4.3 Review

Applications of Two-dimensional Correlation Infrared Spectroscopy in the Characterization of Polymers

期刊

ACTA POLYMERICA SINICA
卷 53, 期 5, 页码 522-538

出版社

SCIENCE PRESS
DOI: 10.11777/j.issn1000-3304.2021.21362

关键词

Molecular spectroscopy; Two-dimensional correlation spectroscopy; Polymer; Molecular interactions

向作者/读者索取更多资源

2Dcos is an advanced analysis method that holds great advantages in the field of polymers. It can effectively identify fine structures and dynamic mechanisms within polymer systems, thus improving the analysis results.
Two-dimensional correlation spectroscopy (2Dcos) is an advanced analysis method, which holds great advantages in improving spectral resolutions and interpreting dynamic processes, and has attracted great attention in the field of polymers. Molecular spectroscopy is frequently applied in the characterization of polymers, which involves abundant molecular interactions and complex structures. Under the help of 2Dcos analysis, fine structures as well as dynamic mechanisms within the polymer systems can be effectively identified, thus significantly enriching and improving the analysis results. In this paper, we will mainly focus on the two-dimensional correlation infrared spectroscopy (2DIR). Firstly, the history and basic principles of 2Dcos are briefly introduced. Then, some relevant experimental and analytical techniques are presented based on the actual process. Finally, typical applications of 2DIR in the polymer characterization are demonstrated and the features thereinto are also shown. Particularly, the response mechanisms of temperature-responsive polymers, complex molecular interactions in stretchable ionic conductors, diffusion processes of small molecules in polymer matrix and structures of natural polymers are investigated. It is hoped that this paper will help readers better understand 2Dcos and further expand its applications in the field of polymers. [GRAPHICS] .

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.3
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据