Knol Wouter C, Smeets Jasper P H, Gruendling Till, Pirok Bob W J, Peters Ron A H
Analytical Chemistry Group, Van 't Hoff Institute for Molecular Sciences (HIMS), Faculty of Science, University of Amsterdam, Science Park 904, Amsterdam, the Netherlands; Centre for Analytical Sciences Amsterdam, Science Park 904, Amsterdam, the Netherlands.
Analytical Chemistry Group, Van 't Hoff Institute for Molecular Sciences (HIMS), Faculty of Science, University of Amsterdam, Science Park 904, Amsterdam, the Netherlands; Centre for Analytical Sciences Amsterdam, Science Park 904, Amsterdam, the Netherlands.
J Chromatogr A. 2023 Feb 8;1690:463800. doi: 10.1016/j.chroma.2023.463800. Epub 2023 Jan 14.
An understanding of the composition and molecular heterogeneities of complex industrial polymers forms the basis of gaining control of the physical properties of materials. In the current work we report on the development of an online method to hyphenate liquid polymer chromatography with pyrolysis-GC (Py-GC). The designed workflow included a 10-port valve for fractionation of the first-dimension effluent. Collected fractions were transferred to the Py-GC by means of a second LC pump, a 6-port valve was used to control injection in the Py-GC, allowing the second pump to operate continuously. The optimized large volume injection (LVI) method was capable of analyzing 117 µL of the LC effluent in a 6 min GC separation with a total cycle time of 8.45 min. This resulted in a total run time of 2.1 h while obtaining 15 Py-GC runs over the molar mass separation. The method was demonstrated on various real-life samples including a complex industrial copolymer with a bimodal molar mass distribution. The developed method was used to monitor the relative concentration of 5 different monomers over the molar mass distribution. Furthermore, the molar mass-dependent distribution of a low abundant comonomer (styrene, <1% of total composition) was demonstrated, highlighting the low detection limits and increased resolving power of this approach over e.g. online NMR or IR spectroscopy. The developed method provides a flexible and widely applicable approach to LC-Py-GC hyphenation without having to resort to costly and specialized instrumentation.
了解复杂工业聚合物的组成和分子异质性是控制材料物理性能的基础。在当前工作中,我们报告了一种在线联用液体聚合物色谱与热解气相色谱(Py-GC)方法的开发。设计的工作流程包括一个用于一维流出物分馏的十通阀。收集的馏分通过第二个液相色谱泵转移到Py-GC,使用一个六通阀控制Py-GC中的进样,使第二个泵能够连续运行。优化后的大体积进样(LVI)方法能够在6分钟的气相色谱分离中分析117微升的液相色谱流出物,总循环时间为8.45分钟。这导致总运行时间为2.1小时,同时在摩尔质量分离过程中获得15次Py-GC运行。该方法在各种实际样品上得到了验证,包括一种具有双峰摩尔质量分布的复杂工业共聚物。所开发的方法用于监测摩尔质量分布上5种不同单体的相对浓度。此外,还展示了一种低丰度共聚单体(苯乙烯,占总组成的<1%)的摩尔质量依赖性分布,突出了该方法相对于例如在线核磁共振或红外光谱的低检测限和更高的分辨能力。所开发的方法提供了一种灵活且广泛适用的液相色谱-热解气相色谱联用方法,无需借助昂贵的专用仪器。