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.
Highlights
Portable X-ray fluorescence spectrometry offers some unique advantages in chemical composition analysis, which arise from the multi-element capability, the nondestructive nature and the immediate availability to the researcher of information on the chemical composition of a sample in the field [1]
The Portable X-ray fluorescence spectrometry (pXRF) analysis results and reference values of the samples are shown in Tables S1 and S2, respectively
16 certified reference materials were determined by pXRF analysis, and major elements were used to calibrate the analysis results with the application of multiple linear regression analysis
Summary
Portable X-ray fluorescence spectrometry (pXRF) offers some unique advantages in chemical composition analysis, which arise from the multi-element capability, the nondestructive nature and the immediate availability to the researcher of information on the chemical composition of a sample in the field [1]. This technique is characterized by decreased production of hazardous waste and low running costs [2]. The matrix effect that occurs in pXRF analysis generally has a heavy influence on the quality of the analysis results, especially for trace elements [7]. Matrix effect correction has been the focus of much attention, and many correction methods have been put forward from different points of view [10]
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