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In order to deal with the matrix effect in the simultaneous determination of multi-components in a complex system, we have developed a novel method named matrix coefficient multivariate calibration method (MCMCM) for simultaneously determining n analytes in complex systems. The calibration models of n analytes, which are based on the experimental data of known samples, are first transformed into n linear equations, and then the equations are solved to obtain matrix calibration coefficients of the analytes in congeneric samples. In this way, the concentrations of n analytes in the unknown sample could be obtained easily and simultaneously by solving another n-variate linear equations with the help of the matrix calibration coefficients obtained-above. The method proposed in this work has been tested by voltammetry and atomic absorption spectrometry (AAS) with satisfactory results. On determining the elements such as Cu, Pb, Cd, Ni, Zn, Fe, Mn, Co, Ca, Mg, etc. in synthetic samples, the relative standard deviations (RSDs) of the results were 0.91 - 4.5%, and the recoveries were 95.8 - 105%. For actual samples, the RSDs and the recoveries were 1.5 - 6.9 and 92.0 - 110%, respectively.

analytical sciences

Elimination of Matrix Effect and Simultaneous Determination of Multi-components in Complex Systems by Matrix Coefficient Non-linearity Multivariate Calibration Based on Single Point Response Signals