A Matrix Effect Correction Method for Portable X-ray Fluorescence Data

Abstract

Portable X-ray fluorescence spectrometry (pXRF) is an analytical technique that can be used for rapid and non-destructive analysis in the field. However, the testing accuracy and precision for trace elements are significantly affected by the matrix effect, which comes mainly from major elements that constitute most of the matrix of a sample. To solve this problem, many methods based on linear regression models have been proposed, but when extreme values or outliers occur, the application of these methods will be greatly affected. In this study, 16 certified reference materials were collected for pXRF analysis, and the major elements most closely related to the elements to be measured were employed as correction indicators to calibrate the analysis results through the application of multiple linear regression analysis. Some statistical parameters were calculated to evaluate the correction results. Compared with the calibration data obtained from simple linear regression analysis without taking major elements into account, those corrected by the new method were of higher quality, especially for elements of Co, Zn, Mo, Ta, Tl, Pb, Cd and Sn. The results show that the new method can effectively suppress the influence of the matrix effect.