István Krisztina, Rajkó Róbert, Keresztury Gábor
Chemical Research Center, Hungarian Academy of Sciences, P.O. Box 17, H-1525 Budapest, Hungary.
J Chromatogr A. 2006 Feb 3;1104(1-2):154-63. doi: 10.1016/j.chroma.2005.11.131. Epub 2005 Dec 27.
The high-performance liquid chromatography-infrared spectroscopy (HPLC-IR) technique utilizing on-line flow through cell (FTC) detection has an inherent practical problem: strong absorption bands of the eluent may mask valuable analytical regions of the IR spectrum. The experimentalists' answer to this challenge is physical elimination of the chromatographic eluent before spectroscopic detection, which however results in off-line measurement of spectra. In the present work, the capabilities of some chemometric algorithms using iteratively applied multi-way methods such as parallel factor analysis (PARAFAC) and PARAFAC2, developed with the aim of overcoming the problems of eluent elimination are examined and evaluated. Test calculations done on simulated liquid chromatographic infrared (LC-IR) data cubes have shown that although PARAFAC2 performs much better than the simple PARAFAC method, it does not give correct decompositions, just like multivariate curve resolution with alternative least squares (MCR-ALS) and related bilinear data based methods. In search for a better solution, a method named objective subtraction of solvent spectrum with iterative use of PARAFAC and PARAFAC2 (OSSS-IU-PARAFAC and OSSS-IU-PARAFAC2) has been developed. Calculations performed with the corresponding Matlab program developed by the authors and run with the appropriate functions in PLS_Toolbox yielded very promising results in evaluations of both simulated and real HPLC-IR data sets, after necessary data pretreatments.
利用在线流通池(FTC)检测的高效液相色谱 - 红外光谱(HPLC - IR)技术存在一个固有的实际问题:洗脱液的强吸收带可能会掩盖红外光谱中有价值的分析区域。实验人员应对这一挑战的方法是在光谱检测之前对色谱洗脱液进行物理去除,然而这会导致光谱的离线测量。在本工作中,研究并评估了一些化学计量学算法的能力,这些算法使用诸如平行因子分析(PARAFAC)和PARAFAC2等迭代应用的多向方法,旨在克服洗脱液去除问题。对模拟液相色谱红外(LC - IR)数据立方体进行的测试计算表明,尽管PARAFAC2的性能比简单的PARAFAC方法好得多,但它并不能给出正确的分解结果,就像交替最小二乘法多元曲线分辨(MCR - ALS)和基于相关双线性数据的方法一样。为了寻找更好的解决方案,开发了一种名为用PARAFAC和PARAFAC2迭代使用进行溶剂光谱目标扣除(OSSS - IU - PARAFAC和OSSS - IU - PARAFAC2)的方法。在进行必要的数据预处理后,使用作者开发的相应Matlab程序并结合PLS_Toolbox中的适当函数运行,对模拟和实际HPLC - IR数据集进行评估时,计算结果非常有前景。