首页> 外文期刊>Journal of Fluorescence >The use of poly(sodium N-undecanoyl-L-leucylvalinate), poly(sodium N-undecanoyl-L-leucinate) and poly(sodium N-undecanoyl-L-valinate) surfactants as chiral selectors for determination of enantiomeric composition of samples by multivariate regression
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The use of poly(sodium N-undecanoyl-L-leucylvalinate), poly(sodium N-undecanoyl-L-leucinate) and poly(sodium N-undecanoyl-L-valinate) surfactants as chiral selectors for determination of enantiomeric composition of samples by multivariate regression

机译:聚(N-十一烷酰基-L-亮氨酸缬氨酸钠),聚(N-十一烷酰基-L-亮氨酸丙氨酸钠)和聚(N-十一烷酰基-L-缬氨酸钠)表面活性剂作为手性选择剂的测定样品的对映体组成多元回归

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摘要

Steady-state fluorescence spectroscopy was employed to investigate the use of chiral polymeric surfactants as chiral selectors in chiral analysis by multivariate regression modeling of spectral data. Partial-least-squares regression modeling (PLS-1) was used to correlate changes in the fluorescence spectral data of 1,1'-bi-2-naphthol (BOH), 1,1'-binaphthyl-2,2'-diamine (BNA), or 2,2,2-trifluoroanthrylethanol (TFA) in the presence of poly(sodium N-undecanoyl-L-leucylvalinate), poly(sodium N-undecanoyl-L-leucinate) or poly(sodium N-undecanoyl-L-valinate) as the enantiomeric composition of the chiral analytes was varied. The regression models produced from the spectral data were validated by determining the enantiomeric composition of independently prepared test solutions. The ability of the model to correctly predict the enantiomeric composition of future samples was evaluated using the root-mean-square percent-relative error (RMS%RE) of prediction. In terms of RMS%RE, the ability of the model to accurately predict the enantiomeric composition of future samples was dependent on the chiral analyte, the polymeric surfactant used, and the surfactant medium, and ranged between 1.57 and 6.10%. Chiral analyte concentrations as low as 5x10(-6) M were found to give regression models with good predictability.
机译:通过对光谱数据进行多元回归建模,采用稳态荧光光谱研究手性聚合物表面活性剂作为手性选择剂在手性分析中的应用。偏最小二乘回归模型(PLS-1)用于关联1,1'-联-2-萘酚(BOH),1,1'-联萘-2,2'-二胺的荧光光谱数据变化(BNA)或2,2,2-三氟蒽乙醇(TFA)在聚(N-十一烷酰基-L-亮氨酰戊二酸钠),聚(N-十一烷酰基-L-亮氨酸钠)或聚(N-十一烷酰基-钠L-缬氨酸盐)作为手性分析物的对映体组成是变化的。通过确定独立制备的测试溶液的对映体组成,可以验证由光谱数据产生的回归模型。使用预测的均方根相对误差百分比(RMS%RE)评估模型正确预测未来样品的对映体组成的能力。在RMS%RE方面,模型准确预测未来样品的对映体组成的能力取决于手性分析物,所用的聚合物表面活性剂和表面活性剂介质,范围为1.57%至6.10%。发现手性分析物浓度低至5x10(-6)M,可以为回归模型提供良好的可预测性。

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