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<p>The pursuit of non-toxic and sustainable photovoltaic materials has driven growing interest in double perovskite halides as promising alternatives to conventional lead-based absorbers. In this study, a comprehensive design, simulation, and machine learning (ML)-based optimization of lead-free K<sub>2</sub>AMoI<sub>6</sub> (A = Na, Rb) perovskite solar cells has been presented. The impact of A-site cation substitution on structural and optoelectronic properties was systematically analyzed to elucidate its influence on device performance. The Na-based perovskite (K<sub>2</sub>NaMoI<sub>6</sub>) exhibits a relatively wider bandgap and superior open-circuit voltage, whereas the Rb-based analogue (K<sub>2</sub>RbMoI<sub>6</sub>) shows improved carrier mobility attributed to enhanced orbital interactions. Device simulations conducted in SCAPS-1D optimized absorber thickness, defect density, and doping concentration for both configurations. Experimental validation revealed that K<sub>2</sub>NaMoI<sub>6</sub> achieved a higher power conversion efficiency (21.6%) compared to K<sub>2</sub>RbMoI<sub>6</sub> (11.6%), demonstrating its superior photovoltaic potential. Additionally, the ML regression model effectively predicted device performance with an accuracy of 89.35% and 88.47% for Na- and Rb-based systems, respectively, confirming the robustness of the computational approach. Overall, these results highlight K<sub>2</sub>NaMoI<sub>6</sub> as a stable, lead-free double perovskite absorber with promising efficiency and scalability for next-generation environmentally sustainable solar cells.</p>

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Design and optimization of K2AMoI6 (A = Rb, Na) lead-free perovskite solar cells using machine learning

  • 期刊论文

  • 发表日期：

    2025年12月5日

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  • Ranadip Kundu

摘要

The pursuit of non-toxic and sustainable photovoltaic materials has driven growing interest in double perovskite halides as promising alternatives to conventional lead-based absorbers. In this study, a comprehensive design, simulation, and machine learning (ML)-based optimization of lead-free K2AMoI6 (A = Na, Rb) perovskite solar cells has been presented. The impact of A-site cation substitution on structural and optoelectronic properties was systematically analyzed to elucidate its influence on device performance. The Na-based perovskite (K2NaMoI6) exhibits a relatively wider bandgap and superior open-circuit voltage, whereas the Rb-based analogue (K2RbMoI6) shows improved carrier mobility attributed to enhanced orbital interactions. Device simulations conducted in SCAPS-1D optimized absorber thickness, defect density, and doping concentration for both configurations. Experimental validation revealed that K2NaMoI6 achieved a higher power conversion efficiency (21.6%) compared to K2RbMoI6 (11.6%), demonstrating its superior photovoltaic potential. Additionally, the ML regression model effectively predicted device performance with an accuracy of 89.35% and 88.47% for Na- and Rb-based systems, respectively, confirming the robustness of the computational approach. Overall, these results highlight K2NaMoI6 as a stable, lead-free double perovskite absorber with promising efficiency and scalability for next-generation environmentally sustainable solar cells.