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首页> 外文期刊>Macromolecular theory and simulations >Randomly-Branched Polymers by Size Exclusion Chromatography with Triple Detection: Computer Simulation Study for Estimating Errors in the Distribution of Molar Mass and Branching Degree
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Randomly-Branched Polymers by Size Exclusion Chromatography with Triple Detection: Computer Simulation Study for Estimating Errors in the Distribution of Molar Mass and Branching Degree

机译：通过尺寸排阻色谱三重检测随机分支聚合物：估算摩尔质量分布和支化度误差的计算机模拟研究

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摘要

This article theoretically evaluates the biases introduced into the distributions of molar masses (MMD) and number of long chain branches per molecule (LCBD), when randomlybranched polymers are analyzed by size exclusion chromatography (SEC) with molar masssensitive detectors. The MMD of a polymer with tetrafunctional branch units is simulated under ideal SEC, i.e., θ-solvent, perfect measurements, and perfect fractionation by hydrodynamic volume except for a minor mixing in the detector cells. A negligible bias is introduced into the MMD, even when including band broadening in the columns. In contrast, poor MMD estimates are obtained when the chromatograms are contaminated with additive noise. Only qualitative estimates of the LCBD are possible.
机译：当使用摩尔质量敏感检测器通过尺寸排阻色谱法（SEC）分析随机支链聚合物时，本文从理论上评估了摩尔质量分布（MMD）和每分子长链分支数（LCBD）引入的偏差。具有四官能分支单元的聚合物的MMD是在理想的SEC（即θ溶剂），理想的测量结果和理想的流体动力学体积分馏条件下进行模拟的，除了在检测器单元中的微小混合之外。即使在列中包括谱带展宽时，也可以将忽略不计的偏差引入MMD。相反，当色谱图被附加噪声污染时，MMD估计值将很低。仅对LCBD进行定性评估。

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