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MDGC技术的发展历程:从经典多维气相色谱到全二维气相色谱

Continuum in MDGC Technology: From Classical Multidimensional to Comprehensive Two-Dimensional Gas Chromatography.

作者信息

Kulsing Chadin, Nolvachai Yada, Rawson Paul, Evans David J, Marriott Philip J

机构信息

Australian Centre for Research on Separation Science, School of Chemistry, Monash University , Wellington Road, Clayton, Victoria 3800, Australia.

Defence Science and Technology Group, 506 Lorimer Street, Fishermans Bend, Victoria 3207, Australia.

出版信息

Anal Chem. 2016 Apr 5;88(7):3529-38. doi: 10.1021/acs.analchem.5b03839. Epub 2016 Mar 22.

Abstract

Recent advances in multidimensional gas chromatography (MDGC) comprise methods such as multiple heart-cut (H/C) analysis and comprehensive two-dimensional gas chromatography (GC × GC); however, clear approaches to evaluate the MDGC results, choice of the most appropriate method, and optimized separation remain of concern. In order to track the capability of these analytical techniques and select an effective experimental approach, a fundamental approach was developed utilizing a time summation model incorporating temperature-dependent linear solvation energy relationship (LSER). The approach allows prediction of optimized analyte distribution in the 2D space for various MDGC approaches employing different experimental variables such as column lengths, temperature programs, and stationary phase combinations in order to evaluate separation performance (apparent (1)D, (2)D, total number of separated peaks, and orthogonality) for simulated MDGC results. The methodology applied LSER to generate results for nonpolar-polar and polar-nonpolar 2D column configurations for separation of 678 compounds in an oxidized kerosene-based jet fuel sample. Three-dimensional plots were generated in order to illustrate the dependency of separation performance on (2)D column length and number of injections for different stationary phase combinations. With a given limit of analysis time, a MDGC approach to obtain an optimized total separated peak number for a particular column set was proposed depending on (1)D and (2)D analyte peak distribution. This study introduces fundamental concepts and establishes approaches to design effective GC × GC or multiple H/C systems for different column combinations, to provide the best overall separation outcomes with the highest separated peak number and/or orthogonality.

摘要

多维气相色谱法(MDGC)的最新进展包括多种方法,如多中心切割(H/C)分析和全二维气相色谱法(GC×GC);然而,评估MDGC结果的明确方法、最合适方法的选择以及优化分离仍然是令人关注的问题。为了追踪这些分析技术的能力并选择有效的实验方法,开发了一种基本方法,该方法利用了包含温度依赖性线性溶剂化能关系(LSER)的时间求和模型。该方法能够预测在采用不同实验变量(如柱长、温度程序和固定相组合)的各种MDGC方法中,分析物在二维空间中的优化分布,以便评估模拟MDGC结果的分离性能(表观一维、二维、分离峰总数和正交性)。该方法应用LSER生成了用于非极性-极性和极性-非极性二维柱配置的结果,以分离基于氧化煤油的喷气燃料样品中的678种化合物。生成了三维图,以说明不同固定相组合下分离性能对二维柱长和进样次数的依赖性。在给定的分析时间限制下,根据一维和二维分析物峰分布,提出了一种MDGC方法,以获得特定柱组的优化总分离峰数。本研究引入了基本概念,并建立了针对不同柱组合设计有效的GC×GC或多H/C系统的方法,以提供具有最高分离峰数和/或正交性的最佳整体分离结果。

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