Quantitative Analysis of Iron and Silicon Concentrations in Iron Ore Concentrate Using Portable X-ray Fluorescence (XRF)

Abstract

As a technique capable of rapid, nondestructive, and multi-elemental analysis, portable X-ray fluorescence (pXRF) has applications to mineral exploration, environmental evaluation, and archaeological analysis. However, few applications have been conducted in the smelting industry especially when analyzing the metal concentration in ore concentrate samples. This research analyzed the effectiveness of using pXRF in determining the metal concentration in Fe concentrate. For this proof of concept study, Fe ore samples dominated by Fe and Si were collected from the Northeastern University Mineral Processing Laboratory (Shenyang, China) and directly analyzed using pXRF, laboratory-based XRF, and titration methods. The compactness (density) of the ore concentrate was found to have very little effect on pXRF readings. The pXRF readings for Fe and Si were comparative to laboratory-based XRF results. Based on the strong correlations between the pXRF and XRF results (Fe: R2 > 0.99, Si: R2 > 0.96), linear calibrations were adopted to improve the accuracy of pXRF readings. Linear regression equations derived from the relations between XRF results and pXRF results of 21 Fe ore concentrate samples were used to calibrate the pXRF, and then validation was performed on five additional samples. Results from this preliminary study suggest that ordinary least squares (OLS) regression improves the accuracy dramatically, especially for Fe with relative errors (REs) decreasing to 0.03%–3.27% from 4.26%–8.32%. Consequently, pXRF shows strong promise for rapid, quantitative analysis of Fe concentration in Fe ore concentrate. Based on the results obtained in this study, a larger, more comprehensive study is warranted to confirm the results obtained.

Fuzzy Decision Support System for the Calibration of Laboratory-Scale Mill Press Parameters

“…The authors demonstrate that it is possible to reduce the sampling error by decreasing the particle size in the sample. Alternatively, [17] analyze the effectiveness of using portable X-ray fluorescence in determining the metal iron concentration. Results from this study suggest that ordinary linear regression (OLR) improves the accuracy.…”

A Review of Portable High-Performance Liquid Chromatography: the Future of the Field?

“…A considerable number of research articles and reviews have directed their attention to the potential of developing mobile and handheld devices based on various detection methods. Some of these include Raman [82][83][84][85][86][87], ultraviolet (UV) [88], visible [89], ultraviolet-visible (UV-vis) [90][91][92], near-infrared (NIR) [93,94], Fourier-transform infrared spectroscopy (FTIR) [95,96], induced fluorescence [97][98][99], electrochemical detectors (ECDs), and X-ray fluorescence [100][101][102]. The vast majority of these methods can be adapted to detect and quantify eluting analytes in an LC instrument.…”

Determination of trace element concentrations in organic materials of “intermediate-thickness” via portable X-ray fluorescence spectrometry

“…For example, Pearson et al (2017) and Zhou et al used soil mode to determine the elemental concentrations in water samples and corrected pXRF readings using simple linear regression (SLR) calibration models 14,32 . Zhou et al used mining mode to determine Fe and Si concentrations in iron ore concentrate; a SLR calibration model was developed to improve pXRF accuracy 33 . Furthermore, SLR calibration models have been used for predicting the ICP-MS results for organic samples.…”

“…14,32 Zhou et al used mining mode to determine Fe and Si concentrations in an iron ore concentrate; and a SLR calibration model was developed to improve pXRF accuracy. 33 Furthermore, SLR calibration models have been used for predicting the ICP-MS results for organic samples. For example, McGladdery et al used soil mode to determine the elemental concentrations in vegetation samples.…”