Correction method for the matrix effect in x-ray fluorescence spectrometric analysis

1998 ◽  
Vol 27 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Binghe Tan ◽  
Weiying Sun
Keyword(s):  
Matrix Effect ◽  
Correction Method ◽  
Spectrometric Analysis ◽  
X Ray ◽  
The Matrix

Substitution–dilution method to correct the matrix effect in multi-element quantitative analysis by X-ray fluorescence

2001 ◽  
Vol 56 (2) ◽  
pp. 187-201 ◽  
Author(s):  
F Bosch-Reig ◽  
J.V Gimeno-Adelantado ◽  
S Sánchez-Ramos ◽  
D.J Yusá-Marco ◽  
F Bosch-Mossi
Keyword(s):  
Quantitative Analysis ◽  
Matrix Effect ◽  
Dilution Method ◽  
X Ray ◽  
The Matrix

The Matrix Effect and Application of the Multi-Parameter Optimization Method for X-Ray Spectrometric Determination of the Quantitative Composition of Clays

2018 ◽  
Vol 788 ◽  
pp. 108-113
Author(s):  
Anna Trubaca-Boginska ◽  
Andris Actins ◽  
Ruta Švinka ◽  
Visvaldis Švinka
Keyword(s):  
Chemical Composition ◽  
Parameter Optimization ◽  
Matrix Effect ◽  
Standard Addition ◽  
Optimization Method ◽  
Quantitative Composition ◽  
Parameter Method ◽  
X Ray ◽  
Influence Coefficients ◽  
The Matrix

Determining the quantitative composition of clay samples with X-ray fluorescent spectrometry is complicated because of the matrix effect, in which any element can increase or decrease the analytical signals of other elements. In order to predict the properties of clays, it is essential to know their precise chemical composition. Therefore, using the standard addition method was determined calibration and empirical influence coefficients, as well as the true composition of the elements. Farther, these coefficients were used to correct the matrix effect and develop a multi-parameter optimization method. It was determined that in clay samples, consisting of Si, Al, Fe, K, Mg, Ca, Na and Ti oxide formula units, the most significant contribution for matrix effect correction calculations was from the calibration coefficients. Moreover, the largest deviation from the X-ray fluorescent data and true values was determined in the MgO and Na2O cases. In this study was established, that the developed multi-parameter method can be successfully applied to determine the quantitative chemical composition of clay samples of similar compositions.

Quantitative Analysis of LIBS Reduces the Matrix Effect Methods

2013 ◽  
Vol 313-314 ◽  
pp. 579-582
Author(s):  
You Liang Yang ◽  
Jun Xiang Li ◽  
Fan Wei Meng ◽  
Cui Hong Ma
Keyword(s):  
Quantitative Analysis ◽  
Matrix Effect ◽  
Correction Method ◽  
Analysis Method ◽  
Network Reduction ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown ◽  
The Matrix ◽  
Quantitative Analysis Method ◽  
The Impact

This paper introduced the principle about the technology of Laser-induced Breakdown Spectroscopy (LIBS) of quantitative analysis. It was reviewed about the quantitative analysis of LIBS reduced method of matrix. The reason of cause matrix effect was not clear, but the matrix effect on the LIBS quantitative analysis of the impact can not be ignored. The LIBS quantitative analysis method was divided into two categories: one was based on the calibration curve with the mathematical matrix correction method; the other was combined with neural network reduction method of matrix. This paper was introduced for the two categories of methods, and gives an example to explain.

Some Features of Quantitative Analysis of Rock-Forming Minerals Using a JXA-8230 Electron Probe Microanalyzer

2021 ◽  
Vol 62 (11) ◽  
pp. 1209-1213
Author(s):  
Yu.G. Lavrent’ev ◽  
L.V. Usova
Keyword(s):  
Quantitative Analysis ◽  
Theoretical Data ◽  
Correction Method ◽  
Positive Influence ◽  
Analytical Line ◽  
X Ray ◽  
Electron Probe Microanalyzer ◽  
The Matrix ◽  
Isomorphic Series ◽  
Atomic Electrons

Abstract —The basic software package of a JXA-8230 microanalyzer, like its predecessor JXA-8100, uses the long-established ZAF correction method (with some differences) for a quantitative analysis: Calculation of mass absorption coefficients is based on Chantler’s theoretical data. The core of this method is quantum-mechanical calculation of the cross section of the interaction between an X-ray photon and atomic electrons. This innovation has had a positive influence on the trueness of X-ray microanalysis. Control tests on specimens where the absorption effect is dominant have demonstrated that the results of this analysis are slightly lower (by less than 2%) independently of the matrix absorption interval in which the analytical line is located. As a consequence, the selection of comparison specimens becomes easier: It is sufficient that the specimen under study and the comparison specimen belong to the same isomorphic series and that the intensity of the analytical line of the comparison specimen allows for the measurement with the required accuracy.

Correction of Matrix Effect in Multielemental Quantitative Analysis by X-Ray Fluorescence Spectroscopy Using the Linear Behavior in the Analytical Range of the Substitution-Dilution Method

2002 ◽  
Vol 56 (1) ◽  
pp. 58-61
Author(s):  
F. Bosch-Reig ◽  
J. V. Gimeno-Adelantado ◽  
S. Sánchez-Ramos ◽  
D. J. Yusá-Marco ◽  
F. Bosch-Mossi ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Matrix Effect ◽  
Linear Range ◽  
Factor H ◽  
Dilution Method ◽  
X Ray ◽  
Linear Behavior ◽  
Relative Standard ◽  
The Matrix ◽  
Analytical Range

This paper is an analytical study of the possibility of applying the linear range of the substitution-dilution method to correct the matrix effect in quantitative analysis by X-ray fluorescence (XRF) spectroscopy. The analytical range is obtained from a series of samples prepared in the form of glass discs by substituting the unknown sample with a standard sample (substitution factor, h) including a diluent-melt. In general, the substitution-dilution method is hyperbolic in character and therefore the diluent is required to ensure linear behavior between If vs. h in the experimental range. The linear range is located between the concentrations of standard and unknown for each element analyzed. This linear model makes it possible to correct the matrix effect in quantitative analysis by XRF using a single multi-elemental standard for different types of samples with a complex matrix, such as geologicals and cements. The results found for Si, Ti, Al, Fe, Mn, Ca, K, and P in soil and sediment samples and Si, Fe, Al, Ca, and K in cements (white and gray) are statistically satisfactory. Thus, the mean relative standard deviation calculated for all analytes in each sample was: ±4.0% and ±5.0% in soils; ±5.0% in sediments; and ±6.0% or ±3.0% in cements, white and gray, respectively.

scholarly journals Assessing Soil Key Fertility Attributes Using a Portable X-ray Fluorescence: A Simple Method to Overcome Matrix Effect

Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 787 ◽  
Author(s):  
Tiago Rodrigues Tavares ◽  
Abdul Mounem Mouazen ◽  
Elton Eduardo Novais Alves ◽  
Felipe Rodrigues dos Santos ◽  
Fábio Luiz Melquiades ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Matrix Effect ◽  
Prediction Accuracy ◽  
Matrix Effects ◽  
Soil Samples ◽  
Least Squares Regression ◽  
Simple Method ◽  
Soil Matrix ◽  
X Ray ◽  
The Matrix

The matrix effect is one of the challenges to be overcome for a successful analysis of soil samples using X-ray fluorescence (XRF) sensors. This work aimed at evaluation of a simple modeling approach consisted of Compton normalization (CN) and multivariate regressions (e.g., multiple linear regressions (MLR) and partial least squares regression (PLSR)) to overcome the soil matrix effect, and subsequently improve the prediction accuracy of key soil fertility attributes. A portable XRF was used for analyzing 102 soil samples collected from two agricultural fields with contrasting soil matrices. Using the intensity of emission lines as input, preprocessing methods included with and without the CN. Univariate regression models for the prediction of clay, cation exchange capacity (CEC), and exchangeable (ex-) K and Ca were compared with the corresponding MLR models to assess matrix effect mitigation. The MLR and PLSR models improved the prediction results of the univariate models for both preprocessing methods, proving to be promising strategies for mitigating the matrix effect. In turn, the CN also mitigated part of the matrix effect for ex-K, ex-Ca, and CEC predictions, by improving the predictive performance of these elements when used in univariate and multivariate models. The CN has not improved the prediction accuracy of clay. The prediction performances obtained using MLR and PLSR were comparable for all evaluated attributes. The combined use of CN with multivariate regressions (MLR or PLSR) achieved excellent prediction results for CEC (R2 = 0.87), ex-K (R2 ≥ 0.94), and ex-Ca (R2 ≥ 0.96), whereas clay predictions were comparable with and without CN (0.89 ≤ R2 ≤ 0.92). We suggest using multivariate regressions (MLR or PLSR) combined with the CN to remove the soil matrix effects and consequently result in optimal prediction results of the studied key soil fertility attributes. The prediction performance observed for this solution showed comparable results to the approach based on the preprogrammed measurement package tested (Geo Exploration package, Bruker AXS, Madison, WI, USA).

scholarly journals Correction method for matrix effect in fluorescent X-ray analysis of high-alloy steels

1967 ◽  
Vol 16 (4) ◽  
pp. 299-303
Author(s):  
Nobuhisa MATANO ◽  
Katsumi ONO ◽  
Hideo SENO
Keyword(s):  
Matrix Effect ◽  
Correction Method ◽  
High Alloy ◽  
X Ray ◽  
Alloy Steels ◽  
High Alloy Steels
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