Optimized design of silver nanoparticles for broadband and high efficiency light trapping in thin film solar cells

Author:

Wang Zhiye1,Wang Shuying1,Jiang Yue1,Zhou Hua2,Tuokedaerhan Kamale1,Chen Yanhua1,Shen Xiangqian1ORCID

Affiliation:

1. School of Physical Science and Technology, Xinjiang University, Urumqi 830046, P. R. China

2. School of Physics, Shandong University, 27 Shanda Nanlu, Jinan, Shandong 250100, P. R. China

Abstract

This paper reports a high-efficiency approach to improve the photoelectric-conversion efficiency of thin-film solar cells by plasmonic scattering and local near-field amplification of silver nanoparticles. We employ a three-dimensional (3D) electromagnetic model and use the finite-difference time-domain (FDTD) and rigorously coupled-wave analysis methods to investigate the interaction of light with such a metallic particle. The numerical results show that the absorption and scattering spectra depend upon the properties of the embedded particles and the refractive index of the surrounding material. Strong redshifts and high-order modes are observed in the response spectrum with the increase of the particle size and the refractive index of the surrounding material. With an optimized design having [Formula: see text], [Formula: see text], and [Formula: see text] nm, the performance of cell device is improved over a broad spectral range. Moreover, some of the absorption, in the resonance region, is beyond the Yablonovitch limit. The corresponding light-generated photocurrent is increased from 14.2 mA/cm2 to 18.3 mA/cm2, with a 28.9% enhancement compared with conventional cells with antireflective coatings (ARCs).

Funder

Natural Science Foundation of Xinjiang Province

Higher education research program of Xinjiang Province

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Predicting the Thickness of Solar Films Based on Neural Networks;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02

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