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采用二维气相色谱-光电离飞行时间质谱法解析复杂烯烃异构体混合物。

Unraveling the Complex Olefin Isomer Mixture Using Two-Dimensional Gas Chromatography-Photoionization-Time of Flight Mass Spectrometry.

机构信息

Organic and biological analytical chemistry group, MolSys Research Unit, University of Liège, Allée du 6 aout, B6c, B-4000 Liège Sart Tilman, Belgium.

ExxonMobil Chemical Europe Inc., Hermeslaan 2, 1831 Machelen, Belgium.

出版信息

J Chromatogr A. 2021 May 24;1645:462103. doi: 10.1016/j.chroma.2021.462103. Epub 2021 Mar 26.

Abstract

Commercial dodecenes are a complex chemical mixture with a majority of C olefins and minority of C olefins. Structurally, dodecene products may consist of straight-chain alkenes, branched alkenes, as well as cyclic hydrocarbons. Due to the difference of feeds and catalysts used in the oligomerization reaction, the composition of the dodecenes is complex and their properties are very different. Knowing the complex composition of dodecenes can help tune the production process and select the appropriate products according to their end use. To reveal the complex profile of dodecenes, an analytical method using two-dimensional gas chromatography (GC×GC) coupled photoionization (PI) - time of flight mass spectrometry (TOFMS) was developed in this study. A conventional (nonpolar × polar) column combination (non-polar column as 1 dimension and mid-polar column as 2 dimension) was selected. The analytical condition of GC was optimized using fractional factorial experimental design (DoE). Olefin congener grouping by carbon chain length and double bond equivalent (DBE) was achieved based on the detection of molecular ions by PI-TOFMS. Grouping of dodecenes by linear, mono-branched, di- and tri-branched subgroups was achieved based on branching index (BI) under the assumption of no retention time (RT) overlap among subgroups. Certain dodecene isomers were identified by retention index (RI) and further confirmed by PI mass spectra. The information altogether provided a multimodal characterization possibility to be used with statistical tools. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) of seventeen dodecene samples explained the composition variance between catalysts solid phosphoric acid and zeolite, as well as between feeds with C and without C.

摘要

商业十二烯是一种由多数 C 烯烃和少数 C 烯烃组成的复杂化学混合物。在结构上,十二烯产品可能由直链烯烃、支链烯烃以及环状烃组成。由于齐聚反应中使用的原料和催化剂的差异,十二烯的组成复杂,性质差异很大。了解十二烯的复杂组成可以帮助调整生产工艺,并根据其最终用途选择合适的产品。为了揭示十二烯的复杂分布,本研究开发了一种使用二维气相色谱(GC×GC)结合光电离(PI)-飞行时间质谱(TOFMS)的分析方法。选择了常规(非极性×极性)柱组合(非极性柱为一维,中极性柱为二维)。通过部分因子实验设计(DoE)优化了 GC 的分析条件。通过 PI-TOFMS 检测分子离子,实现了按碳链长度和双键等价物(DBE)分组的烯烃同系物分组。基于无保留时间(RT)重叠的假设,根据分支指数(BI)实现了十二烯的线性、单支、二支和三支亚组的分组。通过保留指数(RI)鉴定了某些十二烯异构体,并通过 PI 质谱进一步确认。这些信息共同提供了一种多模态特征化的可能性,可与统计工具一起使用。对十七个十二烯样品进行的主成分分析(PCA)和层次聚类分析(HCA)解释了固体磷酸和沸石催化剂之间以及含 C 和不含 C 原料之间的组成差异。

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