Optimized Cu-doping in ZnO electro-spun nanofibers for enhanced photovoltaic performance in perovskite solar cells and photocatalytic dye degradation

Lee, Kang Hoon; Farheen, Rabeea; Arshad, Zafar; Ali, Mumtaz; Hassan, Hamza; Alshareef, Mubark; A.Dahshan,; Khalid, Usama

doi:10.1039/d4ra01544d

RSC Adv.

2024

DOI: 10.1039/d4ra01544d

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Optimized Cu-doping in ZnO electro-spun nanofibers for enhanced photovoltaic performance in perovskite solar cells and photocatalytic dye degradation

Kang Hoon Lee,

Rabeea Farheen,

Zafar Arshad

et al.

Abstract: Perovskite solar cells (PSCs) compete with conventional solar cells regarding their low-temperature processing and suitable power conversion efficiency.

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Cited by 7 publications

References 78 publications

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Enhancing the Performance of MAPbI3-Based Perovskite Solar Cells Fabricated Under Ambient Air: Effect of Cu, Ni, and Zn Doping into TiO2

Al Qadri,

Sipahutar,

Khamidy

et al. 2024

J. Electron. Mater.

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Enhancing the Performance of MAPbI3-Based Perovskite Solar Cells Fabricated Under Ambient Air: Effect of Cu, Ni, and Zn Doping into TiO2

Al Qadri,

Sipahutar,

Khamidy

et al. 2024

J. Electron. Mater.

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Textile dyes removing from the wastewater by green synthesized Cu-doped ZnO photocatalysts under the simulated sunlight illumination

Sajjadi,

Hossinzadeh

2024

Ceramics International

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Optimization of Solar Panel Efficiency using Genetic Algorithms

Vijya Ram Raju,

Suryanarayana Reddy,

Mishra

et al. 2024

E3S Web Conf.

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Maximizing the efficiency of solar panels is crucial for enhancing the viability of solar energy in both residential and commercial sectors. In this study, we employ Genetic Algorithms (GAs) to optimize various parameters affecting solar panel performance, such as tilt angle, azimuth angle, and environmental conditions like temperature and solar irradiance. We develop a model that simulates the efficiency of solar panels under varying conditions and apply GAs to find the optimal configuration. The results demonstrate a significant improvement in energy output, with optimized parameters yielding up to a 15% increase in solar panel efficiency. This research shows the potential of GAs in solving complex optimization problems in renewable energy systems.

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Optimized Cu-doping in ZnO electro-spun nanofibers for enhanced photovoltaic performance in perovskite solar cells and photocatalytic dye degradation

Abstract: Perovskite solar cells (PSCs) compete with conventional solar cells regarding their low-temperature processing and suitable power conversion efficiency.

Cited by 7 publications

References 78 publications

Enhancing the Performance of MAPbI3-Based Perovskite Solar Cells Fabricated Under Ambient Air: Effect of Cu, Ni, and Zn Doping into TiO2

Enhancing the Performance of MAPbI3-Based Perovskite Solar Cells Fabricated Under Ambient Air: Effect of Cu, Ni, and Zn Doping into TiO2

Textile dyes removing from the wastewater by green synthesized Cu-doped ZnO photocatalysts under the simulated sunlight illumination

Optimization of Solar Panel Efficiency using Genetic Algorithms

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