scholarly journals Phosphorene-AsP heterostructure as a potential excitonic solar cell material - A first principles study

2018 ◽  
Author(s):  
M. R. Ashwin Kishore ◽  
P. Ravindran
Keyword(s):  
Solar Cell ◽  
First Principles ◽  
First Principles Study ◽  
Cell Material ◽  
Solar Cell Material

scholarly journals The role of Sb in solar cell material Cu2ZnSnS4

2017 ◽  
Vol 5 (14) ◽  
pp. 6606-6612 ◽  
Author(s):  
Xiaoli Zhang ◽  
Miaomiao Han ◽  
Zhi Zeng ◽  
Yuhua Duan
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
First Principles ◽  
Point Of View ◽  
Efficiency Improvement ◽  
First Principles Calculations ◽  
Cell Material ◽  
Related Defect ◽  
Solar Cell Material

In this study, based on first-principles calculations we report a possible mechanism of efficiency improvement of Sb-doped Cu2ZnSnS4 (CZTS) solar cells from the Sb-related defect point of view.

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.

A low cost and nontoxic absorber for intermediate band solar cell based on P-doped Cu2SiS3: A first-principles study

2021 ◽  
Vol 718 ◽  
pp. 138473
Author(s):  
Yang Xue ◽  
Lijie Ding ◽  
Wentong Zhou ◽  
Wei Kuang ◽  
Hua Ning ◽  
...  
Keyword(s):  
Solar Cell ◽  
First Principles ◽  
Low Cost ◽  
Intermediate Band ◽  
Intermediate Band Solar Cell ◽  
First Principles Study

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
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