Nur-E-Alam Mohammad, Islam Mohammad Aminul, Kar Yap Boon, Kiong Tiong Sieh, Misran Halina, Khandaker Mayeen Uddin, Fouad Yasser, Soudagar Manzoore Elahi M, Cuce Erdem
Institute of Sustainable Energy, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor, 43000, Malaysia.
School of Science, Edith Cowan University, 270 Joondalup Dr., 6027, Joondalup, WA, Australia.
Sci Rep. 2024 Aug 28;14(1):19995. doi: 10.1038/s41598-024-70344-3.
Perovskite solar cells (PSCs) hold potential for low-cost, high-efficiency solar energy, but their sensitivity to moisture limits practical application. Current fabrication requires controlled environments, limiting mass production. Researchers aim to develop stable PSCs with longer lifetimes under ambient conditions. In this research work, we investigated the stability of perovskite films and solar cells fabricated and annealed in natural air using four different anti-solvents: toluene, ethyl acetate, diethyl ether, and chlorobenzene. Films (about 300 nm thick) were deposited via single-step spin-coating and subjected to ambient air-atmosphere for up to 30 days. We monitored changes in crystallinity, electrical properties, and optics over time. Results showed a gradual degradation in the films' crystallinity, morphology, and electro-optical properties. Notably, films made with ethyl acetate exhibited superior stability compared to other solvents. These findings contribute to advancing stable and high-performance PSCs manufactured under normal ambient conditions. In addition, we also discuss the possible machine learning (ML) approach to our future work direction to optimize the materials structures, and synthesis process parameters for future high-efficient perovskite solar cells fabrication.
钙钛矿太阳能电池（PSCs）具有实现低成本、高效率太阳能的潜力，但其对水分的敏感性限制了实际应用。目前的制造过程需要可控环境，限制了大规模生产。研究人员旨在开发在环境条件下具有更长寿命的稳定PSCs。在这项研究工作中，我们使用四种不同的反溶剂：甲苯、乙酸乙酯、二乙醚和氯苯，研究了在自然空气中制备和退火的钙钛矿薄膜和太阳能电池的稳定性。通过单步旋涂沉积薄膜（约300纳米厚），并在环境空气中放置长达30天。我们监测了结晶度、电学性质和光学性质随时间的变化。结果表明，薄膜的结晶度、形态和电光性质逐渐退化。值得注意的是，与其他溶剂相比，用乙酸乙酯制成的薄膜表现出优异的稳定性。这些发现有助于推动在正常环境条件下制造稳定且高性能的PSCs。此外，我们还讨论了在未来工作方向中可能采用的机器学习（ML）方法，以优化材料结构以及未来高效钙钛矿太阳能电池制造的合成工艺参数。
