Abstract
Organic-inorganic metal halide perovskites solar cells (PSCs) have been emerging as a counterpart or a supplement of silicon-based solar cells. They have shown various interesting optoelectronic properties and impressive power conversion efficiencies, even outperforming the theoretical limits in tandem configurations. However, challenges such as long-term stability and scalable manufacturing remain significant obstacles to commercialization. Key factors like material composition and crystal quality are essential for the reliability and performance of PSCs. Traditional solution-based processes face challenges in scalability and reproducibility. This has drawn attention to vacuum processes, which have been successfully employed in the commercial mass production of optoelectronic devices like displays. Also, recent innovations in automated deposition systems aided by machine learning offer promising solutions. These technological advancements enable rapid optimization of material combinations and manufacturing processes, facilitating a transition from lab-scale prototypes to industrial applications. This review highlights the converging efforts from multiple disciplines—materials science, process engineering and machine learning—that are essential for the transition from experimental validation to commercial, sustainable energy solutions. In summary, the work sets a path forward, where collective expertize can address lingering challenges, making clean, accessible, and affordable energy an attainable goal.
| Original language | English |
|---|---|
| Article number | 100103 |
| Journal | Next Materials |
| Volume | 3 |
| DOIs | |
| State | Published - Apr 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Automatic deposition systems
- Perovskites
- Solar cells
- Vacuum deposition
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