STUDY OF A PARTIAL LEAST-SQUARES REGRESSION-MODEL FOR RARE-EARTH ELEMENT DETERMINATION BY INDUCTIVELY-COUPLED PLASMA-MASS SPECTROMETRY

A partial least-squares regression (PLSR) model was developed for rare earth element (REE) determination by inductively coupled plasma mass spectrometry (ICP-MS), in order to correct interferences from REE oxid es, hydroxides and isobaric spectral overlap, The total variance was e xplained by a 14 factor PLSR model, The square error of prediction was less than 0.005 and the oxide/hydroxide/isobaric interferences were a lmost completely removed, It was found that Nd, Sm, Gd, Dy and Yb play ed a more significant role in the model than the other REEs because th ey possess multiple isotopes which require repeated calibration, REE c oncentrations could be accurately predicted despite barium interferenc e, even in samples with high ratios of Ba to REE, when the weights of certain isotopes in the model were set below 0.1, The PLSR model was c ompared with the normal calibration method (NCM) and the Gauss elimina tion method (GEM), The results indicated that the PLSR model was more accurate than the NCM and exhibited greater flexibility than the GEM.