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Advancing perovskite solar cell commercialization: Bridging materials, vacuum deposition, and AI-assisted automation
- Source :
- Next Materials, Vol 3, Iss , Pp 100103- (2024)
- Publication Year :
- 2024
- Publisher :
- Elsevier, 2024.
-
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.
- Subjects :
- Perovskites
Solar cells
Vacuum deposition
Automatic deposition systems
Technology
Subjects
Details
- Language :
- English
- ISSN :
- 29498228
- Volume :
- 3
- Issue :
- 100103-
- Database :
- Directory of Open Access Journals
- Journal :
- Next Materials
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.b749482aed8946a8b4f5987be1fb9715
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.nxmate.2023.100103