-efficiency dye sensitized solar cells,” Journal of Coordination Chemistry, vol. 77, no. 17-19, pp. 1933–1968, 2024.
N. Nuryani, A. B. Mutiara, I. M. Wiryana, D. Purnamasari, and S. N. W. Putra, “Artificial intelligence model for detecting tax evasion involving complex network schemes,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 3, pp. 339–356, 2024.
R. R. Kumar and D. Punetha, “Noble metal-based hybrid nanogenerators for sustainable energy and optoelectronic innovation,” in Advanced Optical Sensors: Noble Metal-Based Hybrid Composites. Springer,2025, pp. 99–133.
M. Nur Aida, M. Q. Khokhar, H. Yousuf, M. Chu, J. Bae, R. Ur Rahman, J. A. Jony, S. Park, and J. Yi, “A comparative study of silicon heterojunction solar cells utilizing a double-layer anti-reflection coating on the front side,” physica status solidi (a), vol. 222, no. 7, p. 2400651, 2025.
A. Juan-Arturo, A. Leonel Mendoza-Mart´ınez, G. Morales-Luna, and M. Morales-Luna, “Exploring the optical properties of molybdenum trioxide: approach of theory modeling and depositions techniques,” Advances in Physics: X, vol. 10, no. 1, p. 2451687, 2025.
T. Mariyanti, I. Wijaya, C. Lukita, S. Setiawan, and E. Fletcher, “Ethical framework for artificial intelligence and urban sustainability,” Blockchain Frontier Technology, vol. 4, no. 2, pp. 98–108, 2025.
K. Saputra, N. D. Khuzaima, M. Melani, W. Wahyudin, and A. O. Madani, “A scoping review of potential biomaterials as optimal platforms for triboelectric nanogenerators,” Narra X, vol. 3, no. 2, pp. e214–e214, 2025.
Q. Aini, P. Purwanti, R. N. Muti, E. Fletcher et al., “Developing sustainable technology through ethical ai governance models in business environments,” ADI Journal on Recent Innovation, vol. 6, no. 2, pp. 145–156, 2025.
A. Nyabadza, S. Chatterjee, S. Ryan, J. I. M. Santos, V. Nicolosi, D. Brabazon, and M. Vazquez, “Machine learning-guided inkjet printing of tin oxide nanoparticle inks on laser-textured copper foils for high performance sodium-ion battery anodes,” Results in Engineering, p. 106338, 2025.
L. S. Lutfiani, A. Birgithri, and Z. Queen, “Technological aspects in the era of digital transformationleading to the adoption of big data,” Startupreneur Business Digital (SABDA Journal), vol. 3, no. 1, pp. 43–53, 2024.
R. Aprianto, E. P. Lestari, E. Fletcher et al., “Harnessing artificial intelligence in higher education: Balancing innovation and ethical challenges,” International Transactions on Education Technology (ITEE), vol. 3, no. 1, pp. 84–93, 2024.
R. Royani, S. D. Maulina, S. Sugiyono, R. W. Anugrah, and B. Callula, “Recent developments in health care through machine learning and artificial intelligence,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 6, no. 1, pp. 86–94, 2024.
Y. Liu, K. Lee, H. Liu, C. Li, X. Zeng, R. Liu, Y. Chen, Z. Chen, J. Yang, X. Huan et al., “Universal 3d-printing of suspended metal oxide nanowire arrays on mems for ai-optimized combinatorial gas fingerprinting,” Advanced Science, p. e11794, 2025.
T. S. Goh, D. Jonas, B. Tjahjono, V. Agarwal, and M. Abbas, “Impact of ai on air quality monitoring systems: A structural equation modeling approach using utaut,” Sundara Advanced Research on Artificial Intelligence, vol. 1, no. 1, pp. 9–19, 2025.
W. G. Mengesha, “Ai-driven design of multifunctional nanomaterials in revolutionizing high-temperature, high-power solutions for space technology: potentials, challenges and perspectives,” Discover Nano, vol. 20, no. 1, p. 220, 2025.
M. H. R. Chakim, A. Kho, N. P. L. Santoso, and H. Agustian, “Quality factors of intention to use in artificial intelligence-based aiku applications,” ADI Journal on Recent Innovation, vol. 5, no. 1, pp. 72–85, 2023.
A. Sutarman, J. Williams, D. Wilson, and F. B. Ismail, “A model-driven approach to developing scalable educational software for adaptive learning environments,” International Transactions on Education Technology (ITEE), vol. 3, no. 1, pp. 9–16, 2024.
Y. Zhang, T. Shi, L. Duan, B. Hoex, and Z. Tang, “Progress in passivating selective contacts for heterojunction silicon solar cells,” Nano Energy, vol. 131, p. 110282, 2024.
X. Ru, M. Yang, S. Yin, Y. Wang, C. Hong, F. Peng, Y. Yuan, C. Sun, C. Xue, M. Qu et al., “Silicon heterojunction solar cells achieving 26.6% efficiency on commercial-size p-type silicon wafer,” Joule, vol. 8, no. 4, pp. 1092–1104, 2024.
Z. Rhaim, F. Echouchene, S. Habli, M. H. Gazzah, M. A. Albedah, and H. Belmabrouk, “Optimization of monocrystalline silicon solar cell using box–behnken design and machine learning models,” The European Physical Journal Plus, vol. 139, no. 10, p. 916, 2024.
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