Rare earth elements recovery using staged precipitation from a leachate generated from coarse coal refuse

Zhang, Wencai; Honaker, R.Q.

doi:10.1016/j.coal.2018.06.008

Cited by 133 publications

(48 citation statements)

References 49 publications

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“…Previous investigations have shown that some coals from China [5][6][7], Russia [3,8], and the USA contain high concentrations of REY [9][10][11], comparable to or even higher than those of conventional REY deposits [3]. Other studies concerning REY resources [12,13], modes of REY occurrence in coal and CCPs [14,15], and extraction technology [16] have also suggested the great potential of coal as REY source.…”

Section: Introductionmentioning

confidence: 98%

Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS

2019

Minerals

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Ba-based ion interference with Eu in coal and coal combustion products during quadrupole-based inductively coupled plasma mass spectrometry procedures is problematic. Thus, this paper proposes machine-learning-based prediction models for determination of the threshold value of Ba interference with Eu, which can be used to predict such interference in coal. The models are trained for Eu, Ba, Ba/Eu, and Ba interference with Eu. Under different user-defined parameters, different prediction models based on the corresponding model tree can be applied to Ba interference with Eu. We experimentally show the effectiveness of these different prediction models and find that, when the Ba/Eu value is less than 2950, the Ba-Eu interference prediction model is y = −0.18419411 + 0.00050737 × x, 0 < x < 2950. Further, when the Ba/Eu value is between 2950 and 189,523, the Ba-Eu interference prediction model of y = 0.293982186 + 0.00000181729975 × x, 2950 < x < 189, 523 yields the best result. Based on the optimal model, a threshold value of 363 is proposed; i.e., when the Ba/Eu value is less than 363, Ba interference with Eu can be neglected during Eu data interpretation. Comparison of this threshold value with a value proposed in earlier works reveals that the proposed prediction model better determines the threshold value for Ba interference with Eu.Minerals 2019, 9, 259 2 of 17 (INAA) [19][20][21], laser-ablation inductively-coupled plasma mass spectroscopy (La-ICP-MS) [22], sector-field inductively-coupled plasma mass spectroscopy ICP-MS [23], laser-induced break-down spectrometry [24][25][26], and quadrupole-based ICP-MS (ICP-Q-MS) [4,27]. Among these techniques, ICP-Q-MS has mostly been used for determination of REY concentrations in coal and CCPs. This is because of this method's ability to rapidly, precisely, and accurately measure REY content at very low detection limits in liquid and solid samples, with relatively simple spectra and a wide linearity range [14,[27][28][29]. However, in some cases, Eu concentrations in coal and CCPs cannot be accurately measured by the ICP-Q-MS. This difficulty is attributed to overlapping ion interference (such as those from M + , MO + , and/or MOH + ions) with Eu, which affects interpretation of the ICP-Q-MS spectra [30][31][32][33][34][35]. Because Ba concentrations in coal and CCPs are generally much higher than those of Eu [4,36], the most significant types of interference encountered for Eu in coal and CCPs are due to 135 Ba 16 O, 134 Ba 16 OH, 137 Ba 16 O, and/or 136 Ba 16 OH interfering with 151 Eu and/or 153 Eu. For example, the ratio of Ba vs. Eu for world coals is as high as~882 (with an average concentration of 150 µg/g Ba and 0.47 µg/g Eu) [36]. Therefore, as noted by Dai et al. [4], Eu content values in coal and CCPs determined via ICP-Q-MS should be treated with great caution. Recently, Yan et al. [27] described a reliable analytical method to avoid Ba-based ion interference with Eu in coal, CCPs, and sedimentary rocks during ICP-Q-MS procedures, which was based on AG50W-X8...

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Section: Introductionmentioning

confidence: 98%

Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS

2019

Minerals

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“…Acid mine drainage (AMD) is one of the most widespread forms of metal pollution affecting continental waters (Bigham and Nordstrom, 2000;Nordstrom, 2011;Nordstrom et al, 2015). The REE concentrations in AMD are several orders of magnitude higher than those of other surface waters and could be a future supplementary source of some highly valuable REE (Ayora et al, 2016;Stewart et al, 2017;Zhang and Honaker, 2018). Moreover, although REE have been considered a minor environmental concern due to their common use in modern industry, some toxicological studies suggest that they could have pathogenic potential (Zhuang et al, 1996;Dai et al, 2002;Pagano et al, 2015;Roncati et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Geochemical behavior of rare earth elements in acid drainages: Modeling achievements and limitations

Lozano

Ayora

Macías

et al. 2020

Journal of Geochemical Exploration

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“…The enrichment and potential for extraction of the lanthanides Sc and Y, collectively rare earth elements (REE) after Connelly et al [1], from both coal [2][3][4][5][6][7] and fly ash as well as other coal combustion products has attracted much attention in recent years [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25]. The Pennsylvanian Fire Clay coal, primarily in its central eastern Kentucky locations, is a prime source of coal-based REE; thus, the fly ash from the combustion of the Fire Clay coal has also been of interest [9,13,17,18,26].…”

Section: Introductionmentioning

confidence: 99%

Nano-Scale Rare Earth Distribution in Fly Ash Derived from the Combustion of the Fire Clay Coal, Kentucky

et al. 2019

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Fly ash from the combustion of eastern Kentucky Fire Clay coal in a southeastern United States pulverized-coal power plant was studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and selected area electron diffraction (SAED). TEM combined with elemental analysis via energy dispersive X-ray spectroscopy (EDS) showed that rare earth elements (REE; specifically, La, Ce, Nd, Pr, and Sm) were distributed within glassy particles. In certain cases, the REE were accompanied by phosphorous, suggesting a monazite or similar mineral form. However, the electron diffraction patterns of apparent phosphate minerals were not definitive, and P-lean regions of the glass consisted of amorphous phases. Therefore, the distribution of the REE in the fly ash seemed to be in the form of TEM-visible nano-scale crystalline minerals, with additional distributions corresponding to overlapping ultra-fine minerals and even true atomic dispersion within the fly ash glass.

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Rare earth elements recovery using staged precipitation from a leachate generated from coarse coal refuse

Cited by 133 publications

References 49 publications

Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS

Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS

Geochemical behavior of rare earth elements in acid drainages: Modeling achievements and limitations

Nano-Scale Rare Earth Distribution in Fly Ash Derived from the Combustion of the Fire Clay Coal, Kentucky

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