journal article·2022-03

Optical Designing of Perovskite Solar Cells

Sonia Rani, Arun Kumar, Dhriti Sundar Ghosh

IEEE Journal of Photovoltaics· Volume 12· Issue 2
Publisher page

Abstract

We report a detailed optical designing of perovskite solar cells (PvSCs) taking an example of a planar architecture cell having methylammonium lead iodide as active layer and incorporating a transparent electrode (TE) consisting of TiO 2 /Ag/TiO 2 (TAT). In the proposed electrode, the overcoat TiO 2 layer not only reduces the inherent reflection of the silver layer but also acted as the electron transport layer. A comparative study between the optical spectra of the TE is performed and it has been observed that the best thickness combination of the undercoat and overcoat TiO 2 layer for the highest transmittance of 89.8% does not correspond to the best device performance. We found that this is due to the lower optical field density within the active layer especially for the longer wavelength regime. Besides this, with the help of 3-D scatter plots, we have optimized the thickness of the electron transporting, active, and hole transporting layer simultaneously for getting a maximum current density. We found that for the TAT-based device 75, 600, and 30 nm are the optimized thicknesses of overcoat TiO 2 , perovskite layer, and spiro-OMeTAD, respectively, for getting a maximum current density of 23.28 mAcm −2 which is similar to ITO (indium tin oxide) based device of 24.14 mAcm −2 . This article gives insight into the potential of TAT electrode which can be used as an alternative to conventionally used ITO as TE. Additionally, optical modeling demonstrates that by optimizing the thickness of the critical layers in the stack, it is possible to get high-performance PvSCs.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Perovskite Materials and Applications · Conducting polymers and applications · Organic Light-Emitting Diodes Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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