Polymer crystallinity and crystallization kinetics via benchtop 1H NMR relaxometry: Revisited method, data analysis, and experiments on common polymers

Polymer(2018)

引用 24|浏览10
暂无评分
摘要
Semi-crystalline polymers play an enormously important role in materials science, engineering, and nature. Two thirds of all synthetic polymers have the ability to crystallize which allows for the extensive use of these materials in a variety of applications as molded parts, films, or fibers. Here, we present a study on the applicability of benchtop 1H NMR relaxometry to obtain information on the bulk crystallinity and crystallization kinetics of the most relevant synthetic semi-crystalline polymers. In the first part, we investigated the temperature-dependent relaxation behavior and identified T = Tg + 100 K as the minimum relative temperature difference with respect to Tg for which the mobility contrast between crystalline and amorphous protons is sufficient for an unambiguous determination of polymer crystallinity. The obtained bulk crystallinities from 1H NMR were compared to results from DSC and XRD, and all three methods showed relatively good agreement for all polymers. In the second part, we focused on the determination of the crystallization kinetics, i.e., monitoring of isothermal crystallization, which required a robust design of the pulse sequence, precise temperature calibration, and careful data analysis. We found the combination of a magic sandwich echo (MSE) with a short acquisition time followed by a Carr-Purcell-Meiboom-Gill (CPMG) echo train with short pulse timings to be the most suitable for monitoring crystallization. This study demonstrates the application of benchtop 1H NMR relaxometry to investigate the bulk crystallinity and crystallization kinetics of polymers, which can lead to its optimal use as an in-situ technique in research, quality control, and processing labs.
更多
查看译文
关键词
Polymer crystallinity,Crystallization kinetics,Semi-crystalline polymers,Low-field NMR,TD-NMR,NMR relaxometry,Molecular dynamics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要