Control of matrix interferences by the multiple linear regression model in the determination of arsenic, antimony and tin in lead pellets by inductively coupled plasma atomic emission spectrometry

Abstract

A multiple linear regression technique was used to evaluate the matrix interferences in the determination of hydride-forming elements in lead shotgun pellets by inductively coupled plasma atomic emission spectrometry. The determination of arsenic, antimony, and tin in SRM C2416 (Bullet Lead) by ICP-AES failed to obtain the certified concentrations at the 95% level of confidence using the t-test. However, it proved possible, by using the multiple linear regression technique, to correct the concentrations of all three elements to a statistically acceptable level. This method of correction is based on the multiple regression line obtained from the analysis of 19 synthetic mixtures of matrix elements (arsenic, antimony, bismuth, copper, silver, and tin) in five levels of concentrations. The direct determination of bismuth, copper and silver in SRM C2416 was performed with high accuracy and precision (RSD < 2.2%) as was the determination of arsenic, antimony, and tin after the correction. Total element recovery varied from 95.6% to 101.8% in the SRM sample analyzed.