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Plasmonic effect of metal nanoparticles on enhancing performance of transparent electrodes: a computational investigation

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Abstract

In this paper, metal nanoparticles are used as a new concept to enhance the optical and conductive properties of transparent electrode films. Finite difference time domain (3D-FDTD) numerical analysis is carried out to study the influence of engineered nanoparticles on the electrode transparency and resistivity performances. Our investigation demonstrates that metal nanoparticles are responsible for inducing plasmonic and light trapping effects, where their spatial arrangement, geometry and position in transparent conductive oxide (TCO) play a crucial role in modulating the electrode optical and electrical properties. Besides, an enhanced average transmittance and reduced sheet resistance over the conventional electrodes are recorded. Subsequently, a new hybrid modeling approach based on 3D-FDTD supported by genetic algorithm global optimization is proposed to identify the metal of nanoparticles and their spatial distribution, allowing an excellent trade-off between transparency and resistivity characteristics. Interestingly, the investigated electrode structure with optimized nanoparticles patterning showcases promising pathways for boosting the TCO performances, where it provides a high average figure of merit of 38 × 10−3 Ω−1. Therefore, this systematic investigation can provide more insights concerning the benefit of plasmonic effects for designing high-performance transparent electrodes suitable for optoelectronic and photovoltaic applications.

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Authors and Affiliations

  1. LEA, Department of Electronics, University Mostefa Benboulaid-Batna 2, 05000, Batna, Algeria

    H. Ferhati & F. Djeffal

  2. LEPCM, University of Batna 1, 05000, Batna, Algeria

    F. Djeffal

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  1. H. Ferhati
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  2. F. Djeffal
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Correspondence to F. Djeffal.

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Ferhati, H., Djeffal, F. Plasmonic effect of metal nanoparticles on enhancing performance of transparent electrodes: a computational investigation. J Comput Electron 19, 333–341 (2020). https://doi.org/10.1007/s10825-019-01412-5

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