Nonfullerene Acceptors for Organic Photovoltaics: From Conformation Effect to Power Conversion Efficiencies Prediction-Reference-Cited by-同舟云学术

Nonfullerene Acceptors for Organic Photovoltaics: From Conformation Effect to Power Conversion Efficiencies Prediction

Published:2019-07-31 Issue:11 Volume:3 Page:1900258
ISSN:2367-198X
Container-title:Solar RRL
language:en
Short-container-title:Sol. RRL

Author:

Sui Ming-Yue¹,Yang Zi-Rui²,Geng Yun³,Sun Guang-Yan¹⁴^ORCID,Hu LiHong²,Su Zhong-Min³

Affiliation:

1. Department of ChemistryFaculty of ScienceYanbian University Yanji 133002 Jilin China

2. School of Information Science and TechnologyNortheast Normal University Changchun 130117 Jilin China

3. Institute of Functional Material ChemistryFaculty of ChemistryNortheast Normal University Changchun 130024 Jilin China

4. Faculty of Chemical Engineering and New Energy MaterialsZhuhai College of Jilin University Zhuhai 519041 Guangdong China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/solr.201900258

Reference51 articles.

1. Polymer-Fullerene Bulk-Heterojunction Solar Cells

2. Polymer Photovoltaic Cells: Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions

3. Organic solar cells based on non-fullerene acceptors

4. Realizing Over 13% Efficiency in Green‐Solvent‐Processed Nonfullerene Organic Solar Cells Enabled by 1,3,4‐Thiadiazole‐Based Wide‐Bandgap Copolymers

5. Molecular Optimization Enables over 13% Efficiency in Organic Solar Cells

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Correction of the calculation method of CT state energy in ITIC and Y6 acceptor systems;Journal of Photochemistry and Photobiology A: Chemistry;2024-11

2. Machine learning advancements in organic synthesis: A focused exploration of artificial intelligence applications in chemistry;Artificial Intelligence Chemistry;2024-06

3. Machine Learning Study on the Virtual Screening of Donor–Acceptor Pairs for Organic Solar Cells;physica status solidi (a);2024-03-11

4. Machine learning in the era of smart automation for renewable energy materials;e-Prime - Advances in Electrical Engineering, Electronics and Energy;2024-03

5. Machine learning study of D:A1:A2 ternary organic solar cells;Organic Electronics;2024-02