A model for the calculation of theoretical intensities in X-ray fluorescence obtained by the limit dilution method and for the elimination of the matrix effect

1994 ◽  
Vol 49 (6) ◽  
pp. 607-614 ◽  
Author(s):  
F.Bosch Reig ◽  
V.Peris Martínez ◽  
J.V.Gimeno Adelantado ◽  
F.Bosch Mossi
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

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 ◽  
...  

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.


1968 ◽  
Vol 12 ◽  
pp. 546-562
Author(s):  
R. Tertian

AbstractThe double dilution method has many important advantages. For any element to be determined, let us say A, It enables us to control or calculate the matrix factor (sum of the absorption end enhancement effects) for the sample being Investigated towards A radiation, and it furnishes corrected Intensities which are strictly proportional to A concentration. Thus the results are exact, whatever the general composition of the sample, their accuracy depending only on the quality of measurement and preparation. Another major practical advantage is that the method does not require systematic calibration but only a few permanent standards consisting of a pure compound or of an accurately known sample.The procedure has been tested successfully for accurate determination of rare earth elements using, for solid materials such as ores and oxide mixtures, the borax fusion technique. It also can be readily applied to liquids. All the rare earth elements can be titrated by that method, as well as yttrium, thorium and, if necessary, all the elements relevant to X-ray fluorescence analysis. The concentration range considered for solids is of one comprised between 0.5 and 100 % and, with a lesser accuracy, between 0.1 and 0-5 % Examples are given relative to the analysis of various ores. Finally it rcust be pointed out that the method is universal and applies to the analysis of every solid, especially ores, provided that they can be converted to solid or liquid solutions. It appears that most industrial analyses can be worked on In this way.


2018 ◽  
Vol 788 ◽  
pp. 108-113
Author(s):  
Anna Trubaca-Boginska ◽  
Andris Actins ◽  
Ruta Švinka ◽  
Visvaldis Švinka

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.


1992 ◽  
Vol 344 (1-2) ◽  
pp. 16-21 ◽  
Author(s):  
F. Bosch Reig ◽  
V. Peris Martinez ◽  
F. Bosch Mossi ◽  
J. V. Gimeno Adelantado

1994 ◽  
Vol 23 (2) ◽  
pp. 53-58 ◽  
Author(s):  
M. T. Doménech Carbó ◽  
F. Bosch Reig ◽  
J. V. Gimeno Adelantado ◽  
V. Peris Martinez

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 ◽  
...  

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).


1992 ◽  
Vol 344 (1-2) ◽  
pp. 22-26 ◽  
Author(s):  
F. Bosch Reig ◽  
F. Bosch Mossi ◽  
V. Peris Martinez ◽  
J. V. Gimeno Adelantado

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