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Multi-objective particle swarm optimization on ultra-thin silicon solar cells

Abstract

Finding optimized parameters for any photonic device is a challenging problem, because as the search space enlarges the computation time and design complexity increase. For higher performance solar cells, various studies have been carried out to procure optimized parameters, to attain better performance and low cost as well. In this study, we used a multi-objective particle swarm optimization approach to search design space effectively and obtain fixed parameters for enhanced solar spectrum absorption. Numerical investigations are conducted for pyramid surface pattern, to find proper solar cell parameters for minimum reflection and maximum light trapping which give rise to enhanced absorption of photons. For the ultra-thin-film silicon solar cell having a thickness of 1 µm, a designed double-sided pyramid structure provides an ideal short-circuit photocurrent of 34.23 mA/cm2. In this regard, the proposed approach can be applied to different film thicknesses of semiconductors for different photonic applications by manipulating the reflection/transmission coefficient and light trapping mechanism.

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References

  1. M. Ye, X. Wang, Y. Xu, Parameter extraction of solar cells using particle swarm optimization. J. Appl. Phys. 105, 094502 (2009)

    Article  ADS  Google Scholar 

  2. Y. A. Yilmaz, A. M. Alpkilic, M. Tutgun, D. Yilmaz, I. A. Atalay, A. Yeltik, H. Kurt Inverse design of integrated photonic structures. in 2019 21st International Conference on Transparent Optical Networks (ICTON), (IEEE, 2019), pp. 1–4.

  3. I. A. Atalay, C. Babayiğit, A. M. Alpkiliç, Y. Abdulaziz Yilmaz, H. Kurt Surface texturing with multi-objective particle swarm optimization for absorption enhancement in silicon photovoltaics. in 2019 21st International Conference on Transparent Optical Networks (ICTON), (IEEE, 2019), pp. 1–4.

  4. A. Araújo, M. J. Mendes, T. Mateus, J. Costa, D. Nunes, E. Fortunato,H. Águas, R. Martins (2018) Ultra-fast plasmonic back reflectors production for light trapping in thin Si solar cells. Sol. Energy, 174: 786–792(2018)

  5. K.X. Wang, Z. Yu, V. Liu, Y. Cui, S. Fan, Absorption enhancement in ultrathin crystalline silicon solar cells with antireflection and light trapping nanocone gratings. Nano Lett. 12, 1616–1619 (2012)

    Article  ADS  Google Scholar 

  6. Y. Shi, X. Wang, W. Liu, T. Yang, J. Ma, F. Yang, Nanopyramids and rear-located Ag nanoparticles for broad spectrum absorption enhancement in thin-film solar cells. Opt. Express 22, 20473–20480 (2014)

    Article  ADS  Google Scholar 

  7. X. Zhang, Y. Yu, J. Xi, Y. Wang, X.-H. Sun, Absorption enhancement in double-sided nanocone hole arrays for solar cells. J. Opt. 17, 075901 (2015)

    Article  ADS  Google Scholar 

  8. S. Zhang, M. Liu, W. Liu, Y. Liu, Z. Li, X. Wang, F. Yang, Absorption enhancement in thin film solar cells with bilayer silver nanoparticle arrays. J. Phys. Commun. 2, 055032 (2018)

    Article  Google Scholar 

  9. J. Wu, Absorption enhancement in thin-film solar cells based on periodically chirped structure. Sol. Energy 165, 85–89 (2018)

    Article  ADS  Google Scholar 

  10. L. Guan, G. Shen, Y. Liang, F. Tan, X. Xu, X. Tan, X. Li, Doublesided pyramid texturing design to reduce the light escape of ultrathin crystalline silicon solar cells. Opt. Laser Technol. 120, 105700 (2019)

    Article  Google Scholar 

  11. H. Lu, X. Guo, J. Zhang, X. Zhang, S. Li, C. Yang, Asymmetric metasurface structures for light absorption enhancement in thin film silicon solar cell. J. Opt. 21, 045901 (2019)

    Article  ADS  Google Scholar 

  12. R. C. Eberhart, Y. Shi, Comparison between genetic algorithmsand particle swarm optimization. in International Conference on Evolutionary Programming, (Springer, 1998), pp. 611–616.

  13. R. Kennedy, J. Eberhart, Particle swarm optimization. inProceedings of IEEE International Conference on Neural Networks IV,pages,vol. 1000 (1995), p. 33.

  14. A. Mavrokefalos, S.E. Han, S. Yerci, M.S. Branham, G. Chen, Efficient light trapping in inverted nanopyramid thin crystalline silicon membranes for solar cell applications. Nano Lett. 12, 2792–2796 (2012)

    Article  ADS  Google Scholar 

  15. S.E. Han, G. Chen, Toward the Lambertian limit of light trapping in thin nanostructured silicon solar cells. Nano Lett 10, 4692–4696 (2010)

    Article  ADS  Google Scholar 

  16. P. Campbell, M.A. Green, Light trapping properties of pyramidally textured surfaces. J. Appl. Phys. 62, 243–249 (1987)

    Article  ADS  Google Scholar 

  17. H.R. Philipp, Optical properties of silicon nitride. J. Electrochem. Soc 120, 295 (1973)

    Article  ADS  Google Scholar 

  18. E. Yablonovitch, G.D. Cody, Intensity enhancement in textured optical sheets for solar cells. IEEE Trans. Electron Devices 29, 300–305 (1982)

    Article  ADS  Google Scholar 

  19. M.A. Green, Lambertian light trapping in textured solar cells and light-emitting diodes: analytical solutions. Progress Photovoltaics Res. Appl. 10, 235–241 (2002)

    Article  Google Scholar 

  20. Y. Kanamori, M. Sasaki, K. Hane, Broadband antireflection gratings fabricated upon silicon substrates. Opt. Lett. 24, 1422–1424 (1999)

    Article  ADS  Google Scholar 

  21. H.D. Tong, H.V. Jansen, V.J. Gadgil, C.G. Bostan, E. Berenschot, C.J. van Rijn, M. Elwenspoek, Silicon nitride nanosieve membrane. Nano Lett. 4, 283–287 (2004)

    Article  ADS  Google Scholar 

  22. S. Senthuran, C. Holzwarth, R. Blaikie, M. Alkaisi, Fabricationof sub-wavelength anti-reflective light trapping structures by masklessinterference lithography. in 2011 37th IEEE Photovoltaic Specialists Conference, (IEEE, 2011), pp. 000936–000939.

  23. Z. Yu, H. Gao, W. Wu, H. Ge, S.Y. Chou, Fabrication of large area subwavelength antireflection structures on si using trilayer resist nanoimprint lithography and liftoff. J. Vac. Sci. Technol. B: Microelectron. Nanometer Struct. Process. Meas. Phenom. 21, 2874–2877 (2003)

    Google Scholar 

  24. C.H. Sun, W.L. Min, N.C. Linn, P. Jiang, B. Jiang, Templated fabrication of large area subwavelength antireflection gratings on silicon. Appl. Phys. Lett. 91, 231105 (2007)

    Article  ADS  Google Scholar 

  25. J. Y. Cheng, C. Ross, E. Thomas, H. I. Smith, and G. J. Vancso Fabricationof nanostructures with long-range order using block copolymerlithography. Appl. Phys. Lett, 81: 3657–3659 (2002).

  26. M. Koh, S. Sawara, T. Goto, Y. Ando, T. Shinada, I. Ohdomari, New process for si nanopyramid array (npa) fabrication by ion-beam irradiation and wet etching. Jpn. J. Appl. Phys. 39, 2186 (2000)

    Article  ADS  Google Scholar 

  27. H. Chen, S. Chuang, C.H. Lin, Y. Lin, Using colloidal lithography to fabricate and optimize sub-wavelength pyramidal and honeycomb structures in solar cells. Opt. Express 15, 14793–14803 (2007)

    Article  ADS  Google Scholar 

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Acknowledgements

This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 116F200. H.K. also acknowledges partial support of the Turkish Academy of Sciences.

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Correspondence to Ipek Anil Atalay.

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Atalay, I.A., Gunes, H.A., Alpkilic, A.M. et al. Multi-objective particle swarm optimization on ultra-thin silicon solar cells. J Opt 49, 446–454 (2020). https://doi.org/10.1007/s12596-020-00653-z

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  • DOI: https://doi.org/10.1007/s12596-020-00653-z

Keywords

  • Solar cells
  • Anti-reflection
  • Absorption enhancement
  • Surface texturing
  • Light trapping
  • Multi-objective particle swarm optimization