Energy-dispersive X-ray Fluorescence Data Research Articles

Optimization of pXRF instrumentation conditions and multivariate modeling in soil fertility attributes determination

The increasing global demand for agricultural products, food, and energy requires a sustainable and secure approach to agricultural production. Soil nutrition is vital for enhancing agricultural productivity, and understanding the spatial variability of fertility attributes is crucial in soil fertility prevention. Traditional soil analysis methods are time-consuming, costly, and generate waste. Spectral-analytical techniques, such as energy dispersive X-ray fluorescence (EDXRF) combined with multivariate analysis, offer a faster, cost-effective, and environmentally friendly alternative. This study aimed to optimize measurement conditions for predicting soil fertility attributes using a commercial routine from a portable EDXRF (pXRF) equipment and compare its performance with benchtop EDXRF using Partial Least Squares Regression (PLS) modeling. The data fusion from different measurement conditions using low- and mid-level fusion approaches was explored to evaluate the models' synergy. 364 soil samples at three different depths were used. The study area covers 12 ha of Red Latosol and Red Nitosol. Ten fertility attributes were evaluated: exchangeable macronutrients (Ca2+, Mg2+, and K+), available phosphorus (PM), pH, potential acidity (H + Al), soil organic carbon (SOC), cation exchange capacity (CEC), sum of exchange bases (SB) and base saturation percentage (BSP). The results indicated that the measurement of the three experimental conditions tested is unnecessary, and the data fusion does not significantly improve the model's performance. The use of 15 kV and 12.15 μA without filters provided the best performance results for all attributes simultaneously. By the established RPD ranges, the SOC, CEC, SB, and Ca2+ models were considered very good for quantitative prediction (RPD >2.0), while the K+ and Mg2+ models were considered good for quantitative predictions (1.8 < RPD < 2.0). The PM, pH, BSP, and H + Al models provided fair predictions, which may be used for evaluation and correlation (RPD <1.8). Furthermore, the pXRF optimized condition provided results equivalent to those modeled with benchtop EDXRF data. These results highlight the potential of pXRF as an economical, rapid, and efficient alternative approach to the conventional method, and may provide valuable insight for decision-making related to the use of fertilizers and other soil correction products.

Energy dispersive X-ray fluorescence analysis to estimate the maximum temperature reached in burned soils from an Amazonian region.

Determining the maximum temperature reached in soil during burning is important when evaluating fire intensity. Forest conversion is an ongoing process in the Amazon ecosystem. It is of utmost importance to predict fire effects on soil properties and avoid damaging environmental systems. Spectroscopic methods combined with multivariate statistics may provide chemical and mineralogical information from soil. This study aims at predicting the maximum temperature reached in Oxisols from an Amazonian region in Brazil. Slash-and-burn and pasture samples collected after fire events and unburned forest soil samples submitted to heating (250-800°C) were investigated. Energy-dispersive X-ray fluorescence (EDXRF) was used to acquire chemical data. The experimental procedure is rapid and requires minimal sample preparation and no hazardous chemical reagents. The EDXRF data, combined with partial least squares regression, were applied in controlled-heated samples from five different sites of forest, pasture, and slash-and-burn areas. Estimated temperatures for burned samples ranged from 317 to 609°C. Considering the instrumental advantages and the achieved results, the use of EDXRF combined with multivariate analysis is a feasible alternative technology to evaluate fire effects in soil.

Energy-dispersive X-ray fluorescence combined with chemometric tools applied to tomato and sweet pepper classification

Consumers' interest in organic foods is increasing, and robust analytical tools are necessary to authenticate them. This study investigated the potential of Energy-Dispersive X-Ray Fluorescence (EDXRF) under two measurement conditions combined with chemometric tools to classify tomato and sweet pepper samples according to the agronomic production mode and geographical area cultivation. Initially, the Common Dimension Analysis (ComDim) was applied to 15 kV (Na–Sc) and 50 kV (Ti–U) EDXRF spectra to extract the common information generated by both spectral measurement conditions. According to the ComDim analysis, it was possible to verify that the data generated by both instrumental conditions are complementary. In contrast, it was impossible to cluster tomato or sweet pepper samples effectively according to the agronomic production mode or geographical origin. On the other hand, the junction between EDXRF data and Partial Least Squares with Discriminant Analysis (PLS-DA) proved to be a perfect match, reaching optimal prediction accuracy values for the classifications between 98.8 and 100.0%. These results suggest that EDXRF associated with chemometrics can be an excellent technique to verify the authenticity of tomato and sweet pepper. Besides, it does not require complex sample preparation steps and is fast and relatively inexpensive compared to some chromatographic or spectrometric analytical techniques.

Low-cost spectroscopic devices with multivariate analysis applied to milk authenticity

Milk is one of the main foods present in the human diet. It is a good source of many essential nutrients; however, milk is among the most adulterated food globally. This study investigated the potential of low-cost portable spectroscopy near-infrared (NIR) and energy-dispersive X-ray fluorescence (EDXRF) spectrometry combined with chemometric tools to discriminate authentic cow and goat milk from adulterated ones with whey. The common dimension (ComDim) multi-block analysis enabled us to verify that the EDXRF data had good discrimination between the samples. In contrast, the NIR spectra had no evident discrimination and showed a nonlinear behavior in their data. Both devices had equivalent classification performances of 98.4 to 100% accuracy for the prediction when combined with the appropriate algorithms, such as partial least squares discriminant analysis (PLS-DA) for EDXRF and C-support vector classification (C-SVC) for NIR. Discriminant methods have some limitations for authentication tasks, so class modeling methods such as data driven soft independent modeling of class analogy (DD-SIMCA) were more helpful for this problem, with a prediction accuracy greater than 98.9% for both devices. These results suggest that NIR and EDXRF can be reliably applied to verify milk authenticity. Besides, these devices are portable, cost-effective, user-friendly, fast, robust, do not require extensive sample preparations, and can be easily adapted to desired settings.

Comparison between energy dispersive X-ray fluorescence spectral data and elemental data for soil attributes modelling

Energy dispersive X-ray fluorescence (EDXRF) has been successfully applied for soil attribute prediction. Although, both spectral and elemental EDXRF data may be used in soil fertility attributes modelling, as far as we are concerned, there are no studies that compare the models performance using the two input possibilities. The objective of this study was to compare the performance of partial least squares regression models for soil fertility attributes prediction using different EDXRF inputs (spectral data and peak intensity data) by the evaluation of some figures of merit such as linearity, trueness, precision and robustness. The results show that the input EDXRF dataset type used in the modelling did not significantly interfere in the fertility attributes prediction, valid for the soils evaluated in the present work. However, the use of peak intensity data presented lack of linearity and robustness in some models. Moreover, the present study report relevant protocols for analytical validation in soil fertility attributes prediction when EDXRF data is applied.

Influence of soil sample grain size on energy dispersive X-ray fluorescence analysis: a comparative study case with three spectrometers

This study aims at evaluating the particle size influence on the quantitative Energy Dispersive X-ray Fluorescence data of tropical soils, as well as evaluating the results trueness and precision using different statistical approaches. These objectives were conducted in three spectrometers, a benchtop one, and two portable ones. Certified reference materials were employed in calibration and trueness evaluation. Soil samples were collected, grounded and sieved in particle sizes: macerated (>2 mm), <2, <0.7, <0.3, <0.125, and <0.06 mm. The three spectrometers had different performances and lack of trueness for Potassium and Zinc in the Lab-made spectrometer. Regarding the grain size parameters, the spectrometers responded in different ways. It was identified that the best soil grain size condition for one of the portable spectrometers was <0.06 mm, while for the benchtop and for the other portable spectrometer the best soil grain size was <0.125 mm. In summary, the soil grain size affected the quantitative results in Energy Dispersive X-ray Fluorescence measurements, but it depends on the sensitivity of each spectrometer and the element of interest.

Impurity in sugarcane juice as mineral content: A prospect for analysis using energy-dispersive X-ray fluorescence (EDXRF) and chemometrics

The juice extracted from sugarcane passes through several clarification stages before either sugar or ethanol production. These stages involve chemical addition to purify and clarify the juice, mainly when it is destined for sugar production. The addition of these chemicals can negatively impact the environment, causing soil and water contaminations, as main effects amidst others. Hence, these chemicals, products, and subproducts formed during the clarification stages, which become mineral impurity on the extracted juice, must be assessed. The key idea is the better control of the industrial production of these commodities – sugar and ethanol. Energy-dispersive X-ray fluorescence (EDXRF) presents itself as a high-analytical-frequency technique, with minimal sample preparation, without adding toxic chemicals in most cases. The results shown here is an initial exploratory study of the ability of partial least squares (PLS) to model EDXRF data for the estimation of Ca, Fe and K in sugarcane juices at different clarification stages. At first glance, this method may guide the proper use of chemical reagents towards the stages of sugarcane juice clarification for Ca (in four stages), Fe, and K (in seven stages) to reduce the environmental impact.

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.

Assessment of chemical elements in cosmetics' eyeshadows by X‐ray fluorescence and International Nomenclature of Cosmetic Ingredients characterization

Energy dispersive X‐ray fluorescence (EDXRF) technique, as a qualitative and quantitative analysis, was used for inorganic chemical elements determination (K, S, Cl, Al, Si, Ca, Ti, Mn, Fe, Pb, Zn, Rb, and Bi) in eyeshadows for safe human use. International Nomenclature of Cosmetic Ingredients standardized nomenclature was used for labels investigation to obtain data on legal regularity. Data of 23 samples were clustered by similarity, measuring relative concentrations of detected chemical elements. Calculating the correlation among such values, a similarity matrix was used to generate a dendrogram. Pb was found in samples silver color S12E and copper color S22I above permissible limits (20 μg/g). Same composition was reported for the pink (S01A), black (S02A), and brown (S03A) samples, but the same chemical elements were not detected by EDXRF in them. The best correlation was found between samples S08D and S23 J (0.961). The least correlation was 0.0012 between S01A and S12E. The clustering analysis showed 7 groups of similar samples according to EDXRF data. Relations among 6 eyeshadows' colors and chemical compositions were discovered by using decision trees, where the most determinant elements were Mn, S, Cl, Ca, and Fe, in this order. Commercial regularization and International Nomenclature of Cosmetic Ingredients standardization of eyeshadows in Brazil are not fully complied by the manufacturers of the investigated brands.

Compositional analysis of copper–silica precipitation tubes

Silica gardens consist of hollow tubular structures that form from salt crystals seeded into silicate solution. We investigate the structure and elemental composition of these tubes in the context of a recently developed experimental model that allows quantitative analyses based on predetermined reactant concentrations and flow rates. In these experiments, cupric sulfate solution is injected into large volumes of waterglass. The walls of the resulting tubular structures have a typical width of 10 microm and are gradient materials. Micro-Raman spectroscopy along with energy dispersive X-ray fluorescence data identify amorphous silica and copper(ii) hydroxide as the main compounds within the inner and outer tube surfaces, respectively. Upon heating the blueish precipitates to approximately 150 degrees C, the material turns black as copper(ii) hydroxide decomposes to copper(ii) oxide. Moreover, we present high resolution transmission electron micrographs that reveal polycrystalline morphologies.

Dithionite bleaching of thermomechanical pulp: factors having effects on bleaching efficiency

The efficiency of dithionite bleaching of Norway spruce (Picea abies) thermomechanical pulp was studied by applying various multivariate data analysis techniques to analytical data (temperature, pH, ion chromatographic and energy-dispersive X-ray fluorescence data). In addition, modeling the residual sulfur content of bleached pulp by means of diffuse reflectance UV-vis spectral data from laboratory-scale bleaching experiments was attempted. The results indicated that this lignin-preserving bleaching process could be evaluated by means of the analytical data using either PCR or PLS models. These models also indicated that wavelengths below 400 nm should not be used in measuring the pulp brightness. The residual sulfur content of pulp could not be reliably determined by multivariate modeling of the diffuse reflectance UV-vis spectral data. Copyright © 2000 John Wiley & Sons, Ltd.

Coprecipitative Preconcentration and X-Ray Fluorescence Determination of Rare Earths Based On Characteristic K-Radiation

Abstract This paper describes a method for the determination of rare earths at ppb level by coprecipitative preconcentration using iron (III) hydroxide as collector. the precipitates are collected by vacuum filtration onto filter paper containing ethyl cellulose powder. After drying the residue was powdered and pressed into pellets for quantitation by energy dispersive x-ray fluorescence (EDXRF) via their characteristic K-x ray lines. Various parameters that influence coprecipitative preconcentration of rare earths on iron (III) hydroxide were optimized. Further, a numerical method based on simple least square procedure was developed for smoothing and differentiation of the EDXRF data which had been digitized and averaged. By carrying out the least square calculations on a computer via convolution of the EDXRF data (obtained after co precipitative preconcentration) with properly chosen integers facilitates the determination of as low as 10 ppb each of rare earths.

Software package for quantitative analysis of solid materials by energy-dispersive x-ray fluorescence spectrometry without absolute calibration

A software package for quantifying elements in solids from energy-dispersive x-ray fluorescence data is described. The algorithm is based on the fundamental parameter approach and facilitates the simultaneous determination of several elements at widely varying concentrations. The software comprises three programs. One program, for spectrometer control and data acquisition, resides in a dedicated microcomputer. The two other programs, for spectra deconvulution and data evaluation, reside in a larger central computer. On-line communication between the computers is feasible, and the system facilitates the implementation of new improved programs. The performance of the system was tested on standard reference materials, and satisfactory accuracy was obtained for up to 21 elements.

Computer Code for Analysing X-Ray Fluorescence Spectra of Airborne Particulate Matter

During recent years energy dispersive x-ray fluorescence (EDXRF) has been used to measure the elemental content of atmospheric aerosols. The code described here is used to reduce EDXRF data and determine the elemental composition of samples collected on membrane filters. The program has been specifically written for EDXRF analysis of size-fractionated aerosols collected by a dichotomous sampler.The x-ray fluorescence spectrometer used in our laboratory employs a pulsed-mode x-ray tube and a lithium-drifted silicon detector. Pulse-height spectra are produced for elements ranging in atomic number from Z = 13 to Z = 82 (corresponding to an energy range from 1.4 to 32.1 keV). Approximately uniform x-ray production is attained by producing independent spectra from three secondary targets (Ti, Mo, Sm).

The Resolution of X-Ray Fluorescence Spectra by the Least Squares Method

Least squares computer programs have been used for the resolution of complex gamma-ray spectra obtained from NaI(Tl) detectors for many years. With the addition of computer codes, which account for the differences “between gamma-ray and x-ray fluorescence spectra, these same programs can be used to quantify energy dispersive x-ray fluorescence data.

Reliability of Energy Dispersive X-Ray Fluorescence of Low-Alloy Steels

The reliability of energy dispersive x-ray fluorescence data for the analysis of low-alloy steels is reported for chromium, manganese, nickel, and molybdenum. The accuracy and precision of the analysis were evaluated for two mathematical models, linear and multiple regression, using twelve NBS standard reference samples. Data on results are furnished.