On the fractionation of lignin oligomers by stepwise gradient reversed-phase liquid chromatography

被引:0
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作者
Papp, Daniel [1 ]
Sandahl, Margareta [1 ]
机构
[1] Lund University, Department of Chemistry, Centre for Analysis and Synthesis, P.O. Box 124, Lund,SE-22100, Sweden
关键词
Chromatographic analysis - Fractionation - Gas chromatography - Liquid chromatography - Supercritical fluid extraction;
D O I
10.1016/j.chroma.2024.465458
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学科分类号
摘要
With the increased interest in lignin valorization, the analytical challenge to separate a complex mixture of a vast number of phenolics has made chromatography an indispensable step in lignin analysis. High-resolution separations, such as gas chromatography, reversed-phase liquid chromatography and supercritical fluid chromatography have typically been targeting low-molecular-weight compounds, while larger lignin oligomers have received less attention. These compounds have proven to be difficult to separate due to the inherent complexity of the high-molecular-weight fraction of lignins, in fact, even high-resolving linear reversed-phase gradients elute them as one wide zone. To tackle this, in this study we show that a crude fractionation of lignin oligomers can be achieved by applying stepwise reversed-phase gradients. A commonly employed reversed-phase system with water:acetonitrile mobile phase is evaluated for this task. Special attention was devoted to uncovering the molecular level explanation of the retention phenomenon. Our results indicate that separation is mainly governed by reversed-phase retention phenomena without any major exclusion or viscosity-related effects, shown by great fits to linear retention models (R2avg = 0.9599 for five different oligomers) and apparent differences in retentivity between different stationary phases. The influence of the gradient shape was demonstrated by the comparison of stepwise gradients with different number and frequency of steps, leading to the conclusion that gradients with a low number of steps yield fewer, but better resolved fractions, while finer multi-step gradients can be used to distinguish more fractions. © 2024 The Authors
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