研究目的
Simultaneous quantitation of six organic environmental pollutants using third-order liquid chromatographic data with native and photoinduced fluorescence detection.
研究成果
The work reports a novel strategy to obtain online third-order chromatographic data for the simultaneous quantitation of fluorescent analytes and those with fluorescent photoproducts. The method represents a better alternative than both univariate- and second-order calibration and is a new example of the power and applicability of high-order calibration in complex systems, maintaining the principles of green analytical chemistry.
研究不足
The study discusses the challenges presented by the selected system within the framework of green analytical chemistry, including the simultaneous quantitation of pollutants with different spectroscopic properties and the optimization of experimental conditions considering the analytical goals.
1：Experimental Design and Method Selection:
The strategy involved reducing the linear flow rate at the column outlet to generate third-order liquid chromatographic data online. A postcolumn UV reactor and a fluorimetric detector were used to record photoinduced and native excitation?emission fluorescence matrices.
2：Sample Selection and Data Sources:
Natural water samples were tested as real matrices. The sensitivity of the method was enhanced by a simple solid-phase extraction with C18 membranes.
3：List of Experimental Equipment and Materials:
Agilent 1200 liquid chromatograph, Restek Pinnacle II-C8 column, PTFE tubing, 8 W germicide UV lamp, Agilent Cary-Eclipse luminescence spectrometer.
4：Experimental Procedures and Operational Workflow:
Chromatographic analysis was performed using a mixture of 20 mmol L?1 of sodium acetate/acetic acid buffer pH 5.5 and ACN as mobile phase. An elution gradient program was employed.
5：5 and ACN as mobile phase. An elution gradient program was employed.
Data Analysis Methods:
5. Data Analysis Methods: The obtained third-order liquid chromatography data were chemometrically processed with the multivariate curve resolution?alternating least-squares model.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
