Systematic evaluation of structure–property relationships in heteroacene – diketopyrrolopyrrole molecular donors for organic solar cells

2017 ◽  
Vol 5 (19) ◽  
pp. 9217-9232 ◽  
Author(s):  
Stephen Loser ◽  
Sylvia J. Lou ◽  
Brett M. Savoie ◽  
Carson J. Bruns ◽  
Amod Timalsina ◽  
...  
Keyword(s):  
Solar Cells ◽  
Charge Transport ◽  
Active Layer ◽  
Organic Solar Cells ◽  
Molecular Shape ◽  
Layer Charge ◽  
Systematic Evaluation ◽  
Structure Property ◽  
Structure Property Relationships

Understanding the effects of molecular shape on active layer charge transport in OPVs.

A wrinkled structure with broadband and omnidirectional light-trapping abilities for improving the performance of organic solar cells with low defect density

Nanoscale ◽  
2019 ◽  
Vol 11 (46) ◽  
pp. 22467-22474 ◽  
Author(s):  
Kong Liu ◽  
Yang Sun ◽  
Qicong Li ◽  
Cheng Yang ◽  
Muhammad Azam ◽  
...  
Keyword(s):  
Solar Cells ◽  
Charge Transport ◽  
Active Layer ◽  
Organic Solar Cells ◽  
Light Absorption ◽  
Defect Density ◽  
Light Trapping ◽  
Transport Efficiency ◽  
Wrinkled Structure

A wrinkled structure could enhance omnidirectional light absorption in the organic active layer and charge transport efficiency at the interface.

Improving the charge transport of the ternary blend active layer for efficient semitransparent organic solar cells

2020 ◽  
Vol 13 (12) ◽  
pp. 5177-5185
Author(s):  
Pan Yin ◽  
Zhigang Yin ◽  
Yunlong Ma ◽  
Qingdong Zheng
Keyword(s):  
Solar Cells ◽  
Solar Cell ◽  
Charge Transport ◽  
Active Layer ◽  
Organic Solar Cells ◽  
Organic Solar Cell ◽  
Ternary Blend ◽  
Visible Transmittance

With the aid of a suitable third component acceptor material, the best-performance semitransparent organic solar cell shows an outstanding efficiency of 13.49% at an average visible transmittance of 22.58%.

scholarly journals Charge transport and extraction of PTB7:PC71BM organic solar cells: effect of film thickness and thermal-annealing

RSC Advances ◽  
2019 ◽  
Vol 9 (43) ◽  
pp. 24895-24903 ◽  
Author(s):  
Yingying Zhang ◽  
Xiong Li ◽  
Tingting Dai ◽  
Denghui Xu ◽  
Jianfeng Xi ◽  
...  
Keyword(s):  
Solar Cells ◽  
Charge Carrier ◽  
Film Thickness ◽  
Charge Transport ◽  
Thermal Annealing ◽  
Active Layer ◽  
Organic Solar Cells ◽  
Carrier Transport ◽  
Charge Carrier Transport ◽  
Charge Extraction

Charge carrier transport in the active layer and charge extraction at the electrode have significant impact on the performance of solar cells.

Dicyanovinyl-Substituted Oligothiophenes: Structure-Property Relationships and Application in Vacuum-Processed Small Molecule Organic Solar Cells

2011 ◽  
Vol 21 (5) ◽  
pp. 897-910 ◽  
Author(s):  
Roland Fitzner ◽  
Egon Reinold ◽  
Amaresh Mishra ◽  
Elena Mena-Osteritz ◽  
Hannah Ziehlke ◽  
...  
Keyword(s):  
Solar Cells ◽  
Small Molecule ◽  
Organic Solar Cells ◽  
Structure Property ◽  
Structure Property Relationships

scholarly journals Simultaneous Optimization of Donor/acceptor Pairs and Device Specifications for Non-Fullerene Organic Solar Cells Using a QSPR Model with Morphological Descriptors

2021 ◽  
Author(s):  
Yaping Wen ◽  
Bohan Yan ◽  
Theophile Gaudin ◽  
Jing Ma ◽  
Haibo Ma
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
Chemical Space ◽  
Simultaneous Optimization ◽  
Structure Property ◽  
Qspr Model ◽  
Structure Property Relationships ◽  
Quantitative Structure Property Relationships ◽  
Donor Acceptor ◽  
New Framework

<p><a></a><a>In addition to designing new donor (D) and/or acceptor (A) molecules, the optimization of</a><a></a><a> experimental fabrication conditions </a>for the organic solar cells (OSCs) is also a complex, multidimensional challenge, which hasn’t been theoretically explored. Herein, a new framework for simultaneous optimizing D/A molecule pairs and device specifications of OSCs is proposed, through a quantitative structure-property relationships (QSPR) model built by machine learning. Combining the <a></a><a>device parameters</a> with<a></a><a> structural and electronic </a>variables, the built QSPR model achieved unprecedentedly high accuracy and consistency. Additionally, a huge chemical space containing <a>1,942,785</a> D/A pairs is explored to find potential synergistic ones. Favorable expereimental parameters such as root-mean-square (<i>RMS</i>) and the D/A ratio (<i>DAratio</i>) are further screened by grid search methods. <a></a><a></a><a></a><a>Overall, this study suggests </a>the feasibility to optimize D/A molecule pairs and device specifications simultaneously by enabling better-informed and data-driven techniques and this could facilitate the acceleration of improving OSCs efficiencies.</p>

scholarly journals Simultaneous Optimization of Donor/acceptor Pairs and Device Specifications for Non-Fullerene Organic Solar Cells Using a QSPR Model with Morphological Descriptors

2021 ◽  
Author(s):  
Yaping Wen ◽  
Bohan Yan ◽  
Theophile Gaudin ◽  
Jing Ma ◽  
Haibo Ma
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
Chemical Space ◽  
Simultaneous Optimization ◽  
Structure Property ◽  
Qspr Model ◽  
Structure Property Relationships ◽  
Quantitative Structure Property Relationships ◽  
Donor Acceptor ◽  
New Framework

<p><a></a><a>In addition to designing new donor (D) and/or acceptor (A) molecules, the optimization of</a><a></a><a> experimental fabrication conditions </a>for the organic solar cells (OSCs) is also a complex, multidimensional challenge, which hasn’t been theoretically explored. Herein, a new framework for simultaneous optimizing D/A molecule pairs and device specifications of OSCs is proposed, through a quantitative structure-property relationships (QSPR) model built by machine learning. Combining the <a></a><a>device parameters</a> with<a></a><a> structural and electronic </a>variables, the built QSPR model achieved unprecedentedly high accuracy and consistency. Additionally, a huge chemical space containing <a>1,942,785</a> D/A pairs is explored to find potential synergistic ones. Favorable expereimental parameters such as root-mean-square (<i>RMS</i>) and the D/A ratio (<i>DAratio</i>) are further screened by grid search methods. <a></a><a></a><a></a><a>Overall, this study suggests </a>the feasibility to optimize D/A molecule pairs and device specifications simultaneously by enabling better-informed and data-driven techniques and this could facilitate the acceleration of improving OSCs efficiencies.</p>

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