典型文献
Machine Learning for Organic Photovoltaic Polymers:A Minireview
文献摘要：
Machine learning is a powerful tool that can provide a way to revolutionize the material science.Its use for the designing and screening of materials for polymer solar cells is also increasing.Search of efficient polymeric materials for solar cells is really difficult task.Researchers have synthesized and fabricated so many materials.Sorting the results and get feedback for further research requires an innovative approach.In this minireview,we provides brief introduction of machine learning.The importance of machine learning is also mentioned,and the application of machine learning for polymeric material design is discussed.The key challenges that are hindering the wide spread use of machine are discussed.Suggestions are also given to improve the use of data science.The predictions using machine learning maybe not highly accurate but it definitely better than no prediction at all.
文献关键词：
中图分类号：
作者姓名：
Asif Mahmood;Ahmad Irfan;Jin-Liang Wang
作者机构：
Key Laboratory of Cluster Science of Ministry of Education,Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials,Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering in Ministry of Industry and Information Technology,School of Chemistry and Chemical Engineering,Beijing Institute of Technology,Beijing 100081,China;Department of Chemistry,College of Science,King Khalid University,Abha 61413,Saudi Arabia
文献出处：
引用格式：
[1]Asif Mahmood;Ahmad Irfan;Jin-Liang Wang-.Machine Learning for Organic Photovoltaic Polymers:A Minireview)[J].高分子科学（英文版）,2022(08):870-876
A类：
Minireview
B类：
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AB值：
0.605639
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