Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/49355
Title: Picosecond laser processing enabled geometrical fill factors exceeding 98 % for inverted wide bandgap perovskite solar modules
Authors: Uzuner, BE
Afshord, AZ
AGUIRRE, Aranzazu 
AERNOUTS, Tom 
Gunbas, G
KUANG, Yinghuan 
Yerci, S
Issue Date: 2025
Publisher: Elsevier
Source: Solar Energy Materials and Solar Cells, 292 (Art N° 113793)
Abstract: Perovskite solar cells (PSCs) have exhibited significant advancements over the last decade, positioning them as the most promising candidate for the next-generation photovoltaic technology. Recently, significant efforts have been focused on the scale-up of PSCs towards enabling their commercialization. In this study, we performed electrical simulations to elucidate the balance between electrical and geometric losses in PSMs and verified our model by fabricating opaque (PSMs) and semi-transparent wide-bandgap perovskite solar modules (ST-PSMs). We showed that a P2 width of 20-50 μm provides an optimized P2 contact resistance, resulting in high geometric fill factor (GFF) and fill factor (FF), simultaneously. PSMs with an aperture area of 4.2 cm 2 , reaching a GFF of 98.4%, an FF of 81.5%, and a PCE of 17.78% were fabricated. To demonstrate the scalability of this approach, 16 cm 2 PSMs, reaching a GFF of 97.0%, an FF of 80.1%, and a PCE of 17.58% were fabricated. ST-PSMs (4 cm 2) with >92.5% GFF, 81.4% FF, and 15.68% PCE were fabricated. We believe that the proposed optoelectronic model, along with its validation through the fabrication, exhibiting exceptionally high GFFs and FFs, elucidates the optical-electrical trade-off in PSMs and thus offers valuable insights for the design of highly efficient PSMs.
Keywords: Perovskite solar modules;Laser scribing;Geometrical fill factor;Simulation;Wide band gap perovskites
Document URI: http://hdl.handle.net/1942/49355
ISSN: 0927-0248
e-ISSN: 1879-3398
DOI: 10.1016/j.solmat.2025.113793
ISI #: 001518599800001
Rights: 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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