Abstract From claims of roughly 3 % efficiency in 2009 to over 25 % efficiency now, perovskite solar cells have made amazing developments in recent years. Perovskite solar cells have quickly increased their efficiency, but there are still a number of obstacles to overcome before they can be considered a viable commercial technology. So, improving the stability of the perovskite solar cells and obtaining the mechanical properties of this kind of structure using computer simulation to decrease the computational cost is a challenging issue for designers. In this work, instead of a metal layer in the fabrication of solar cells, a functionally graded (FG) layer in which the material properties in this layer change in each direction. For the first time in the current report, the nonlinear phase velocity of the 3D-FG solar cells via mathematical simulation is presented. For solving the nonlinear partial differential equations (PDEs) of the perovskite solar cells, an analytical method is used. After doing some mathematical manipulation using the analytical method, a multiple scales method for solving the nonlinear equations in the time domain is presented. In order to compensate for the absence of a dataset suitable for deep neural networks (DNN), a mathematical simulation is conducted to acquire the nonlinear phase velocity characteristics of enhanced solar cells. The DNN method is used to forecast the nonlinear phase velocity characteristics of the present study, after the completion of training, testing, and validation processes. This approach has the advantage of cheap computing expense. Finally, the results show that when the panels tend to be too concave or convex, the nonlinear phase velocity is unstable. As an amazing outcome for related industries, the nonlinear phase velocity is very sensitive to the values of Kx, Ky, and Rx/a, and all designers according to their purposes should consider the amount of these parameters. The current results’ outcomes can be used in future building of the perovskite solar cell knowing about nonlinear dynamics features of 3D-FG perovskite solar cells.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Nonlinear elastic wave dispersions of solar cells strengthened by advanced functionally graded materials via both mathematical modeling and deep neural networks technique


    Beteiligte:
    Chang, Lei (Autor:in) / Wu, Hao (Autor:in) / Hu, YangLin (Autor:in) / El-Sherbeeny, Ahmed M. (Autor:in)


    Erscheinungsdatum :

    2024-02-21




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch