A STUDY CHARACTERISTICS AND DETECTION OF METALS ION IN AQUEOUS SOLUTION BY NEAR INFRARED SPECTRA AREA

Abstract

This study was focused on detection of Magnesium (Mg,) Zinc (Zn), Cadmium (Cd) and Manganese (Mn) as minerals in aqueous solution using Near Infrared Spectroscopy (NIRS) and chemo metrics. Although detectable, minerals have no absorption in NIR region, but alteration of the vibration mode of water matrix caused by minerals can be detected by NIRS. Artificial samples used in this research were contained metal diluted in aqueous solutions. Analyses were performed in the 680-1090 nm and 1110-1800 nm region and were subjected to a partial least-square (PLS) regression analysis; validation was performed by mean center and transformed by smoothing. The metals were scanned by NIR System 6500 using cuvette cell with 2 mm path length, in three consecutive days. Data for two days were used as data set and the rest of the data were used as prediction set. The calibration and prediction statistics obtained in this study indicated the potential of NIRS to predict Metals in aqueous solution with correlation coefficient (R2_pred. > 0.7). The RPD (residual predictive deviation) or ratio of standard error of prediction to the standard deviation, values were greater than 2, indicating that the model is appropriate for practical use. These results showed that the PLS model were able to detect metal ions in the NIR region of electromagnetic spectra with high accuracy even at low concentrations (0 -10 ppm). PLS model provided a powerful tool for investigation of the vibration and interaction of a mineral with water.