Machine learning for high performance organic solar cells: current scenario and future prospects-Reference-Cited by-同舟云学术

Machine learning for high performance organic solar cells: current scenario and future prospects

Published:2021 Issue:1 Volume:14 Page:90-105
ISSN:1754-5692
Container-title:Energy & Environmental Science
language:en
Short-container-title:Energy Environ. Sci.

Author:

Mahmood Asif¹²³⁴⁵^ORCID,Wang Jin-Liang¹²³⁴⁵^ORCID

Affiliation:

1. Key Laboratory of Cluster Science of Ministry of Education

2. Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials

3. School of Chemistry and Chemical Engineering

4. Beijing Institute of Technology

5. Beijing

Abstract

In this review, current research status about the machine learning use in organic solar cell research is reviewed. We have discussed the challenges in anticipating the data driven material design.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Beijing Institute of Technology

Publisher

Royal Society of Chemistry (RSC)

Subject

Pollution,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Environmental Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/EE/D0EE02838J

Reference100 articles.

1. Conjugated Polymer-Based Organic Solar Cells

2. Large π-Aromatic Molecules as Potential Sensitizers for Highly Efficient Dye-Sensitized Solar Cells

3. Recent progress in porphyrin-based materials for organic solar cells

4. A novel thiazole based acceptor for fullerene-free organic solar cells

5. Electron‐Deficient and Quinoid Central Unit Engineering for Unfused Ring‐Based A 1 –D–A 2 –D–A 1 ‐Type Acceptor Enables High Performance Nonfullerene Polymer Solar Cells with High V oc and PCE Simultaneously

Cited by 259 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. Machine learning using fingerprints and dye design in the search of lower hole reorganization energy;Dyes and Pigments;2024-12

2. Polymer design with enhanced crystallization tendency aided by machine learning;Physica B: Condensed Matter;2024-12

3. Top 20 influential AI-based technologies in chemistry;Artificial Intelligence Chemistry;2024-12

4. Synthesis guidance of PbS colloidal quantum dots with neural network model for short wave infrared photodetector;Optical Materials;2024-11

5. Recent progress on non-fullerene acceptor materials for organic solar cells;Materials Today Chemistry;2024-10