ABSTRACT
Classical calibration and inverse calibration are two kinds of multivariate calibration in chemical modeling. They use strategies of modeling in component spectral space and in measured variable space, respectively. However, the intrinsic difference between these two calibration models is not fully investigated. Besides, in the case of complex analytical systems, the net analyte signal (NAS) cannot be well defined in inverse calibration due to the existence of uninformative and/or interfering variables. Therefore, application of the NAS cannot improve the predictive performance for this kind of calibration, since it is essentially a technique based on the full-spectrum. From our perspective, variable selection can significantly improve the predictive performance through removing uninformative and/or interfering variables. Although the need for variable selection in the inverse calibration model has already been experimentally demonstrated, it has not aroused so much attention. In this study, we first clarify the intrinsic difference between these two calibration models and then use a new perspective to intrinsically prove the importance of variable selection in the inverse calibration model for complex analytical systems. In addition, we have experimentally validated our viewpoint through the use of one UV dataset and two generated near infrared (NIR) datasets.
ABSTRACT
A numerical model is developed to describe the separation process of countercurrent chromatography (CCC) in this work. The theory of countercurrent extraction table (TCCET) is first proposed to calculate concentration distributions of chemical components in the CCC, which is essential for a numerical model to describe the dynamic equilibrium of mass transfer. According to the theory of countercurrent extraction, the concentration in chromatography obeys binomial distribution, while the outflow from the n-th stage is a negative binomial distribution. As a result of the central limit theorem, they will obey normal distribution for sufficiently large n. Row-stage ratio (R(RS)) is then defined to determine the K value or retention time because it has a linear relationship to K value and retention time. The stage for a certain K value can be subsequently obtained with a very simple form, n(k)=1/(2piq(k)X(2)(k, max)), which can be calculated from the peak height obtained from experiments. Finally, the actual stage for a separation chromatogram can be acquired with using this simple expression. The agreement between theoretic and experimental results is quite satisfactory in the normal-phase and reversed-phase elution mode.
