Synthesis and Structure-Property Relationships of Phosphole-Based π Systems and Their Applications in Organic Solar Cells

2015 ◽  
Vol 15 (3) ◽  
pp. 636-650 ◽  
Author(s):  
Yoshihiro Matano
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
Structure Property ◽  
Structure Property Relationships

Metal Nanoparticle Enhanced Organic Solar Cells: A Numerical Study of Structure Property Relationships

2011 ◽  
Author(s):  
Michael Salvador ◽  
Yong Zhang ◽  
Kung-Shih Chen ◽  
Hin-Lap Yip ◽  
Alex K.-Y. Jen ◽  
...  
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
Numerical Study ◽  
Metal Nanoparticle ◽  
Structure Property ◽  
Structure Property Relationships

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.

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>

Recent advances of polymer acceptors for high-performance organic solar cells

2020 ◽  
Vol 8 (1) ◽  
pp. 28-43 ◽  
Author(s):  
Congcong Zhao ◽  
Jiuxing Wang ◽  
Jiqing Jiao ◽  
Linjun Huang ◽  
Jianguo Tang
Keyword(s):  
Solar Cells ◽  
Organic Solar Cells ◽  
High Performance ◽  
Structure Property ◽  
Structure Property Relationships ◽  
Photovoltaic Materials ◽  
Recent Advances

Recent advances in polymer acceptors that focus on structure–property relationships, which may provide guidance for photovoltaic materials, were systematically summarized.

Sign in / Sign up

Export Citation Format

Share Document