Determination of metal content in industrial powder ink and paint thickness over steel plates using X-Ray Fluorescence.

The Energy Dispersive X-Ray Fluorescence (EDXRF) is a well stablished technique that may be used in quality control of industrial processes. In this study, it was proposed an analysis of a two commercial powder inks widely used in the industry. The goals were to determine the composition of the ink by quantifying its inorganics elements by EDXRF, and check if the amount of toxic elements matches with Restriction of Certain Hazardous Substances (RoHS) and with "Norma Brasileira" (NBR) regulations. Moreover, to build Partial Least Squares Regression (PLSR) models to predict the thickness of the ink layer applied over steel plates using EDXRF data. Evaluating the quantitative results, it was found that some samples presented toxic elements, such as Cr and Pb. The PLSR results ranged from 54 µm to 97 µm with an average relative deviation of 1% compared to the conventional method used for thickness determination (magnetic method). The results show that EDXRF is a reliable alternative technique to determine the metal elements on the powder ink composition. Furthermore, a (PLSR) model can be used to determine the thickness of the ink applied over steel plates.

Modeling the soil burn effect for temperature prediction by energy dispersive X ray Fluorescence in an haplic cambisol soil.

Considered an important hydrological and geomorphological agent, fire can cause physical, chemical and biological changes in the soil. Besides wildfire, the study of fire effects is also related to traditional agriculture. This study presents the characterization and analysis of soil samples submitted to burn simulation with the objective to build a temperature prediction model in order to determine the maximum temperature reached by real soil burn samples. For this purpose, surface soil samples (0-2.5 cm) classified as Haplic Cambisol were collected from a native forest area close to the studied field. The temperature of the simulation samples ranged from 50 to 750 °C. Moreover, a real burn set of samples were measured for temperature prediction using the proposed model. The characterization and quantification of the chemical elements present in the soil were done by Energy Dispersive X-ray Fluorescence (EDXRF) measurements. Plots with Fe concentration and with the Rayleigh and Compton scattering data versus temperature were constructed. The Fe/Rh and Fe/RhC ratios resulted in relative deviations ranging from 14% to 22% using univariate analysis. Multivariate analysis was also applied through partial least squares regression (PLSR) method in four different spectrum regions. The best result was obtained for the model using the spectrum scattering region with r2 = 0.90 and relative deviation ranging from 8% to 25% for the predicted temperature. The use of local multivariate PLSR models improved the results when compared to the univariate regression results.

Quick analysis of organic matter in soil by energy-dispersive X-ray fluorescence and multivariate analysis.

The rapid, simple and accurate determination of soil quality indicators is fundamental for improvements in precision agriculture and consequently in production efficiency. The objectives of this study were to determine the organic matter (OM) and total organic carbon (TOC) concentrations in agricultural soil and to discriminate soil provenance by energy-dispersive X-ray fluorescence (EDXRF) combined with principal component analysis and partial least square regression. The conventional methods used for the determination of OM and TOC concentrations are the gravimetric and Walkley-Black methods, respectively. Figures of merit such as sensitivity, detection and quantification limits, accuracy and precision were evaluated. Samples were differentiated by their provenance, and the quality of the prediction model shows that EDXRF combined with multivariate analysis is a promising methodology to fulfil the lack of rapid and accurate analytical methods for the assessment of OM and TOC concentrations in agricultural soils.

Fast and direct Na and K determination in table, marine, and low-sodium salts by X-ray fluorescence and chemometrics.

X-ray fluorescence (XRF) is a fast, low-cost, nondestructive, and truly multielement analytical technique. The objectives of this study are to quantify the amount of Na(+) and K(+) in samples of table salt (refined, marine, and light) and to compare three different methodologies of quantification using XRF. A fundamental parameter method revealed difficulties in quantifying accurately lighter elements (Z < 22). A univariate methodology based on peak area calibration is an attractive alternative, even though additional steps of data manipulation might consume some time. Quantifications were performed with good correlations for both Na (r = 0.974) and K (r = 0.992). A partial least-squares (PLS) regression method with five latent variables was very fast. Na(+) quantifications provided calibration errors lower than 16% and a correlation of 0.995. Of great concern was the observation of high Na(+) levels in low-sodium salts. The presented application may be performed in a fast and multielement fashion, in accordance with Green Chemistry specifications.

X-ray fluorescence and gamma-ray spectrometry combined with multivariate analysis for topographic studies in agricultural soil.

Physical and chemical properties of soils play a major role in the evaluation of different geochemical signature, soil quality, discrimination of land use type, soil provenance and soil degradation. The objectives of the present study are the soil elemental characterization and soil differentiation in topographic sequence and depth, using Energy Dispersive X-Ray Fluorescence (EDXRF) as well as gamma-ray spectrometry data combined with Principal Component Analysis (PCA). The study area is an agricultural region of Boa Vista catchment which is located at Guamiranga municipality, Brazil. PCA analysis was performed with four different data sets: spectral data from EDXRF, spectral data from gamma-ray spectrometry, concentration values from EDXRF measurements and concentration values from gamma-ray spectrometry. All PCAs showed similar results, confirmed by hierarchical cluster analysis, allowing the data grouping into top, bottom and riparian zone samples, i.e. the samples were separated due to its landscape position. The two hillslopes present the same behavior independent of the land use history. There are distinctive and characteristic patterns in the analyzed soil. The methodologies presented are promising and could be used to infer significant information about the region to be studied.