Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldstr. 10, 07743 Jena, Germany; Jena Center for Soft Matter (JCSM), Friedrich Schiller University Jena, Philosophenweg 7, 07743 Jena, Germany.
Department of Chemistry, The University of Akron, Akron, OH 44325, USA.
Anal Chim Acta. 2016 Aug 17;932:1-21. doi: 10.1016/j.aca.2016.05.024. Epub 2016 May 24.
This review covers the application of mass spectrometry (MS) and its hyphenated techniques to synthetic polymers of varying architectural complexities. The synthetic polymers are discussed as according to their architectural complexity from linear homopolymers and copolymers to stars, dendrimers, cyclic copolymers and other polymers. MS and tandem MS (MS/MS) has been extensively used for the analysis of synthetic polymers. However, the increase in structural or architectural complexity can result in analytical challenges that MS or MS/MS cannot overcome alone. Hyphenation to MS with different chromatographic techniques (2D × LC, SEC, HPLC etc.), utilization of other ionization methods (APCI, DESI etc.) and various mass analyzers (FT-ICR, quadrupole, time-of-flight, ion trap etc.) are applied to overcome these challenges and achieve more detailed structural characterizations of complex polymeric systems. In addition, computational methods (software: MassChrom2D, COCONUT, 2D maps etc.) have also reached polymer science to facilitate and accelerate data interpretation. Developments in technology and the comprehension of different polymer classes with diverse architectures have significantly improved, which allow for smart polymer designs to be examined and advanced. We present specific examples covering diverse analytical aspects as well as forthcoming prospects in polymer science.
这篇综述涵盖了质谱（MS）及其联用技术在不同结构复杂程度的合成聚合物中的应用。根据结构复杂程度，将合成聚合物分为线性均聚物和共聚物、星形聚合物、树枝状聚合物、环状共聚物和其他聚合物进行讨论。MS 和串联 MS（MS/MS）已广泛用于合成聚合物的分析。然而，结构或结构复杂性的增加可能会导致 MS 或 MS/MS 无法单独克服的分析挑战。与不同色谱技术（二维 LC、SEC、HPLC 等）联用、利用其他电离方法（APCI、DESI 等）和各种质量分析器（FT-ICR、四极杆、飞行时间、离子阱等）的联用，可克服这些挑战，实现对复杂聚合物体系更详细的结构表征。此外，计算方法（软件：MassChrom2D、COCONUT、2D 图谱等）也已应用于聚合物科学，以促进和加速数据解释。技术的发展和对不同结构的不同聚合物类别的理解显著提高，这使得智能聚合物设计能够得到检验和推进。我们展示了涵盖各种分析方面的具体实例，以及聚合物科学的未来展望。
