Light scattering effect by rough surface of the solar cell material

2003 ◽  
Author(s):  
Joong Hwan Kwak ◽  
Kyung Hoon Jun ◽  
Koeng Su Lim
Keyword(s):  
Solar Cell ◽  
Light Scattering ◽  
Rough Surface ◽  
Scattering Effect ◽  
Cell Material ◽  
Solar Cell Material ◽  
Light Scattering Effect

Influence of dye-concentration on the light-scattering effect in dye-sensitized solar cell

2015 ◽  
Vol 149-150 ◽  
pp. 594-600 ◽  
Author(s):  
Kyung-Jun Hwang ◽  
Dong-Won Park ◽  
Sungho Jin ◽  
Sang Ook Kang ◽  
Dae Won Cho
Keyword(s):  
Solar Cell ◽  
Light Scattering ◽  
Dye Sensitized Solar Cell ◽  
Dye Sensitized ◽  
Scattering Effect ◽  
Light Scattering Effect

Prediction of Solar Cell Materials via Unsupervised Literature Learning

2021 ◽  
Author(s):  
Lei Zhang ◽  
Mu He
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Language Processing ◽  
Perovskite Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Cell Types ◽  
Data Driven ◽  
Cell Material ◽  
Textual Data ◽  
Solar Cell Material

Abstract Despite the significant advancement of the data-driven studies for physical science, the textual data that are numerous in the literature are not fully embraced by the physics and materials community. In this manuscript, we successfully employ the natural language processing (NLP) technique to unsupervisedly predict the existence of solar cell types including the dye-sensitized solar cells and the perovskite solar cells based on literatures published prior to their first discovery without human annotation. Enlightened by this, we further identify possible solar cell material candidates via NLP starting with a comprehensive training database of 3.2 million paper abstracts published before 2021. The NLP model effectively predicts the existing solar cell materials, while an uncommon solar cell material namely PtSe2 is suggested as an appropriate candidate for the future solar cells. Its optoelectronic properties are comprehensive investigated via first-principles calculations to reveal the decent stability and optoelectronic performance of the NLP-predicted candidate. This study demonstrates the viability of the textual data for the data-driven materials prediction and highlights the NLP method as a powerful tool to reliably predict the solar cell materials.

scholarly journals Intensity Dependent Femtosecond Dynamics in a PBDTTPD-Based Solar Cell Material

2012 ◽  
Vol 3 (20) ◽  
pp. 2952-2958 ◽  
Author(s):  
Arun Aby Paraecattil ◽  
Serge Beaupré ◽  
Mario Leclerc ◽  
Jacques-E. Moser ◽  
Natalie Banerji
Keyword(s):  
Solar Cell ◽  
Femtosecond Dynamics ◽  
Cell Material ◽  
Solar Cell Material

Hydrogenated a ‐ Si x Ge1 − x : A Potential Solar Cell Material

1982 ◽  
Vol 129 (12) ◽  
pp. 2850-2855 ◽  
Author(s):  
M. C. Cretella ◽  
J. A. Gregory
Keyword(s):  
Solar Cell ◽  
Cell Material ◽  
Solar Cell Material
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