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Keywords = pXRF geochemistry

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16 pages, 5734 KiB  
Article
Elemental Geochemistry on Paleoenvironment Reconstruction: Proxies on Miocene-Pliocene of Marine to Fluvial Sediment in Serpong, Banten, Indonesia
by Heri Syaeful, Syaiful Bakhri, Budi Muljana, Agus Sumaryanto, I. Gde Sukadana, Hendra Adhi Pratama, Adi Gunawan Muhammad, Ngadenin, Frederikus Dian Indrastomo, Roni Cahya Ciputra, Susilo Widodo, Nunik Madyaningarum, Puji Santosa, Muhammad Burhannudinnur and Zufialdi Zakaria
Geosciences 2024, 14(7), 189; https://doi.org/10.3390/geosciences14070189 - 13 Jul 2024
Viewed by 762
Abstract
Research of the depositional environment using geological mapping, petrography, gamma-ray (GR) log, palynology, and foraminifera fossils of the Bojongmanik Formation has led to the formation of several different conclusions about the transition to the marine environment, which are attractive to revisit. The expected [...] Read more.
Research of the depositional environment using geological mapping, petrography, gamma-ray (GR) log, palynology, and foraminifera fossils of the Bojongmanik Formation has led to the formation of several different conclusions about the transition to the marine environment, which are attractive to revisit. The expected results of this research are to determine the paleoenvironment of the Bojongmanik and Serpong Formations based on elemental geochemistry, the development of paleoenvironment proxies based on portable X-ray fluorescence (pXRF) in fluvial to transitional environments studies, and the contribution of paleoenvironment analysis to GR-log facies interpretation. The research methodology starts with GR-log facies analysis, Pearson’s correlation, paleoenvironment analysis based on elemental affinity and elemental ratio, and comparing the paleoenvironment with GR-log-based facies. The paleoenvironment analysis based on elemental geochemistry resulted in the Bojongmanik Formation in the research area deposited at the tidal point bar, lagoon, and shoreface, while the Serpong Formation was deposited at the fluvial point bar and floodplain. Compared to previous research, the Bojongmanik Formation in the research area could be stratigraphically related to the upper Bojongmanik Formation. Proxies based on elemental geochemical affinities of carbonate-associated, carbonate-productivity, terrigenous-associated elements, and redox-sensitive trace elements show contrast changes between facies. Proxies based on the specific ratio show a detailed paleoenvironment for paleoclimate (Sr/Cu), paleosalinity (Sr/Ba), paleoredox (Cu/Zn), paleo-hydrodynamics and water depth (Zr/Rb and Fe/Mn), sediment provenance (Cr/Zr), and siliciclastic-dominated (Zr + Rb)/Sr. Adding a geochemistry element-based paleoenvironment analysis benefits from a more specific justification for GR-log facies interpretation. Full article
(This article belongs to the Section Geochemistry)
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Figure 1
<p>Distribution of Bojongmanik and Serpong Formations surrounding the research area (black box).</p>
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<p>GR-log facies analysis of DH-11.</p>
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<p>Drill core and facies unit of DH-11.</p>
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<p>Paleoenvironment analysis based on elemental affinity. Note: The arrow shows the enriched zone.</p>
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<p>Paleoenvironment analysis based on elemental ratio. Note: the red dashed line is the threshold from previous research, and the yellow dashed line is defined in this research.</p>
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<p>Paleoenvironmental change from the tidal point bar to the fluvial point bar (<b>a</b>,<b>b</b>) and from the upper shoreface to the tidal point bar (<b>c</b>,<b>d</b>).</p>
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<p>Box plot of the result of paleoenvironment reconstruction from (Zr + Rb)/Sr (<b>a</b>) and Cu/Zn (<b>b</b>). The vertical dashed line indicates the boundary of the depositional environment, while the horizontal dashed line indicates the threshold value between the marine and fluvial environments.</p>
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16 pages, 2999 KiB  
Article
X-ray Fluorescence Core Scanning for High-Resolution Geochemical Characterisation of Soils
by Shayan Kabiri, Nick M. Holden, Rory P. Flood, Jonathan N. Turner and Sharon M. O’Rourke
Soil Syst. 2024, 8(2), 56; https://doi.org/10.3390/soilsystems8020056 - 17 May 2024
Viewed by 1016
Abstract
X-ray fluorescence (XRF) core scanners are commonly used for fine-scale geochemical analysis in sediment studies, but data are semi-quantitative and require calibration to convert geochemical element counts to concentrations. Application of XRF core scanning in soil science remains largely untapped. This study employed [...] Read more.
X-ray fluorescence (XRF) core scanners are commonly used for fine-scale geochemical analysis in sediment studies, but data are semi-quantitative and require calibration to convert geochemical element counts to concentrations. Application of XRF core scanning in soil science remains largely untapped. This study employed an ITRAX core scanner to scan grassland soil cores and developed a novel calibration method based on a chemometric approach to characterise soil geochemistry. As soil samples are collected based on depth sampling, this study investigated whether higher resolution element concentrations could be inferred from lower resolution reference samples and if regression models from multiple cores could apply to a new core at the same resolution. Reference concentrations were obtained for all cores at 10 cm intervals, with validation conducted at 1 cm for a single core. Two calibration curve types were proposed: one based on the single core’s 10 cm data to validate references at 1 cm intervals; and another using all cores, with each core serving as a test item after exclusion from the training set. Various preprocessing measures and feature selection techniques were tested. Results showed successful calibration for elements Ca, P, Zn, Sr, and S, with high R2 values of 0.94, 0.93, 0.93, 0.92 and 0.91, respectively. The study presents a novel method for calibrating XRF core scanning element counts, demonstrating its potential for high-resolution soil analysis. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>A</b>) Variance explained by each PC and (<b>B</b>) scatter plot for PC1, PC2, and PC3 for element reference concentrations.</p>
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<p>Boxplots for element reference concentrations in different cores.</p>
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<p>Correlation coefficient between pellets and core element counts and 0.6 threshold for keeping the element for calibration input.</p>
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<p>Variance inflation factor for element counts with correlations stronger than r = 0.6 between pellets and cores and threshold of 100 for keeping the element for the calibration input.</p>
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<p>Measured reference concentrations at 10 cm (<b>A</b>–<b>C</b>) and measured and predicted concentrations at 1 cm (<b>D</b>–<b>F</b>) for Ca, P, and S in a Brown Earth soil core.</p>
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<p>Ca, Zn, and Pb, 10 cm validation predictions (orange lines) and reference concentrations (blue cross marks) on three sample cores from three soil types.</p>
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<p>Ca, Zn, and Pb, 10 cm validation predictions (orange lines) and reference concentrations (blue cross marks) on three sample cores from three soil types.</p>
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21 pages, 3801 KiB  
Article
Chemostratigraphic Approach to the Study of Resources’ Deposit in the Upper Silesian Coal Basin (Poland)
by Ewa Krzeszowska
Energies 2024, 17(3), 642; https://doi.org/10.3390/en17030642 - 29 Jan 2024
Viewed by 824
Abstract
The Upper Silesian Coal Basin (USCB), located in southern Poland, is the major coal basin in Poland, and all technological types of hard coal, including coking coal, are exploited. It is also an area of high potential for coal-bed methane (CBM). Despite the [...] Read more.
The Upper Silesian Coal Basin (USCB), located in southern Poland, is the major coal basin in Poland, and all technological types of hard coal, including coking coal, are exploited. It is also an area of high potential for coal-bed methane (CBM). Despite the increasing availability of alternative energy sources globally, it is a fact that the use of fossil fuels will remain necessary for the next few decades. Therefore, research on coal-bearing formations using modern research methods is still very important. The application of geochemistry and chemostratigraphy in reservoir characterization has become increasingly common in recent years. This paper presents the possibility of applying chemostratigraphic techniques to the study of the Carboniferous coal-bearing succession of the Upper Silesian Coal Basin. The material studied comes from 121 core samples (depth 481–1298 m), representing the Mudstone Series (Westphalian A, B). Major oxide concentrations of Al2O3, SiO2, Fe2O3, P2O5, K2O, MgO, CaO, Na2O, K2O, MnO, TiO2, and Cr2O3 were obtained using X-ray fluorescence (XRF) spectrometry. Trace elements were analyzed using inductively coupled plasma mass spectrometry (ICP/MS). The geochemical record from the Mudstone Series shows changes in the concentration of major elements and selected trace elements, leading to the identification of four chemostratigraphic units. These units differ primarily in the content of Fe, Ca, Mg, Mn, and P as well as the concentration of Zr, Hf, Nb, Ta, and Ti. The study also discusses quartz origin (based on SiO2 and TiO2), sediment provenance and source-area rock compositions (based on Al2O3/ TiO2, TiO2/Zr, and La/Th), and paleoredox conditions (based on V/Cr, Ni/Co, U/Th, (Cu+Mo)/Zn, and Sr/Ba) for the chemostratigraphic units. Chemostratigraphy was used for the first time in the study of the Carboniferous coal-bearing series of the USCB, concluding that it can be used as an effective stratigraphic tool and provide new information on the possibility of correlating barren sequences of the coal-bearing succession. Full article
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<p>Lithostratigraphic division of the Carboniferous succession of Western Europe, North America, and China (A, B, C, D are part of the stages from older to younger, respectively) (simplified [<a href="#B27-energies-17-00642" class="html-bibr">27</a>,<a href="#B35-energies-17-00642" class="html-bibr">35</a>,<a href="#B43-energies-17-00642" class="html-bibr">43</a>,<a href="#B44-energies-17-00642" class="html-bibr">44</a>]).</p>
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<p>Location of the study area (modified [<a href="#B34-energies-17-00642" class="html-bibr">34</a>]).</p>
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<p>Stratigraphical variability of the lithological types for the borehole WS within the Mudstone Series of the USCB. Explanations: C, claystones; S, siltstones; As, argillaceous sandstones; Sa, sandstones.</p>
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<p>Major element geochemical profiles of the Mudstone Series from the borehole WS and chemostratigraphic zonation of the profile.</p>
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<p>Average, minimum, and maximum values for the selected major elements within the chemostratigraphic units.</p>
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<p>Correlation diagrams of SiO<sub>2</sub> with TiO<sub>2</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Correlation diagrams of SiO<sub>2</sub> with Al<sub>2</sub>O<sub>3</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Correlation diagrams of K<sub>2</sub>O with Al<sub>2</sub>O<sub>3</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Correlation diagrams of CaO with Fe<sub>2</sub>O<sub>3</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Correlation diagrams of SiO<sub>2</sub> with Fe<sub>2</sub>O<sub>3</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Crossplot of Al<sub>2</sub>O<sub>3</sub> vs. TiO<sub>2</sub> for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Crossplot of TiO<sub>2</sub> vs. Zr for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Crossplot of La vs. Th for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Crossplot of Th vs. Sc for the samples from Unit 1 and Unit 3 (<b>a</b>) and Unit 2 and Unit 4 (<b>b</b>).</p>
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<p>Crossplot of Ni/Co vs. V/Cr (<b>a</b>) and of U/Th vs. (Cu+Mo)/Zn (<b>b</b>) for the analyzed samples.</p>
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<p>The vertical distributions of Zr, Hf, Nb, Ta, Ti in the profile of the Mudstone Series from the borehole WS.</p>
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<p>Relationship between selected trace elements Zr vs. Hf (<b>a</b>), Ti vs. Nb (<b>b</b>), Ti vs. Ta (<b>c</b>), and Zr vs. Nb (<b>d</b>).</p>
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50 pages, 15378 KiB  
Article
Characterizing Archaeological Rhyolites in the Nenana Valley, Interior Alaska
by Angela K. Gore, Kelly Graf and Joshua J. Lynch
Minerals 2023, 13(9), 1146; https://doi.org/10.3390/min13091146 - 30 Aug 2023
Viewed by 1162
Abstract
Portable X-ray fluorescence (pXRF) is a useful geochemical technique employed to explore toolstone procurement strategies in the lithic record, commonly utilized in sourcing obsidians. Non-obsidian volcanic toolstones (e.g., dacites, rhyolites, basalts, and andesites) are abundant in interior Alaskan assemblages yet understudied compared to [...] Read more.
Portable X-ray fluorescence (pXRF) is a useful geochemical technique employed to explore toolstone procurement strategies in the lithic record, commonly utilized in sourcing obsidians. Non-obsidian volcanic toolstones (e.g., dacites, rhyolites, basalts, and andesites) are abundant in interior Alaskan assemblages yet understudied compared to obsidian. Geochemical analyses of these non-obsidian materials offer the potential to gain new insights into ancient toolstone provisioning behaviors. This paper presents a synthesis of geochemical (pXRF) analyses of rhyolite artifacts, systematic regional raw material surveys, and lithic technological analyses collected from nineteen late Pleistocene and Holocene assemblages from the Nenana valley, interior Alaska. Previous research studies on archaeological rhyolites from the region are replicated, new rhyolite artifact groups are identified, and one new rhyolite source is reported and described here. Ultimately, this paper contributes to a growing body of geochemical research seeking to provide a more nuanced look at the complex late Pleistocene and Holocene record of eastern Beringia. Full article
(This article belongs to the Special Issue Archaeological Mineralogy)
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<p>Map of archaeological sites, sample locations, and survey boundaries in the Nenana River valley. Rhyolite outcrops: 1: Triple Lakes; 2: Sugarloaf Mountain; 3: Ferry 1; 4: Ferry 2; 5: Ferry 3; 6: Ferry 4; 7: Ferry 5; and 8: Calico Creek rhyolite (approximate location reported by Coffman and Rasic [<a href="#B98-minerals-13-01146" class="html-bibr">98</a>]; this location was not sampled during survey). Rhyolite alluvial samples: 1: Bear Creek; 2: California Creek; 3: Savage and Teklanika Confluence; 4: Teklanika River.</p>
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<p>Logged (base 10) biplots of principal component 1 and 2 scores for rhyolites sampled from seven rhyolite outcrop locations in this study. Ellipse confidence intervals drawn at 90%.</p>
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<p>Logged (base 10) biplots of rhyolite outcrop samples comparing principal components 2 and 4 scores of Ferry 3, Ferry 5, and Sugarloaf rhyolites (<b>a</b>) and Nb and Zr (ppm) values for Ferry 3, Ferry 5, Sugarloaf, and Triple Lakes rhyolites (<b>b</b>). Ellipse confidence intervals drawn at 90%.</p>
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<p>Logged (base 10) 3D plots of rhyolite outcrops sampled in this study, comparing (<b>a</b>) principal components 1, 2, and 4 scores of the Ferry 1 and Ferry 3 rhyolites and (<b>b</b>) principal components 2, 3, and 5 scores of the Ferry 3 and Triple Lakes rhyolites.</p>
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<p>Logged (base 10) biplots comparing alluvial and outcrop samples by (<b>a</b>) principal components 1 and 2 scores and (<b>b</b>) principal component 1 and 3 scores. Ellipse confidence intervals drawn at 90%.</p>
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<p>Logged (base 10) biplots of (<b>a</b>) rhyolite artifact samples and their assigned groups by scores of principal components 1 and 2, (<b>b</b>) principal components 1 and 3, (<b>c</b>) principal components 1 and 4, and (<b>d</b>) principal components 1 and 5. Unassigned artifacts denoted by black crosses in all plots. Ellipse confidence intervals drawn at 90%. TM = Talkeetna Mountains source area, formerly “group G;” CC = Calico Creek source area, formerly “group H.”.</p>
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<p>Logged (base 10) biplot comparing rhyolite artifact groups (ellipses) and unassigned artifacts with alluvial samples by scores of principal components 1 and 2. Alluvial samples overlapping with artifact rhyolite groups are highlighted in red. Ellipse confidence intervals drawn at 90%. TM = Teklanika Mountains source area; CC = Calico Creek source area.</p>
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<p>Logged (base 10) biplots comparing select rhyolite artifact groups (ellipses) with alluvial samples by scores of principal components 1 and 3 (<b>a</b>) and principal components 3 and 5 (<b>b</b>). Alluvial samples positioned within or near a group ellipse in <a href="#minerals-13-01146-f007" class="html-fig">Figure 7</a> are shown here in red. CC = Calico Creek source area. Ellipse confidence intervals drawn at 90%.</p>
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<p>Logged (base 10) biplots comparing unassigned artifacts and alluvium by (<b>a</b>) principal components 1 and 2, (<b>b</b>) principal components 1 and 3, and (<b>c</b>) principal components 1 and 4. Unassigned artifacts discussed in text denoted by red crosses and the label “UA”; alluvial samples discussed in text denoted by blue alluvial symbol and labeled. ST = Savage and Teklanika Confluence sample; T = Teklanika River sample.</p>
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<p>Logged (base 10) biplots comparing artifact rhyolite group ellipses, unassigned artifacts, and outcrop samples (ellipses) by (<b>a</b>) scores of principal components 1 and 2, (<b>b</b>) principal components 1 and 3, (<b>c</b>) principal components 1 and 4, and (<b>d</b>) principal components 2 and 3. Artifacts assigned to Triple Lakes denoted by red crosses and labeled according to site assemblages (Moose Creek C3 (MC); Owl Ridge C3 (OR1 and OR2)). TM = Talkeetna source area; CC = Calico Creek source area. Ellipse confidence intervals drawn at 90%.</p>
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<p>Logged (base 10) 3D plot of rhyolite outcrops sampled in this study, comparing Sr, Nb, and Rb (ppm) values of Group B artifacts and Ferry 5 outcrop samples.</p>
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<p>Spatial distribution and proportion of rhyolite artifact groups A, B, C, D, E, F, I, J, K, L, M, N, TM (Talkeetna Mountains), CC (Calico Creek), and TRL (Triple Lakes) at sites in the Nenana valley. Density circles are representative of the number of rhyolite artifacts analyzed from each site.</p>
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<p>Stacked bar charts showing (<b>a</b>) proportions and numbers of rhyolite artifact groups by time, and (<b>b</b>) cortex amount by group by time. CC = Calico Creek artifacts; TM = Talkeetna Mountain artifacts; TRL = Triple Lakes artifacts; UNA = unassigned artifacts. Raw counts are given within each bar section, and percentages are measured along the y-axis.</p>
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<p>Stacked bar chart showing proportions and numbers of local and nonlocal rhyolites within each assemblage. Assemblages proceed chronologically, oldest to youngest, from left to right. Raw counts are given in each bar section, and percentages are measured along the y-axis.</p>
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<p>Linear regression graph comparing number of rhyolite groups (y-axis; log base 10) with total number of rhyolite artifacts sampled (x-axis; log base 10). The slope coefficient is 0.369; the intercept coefficient is 0.336; Pearson’s correlation coefficient (R) is 0.824; the R<sup>2</sup> value is 0.659. Assemblages are color coded by time period. WR is Walker Road; DC 1, DC 2, and DC 4 are Dry Creek C1, Dry Creek C2, and Dry Creek C4, respectively; MC 1, MC 2, MC 3, and MC 4 are Moose Creek C1, Moose Creek C2, Moose Creek C3, and Moose Creek C4, respectively; OR 1, OR 2, and OR 3 are Owl Ridge C1, Owl Ridge C2, and Owl Ridge C3, respectively; PC 1, PC 2, and PC 3 are Panguingue Creek C1, Panguingue Creek C2, and Panguingue Creek C1, respectively; ER is Eroadaway; TW 3 is Teklanika West C3; HOU is Houdini Creek; and LPC is Little Panguingue Creek C2.</p>
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<p>Bar chart showing mean standardized residuals (y-axis) for each archaeological assemblage (x-axis), color coded by time period. WR is Walker Road; DC 1, DC 2, and DC 4 are Dry Creek C1, Dry Creek C2, and Dry Creek C4, respectively; MC 1, MC 2, MC 3, and MC4 are Moose Creek C1, Moose Creek C2, Moose Creek C3, and Moose Creek C4, respectively; OR 1, OR 2, and OR 3 are Owl Ridge C1, Owl Ridge C2, and Owl Ridge C3, respectively.</p>
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<p>Bar chart showing proportion and numbers of rhyolite toolstone in each assemblage compared with the proportion and number of rhyolite groups within each assemblage, presented in chronological order from left to right; percentages measured along the y-axis.</p>
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<p>Stacked bar chart showing proportions of toolstone types within each assemblage, with percentages measured along the y axis; raw material type scored during lithic analysis of these assemblages.</p>
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11 pages, 8220 KiB  
Article
The Application of Portable X-ray Fluorescence (pXRF) for Elemental Analysis of Sediment Samples in the Laboratory and Its Influencing Factors
by Shuguang Zhou, Jinlin Wang, Yong Bai, Wei Wang and Shanshan Wang
Minerals 2023, 13(8), 989; https://doi.org/10.3390/min13080989 - 25 Jul 2023
Cited by 1 | Viewed by 1829
Abstract
Several techniques, such as chemical methods and inductively coupled plasma mass spectrometry (ICP-MS), are available to accurately determine element content. However, they are time-consuming, labor-intensive, or expensive. Portable X-ray fluorescence spectrometry (pXRF) can be applied in various scenarios, with significantly higher efficiency and [...] Read more.
Several techniques, such as chemical methods and inductively coupled plasma mass spectrometry (ICP-MS), are available to accurately determine element content. However, they are time-consuming, labor-intensive, or expensive. Portable X-ray fluorescence spectrometry (pXRF) can be applied in various scenarios, with significantly higher efficiency and cost-effectiveness than laboratory methods. However, it also has limitations such as lower detection capability, relatively high detection limits, and lower accuracy than laboratory methods. In this study, we focused on applying pXRF to determine the elemental content of sediment samples and investigate its use in mineral exploration. A variety of factors influencing the results of pXRF analysis were analyzed. Our results showed that pXRF could detect more than 30 elements in stream sediments. The reliability of pXRF’s measurements was affected by factors such as the kind of element, sediment particle size, sample grinding treatment, count time, averaged element content, standard deviation of content, and range of content variation. The combination of pXRF analysis and laboratory analysis of partial samples is adequate for establishing a multi-element content inference equation. With this equation, it is possible to effectively infer the content gradient of elements, which will provide valuable support for mineral resource exploration. Full article
(This article belongs to the Special Issue Geochemical Exploration for Critical Mineral Resources)
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<p>The ability of pXRF to detect various elements in stream sediment samples.</p>
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<p>Comparison of basic statistical parameters for Al, Nb, Ba, and Zr in samples with different particle sizes. par1, par2, par3, and par4 represent the particle diameters (d) in the sample, which are d &gt; 380 μm, 380 μm &lt; d &lt; 150 μm, 75 μm &lt; d &lt; 150 μm, and d &lt; 75 μm, respectively.</p>
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<p>Correlation coefficients between pXRF and laboratory results at different count times. 40s_lab, 80s_lab, 120s_lab, 160s_lab represent the correlation coefficient between pXRF and laboratory results when the pXRF count times are 40 s, 80 s, 120 s, and 160 s, respectively.</p>
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<p>Influence of the true content of elements on pXRF analysis errors.</p>
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24 pages, 34695 KiB  
Article
Petrology and Age of the Yamaat Uul Mafic Complex, Khangai Mountains, Western Mongolia
by Roman Shelepaev, Maria Shapovalova, Vera Egorova, Yaroslav Shelepov, Tumen-Ulzii Oyunchimeg and Nadezhda Tolstykh
Minerals 2023, 13(6), 833; https://doi.org/10.3390/min13060833 - 20 Jun 2023
Viewed by 1327
Abstract
The Yamaat Uul mafic complex with Cu-Ni mineralization is located in the Khangai Mountains of Western Mongolia. We have received new unique data for mafic rocks of the complex: U-Pb dating (SHRIMP II), mineralogy (WDS) and geochemistry (XRF, ICP-MS), Sm-Nd and Rb-Sr isotope [...] Read more.
The Yamaat Uul mafic complex with Cu-Ni mineralization is located in the Khangai Mountains of Western Mongolia. We have received new unique data for mafic rocks of the complex: U-Pb dating (SHRIMP II), mineralogy (WDS) and geochemistry (XRF, ICP-MS), Sm-Nd and Rb-Sr isotope data and sulphur isotopes. The Yamaat Uul mafic complex consists of two intrusions: Intrusion 1 is represented by rocks of plagioclase cumulates and olivine–pyroxene cumulates; Intrusion 2 consists of monzogabbro. Intrusions 1 and 2 are different in composition of minerals such as olivine, plagioclase and biotite. The monzogabbro has higher contents of incompatible elements (REE, K, Ti, P) than rocks of Intrusion 1. Zircon U-Pb dating of the anorthosite and Bt-Am-Ol gabbronorite shows a Late Permian age (255.8 ± 2.9 Ma and 262.6 ± 3.1 Ma, respectively) for the Yamaat Uul mafic complex. All of the rocks of the complex are derived from a unified parental melt due to different amounts of trapped melts in plagioclase and olivine–pyroxene cumulates and without crustal contamination. The Cu-Ni mineralization of the complex has a low degree of evolution of the sulphide melt, similar to PGE-Cu-Ni mafic–ultramafic intrusions of the Khangai Mountains (Nomgon and Oortsog Uul). The Yamaat Uul mafic complex together with other mafic–ultramafic intrusions of the Khangai Mountains is related to the Khangai LIP and can be considered as potential for the PGE-Cu-Ni. The new geological, petrological, geochemical and isotope–geochronological data can later be used to reconstruct the geotectonics of the Khangai Mountains and the Central Asian orogenic belt as a whole. Full article
(This article belongs to the Special Issue Large Igneous Provinces: Research Frontiers)
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Figure 1
<p>A geologic map of the mafic–ultramafic intrusions location within Khangai batholith (modified after [<a href="#B31-minerals-13-00833" class="html-bibr">31</a>,<a href="#B32-minerals-13-00833" class="html-bibr">32</a>]). 1—Central Asian orogenic belt (CAOB); 2—volcano–plutonic belt (SVVPB—Selenga–Vitim volcano–plutonic belt, GAVPB—Gobi–Altay volcano–plutonic belt); 3—Mesozoic–Cenozoic troughs; 4—Late Palaeozoic granitoids of the Khangai batholith; 5—Permian gabbros of the Khangai Mountains; 6–9—orogens: 6—Middle–Late Palaeozoic (Hercynides), 7—Early–Middle Palaeozoic (late Caledonides), 8—Vend–Early Palaeozoic (early Caledonides), 9—Neoproterozoic; 10—tectonic blocks with the Early Precambrian basement; 11—tectonic blocks with the Pre-Vend orogenic basement; 12—main tectonic boundaries. Red box—study area.</p>
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<p>Simplified geological map of the Yamaat Uul mafic complex showing the distribution of lithological unites and sample’s location.</p>
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<p>Photos of outcrops of the Yamaa-Uul mafic complex. (<b>a</b>–<b>c</b>) Plagioclase cumulates of Northwestern part; (<b>d</b>) pyroxene cumulates of Northwestern part; (<b>e</b>) monzogabbro of Intrusion 2; (<b>f</b>–<b>h</b>) Bt-Am leucogabbro of Southeastern part; (<b>i</b>) quartz syenite; (<b>j</b>) quartz monzodiorite; (<b>k</b>) Bt monzogranite; (<b>l</b>–<b>o</b>) gabbroids of Central part. Leucogabbro with fine subvertical layering (<b>c,g</b>). Names of rocks are in <a href="#minerals-13-00833-t001" class="html-table">Table 1</a>.</p>
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<p>(<b>a</b>) Magnetic anomalies map and sample’s location of the Northwestern part of the Yamaat Uul mafic complex; (<b>b</b>,<b>c</b>) shaded-relief magnetic anomaly map of the Northwestern part of the Yamaat Uul mafic complex: view from above (<b>b</b>), view from the northeast (<b>c</b>).</p>
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<p>Photos of thin sections of the Yamaat Uul mafic complex: (<b>a</b>,<b>b</b>) plagioclase cumulate of Intrusion 1; (<b>c</b>–<b>h</b>) pyroxene cumulate of Intrusion 1: (<b>c</b>,<b>d</b>) olivine gabbro, (<b>e</b>,<b>f</b>) Am melagabbronorite, (<b>g</b>,<b>h</b>) Am gabbro; (<b>i</b>–<b>l</b>) monzogabbro of Intrusion 2. (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>k</b>)—PPL; (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>g</b>,<b>l</b>)—XPL. Ol—olivine, Cpx—monoclinic pyroxene, Opx—rhombic pyroxene, Hbl—hornblende, Bt—biotite, Pl—plagioclase, Fsp—K-Na feldspar.</p>
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<p>Transmitted light and CL images, U-Pb spot locations and ages for zircons from anorthosite (sample SH220-14/2) (<b>a</b>) and Bt-Am-Ol gabbronorite (SH105-14) (<b>b</b>). Concordia diagram for zircons from anorthosite (sample SH220-14/2) (<b>c</b>) and Bt-Am-Ol gabbronorite (SH105-14) (<b>d</b>).</p>
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<p>Chemical variation plots of olivine (<b>a</b>), clinopyroxene [<a href="#B55-minerals-13-00833" class="html-bibr">55</a>] (<b>b</b>), amphibole [<a href="#B56-minerals-13-00833" class="html-bibr">56</a>] (<b>c</b>), plagioclase (<b>d</b>) and biotite (<b>e</b>,<b>f</b>) from the studied rocks.</p>
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<p>Classification diagram for rocks of the Yamaat Uul mafic complex and surrounding rocks (after [<a href="#B57-minerals-13-00833" class="html-bibr">57</a>]).</p>
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<p>Variation diagrams of MgO vs. (<b>a</b>) Al<sub>2</sub>O<sub>3</sub>, (<b>b</b>) CaO, (<b>c</b>) K<sub>2</sub>O, (<b>d</b>) TiO<sub>2</sub>, (<b>e</b>) P<sub>2</sub>O<sub>5</sub>, (<b>f</b>) ∑REE, (<b>g</b>) Ba, (<b>h</b>) Sr and (<b>i</b>) Zr for the mafic rocks from the Yamaat Uul mafic complex.</p>
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<p>CI-chondrite-normalized [<a href="#B48-minerals-13-00833" class="html-bibr">48</a>] REE patterns and primitive mantle-normalized [<a href="#B49-minerals-13-00833" class="html-bibr">49</a>] trace element spidergrams for the Yamaat Uul mafic complex: (<b>a</b>,<b>b</b>) Northwestern part, (<b>c</b>,<b>d</b>) Central part, (<b>e</b>,<b>f</b>) Southeastern part.</p>
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<p>Plot of εNd(t) and initial <sup>87</sup>Sr/<sup>86</sup>Sr values for the mafic rocks and Q monzodiorites of the Yamaat Uul mafic complex. DM, depleted mantle; MORB, middle ocean ridge basalt; OIB, ocean island basalt; PM, primitive mantle; EM I and EM II, enriched mantle 1 and 2 sources. Data sources: fields for DM, PM, MORB and OIB are from [<a href="#B60-minerals-13-00833" class="html-bibr">60</a>]; field for regional lithospheric melts is based on the data from [<a href="#B61-minerals-13-00833" class="html-bibr">61</a>]; Permian Tarim basalt is from [<a href="#B12-minerals-13-00833" class="html-bibr">12</a>]; the Precambrian CAOB crust and batholith are from [<a href="#B27-minerals-13-00833" class="html-bibr">27</a>].</p>
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<p>Comparison of MgO vs. K<sub>2</sub>O content in the Yamaat Uul mafic complex and layered intrusions: Yoko–Dovyren [<a href="#B69-minerals-13-00833" class="html-bibr">69</a>], Skye, Skaergaard [<a href="#B68-minerals-13-00833" class="html-bibr">68</a>], Oortsog Uul [<a href="#B17-minerals-13-00833" class="html-bibr">17</a>].</p>
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<p>(<b>a</b>) Chondrite-normalized [<a href="#B75-minerals-13-00833" class="html-bibr">75</a>] chalcophile element distribution patterns for the Yamaat Uul complex in comparison with intrusions of the Khangai Mountains (Nomgon, Oortsog Uul [<a href="#B32-minerals-13-00833" class="html-bibr">32</a>]) and disseminated ores of other deposits related to LIPs (Talnakh [<a href="#B43-minerals-13-00833" class="html-bibr">43</a>], Kalatongke [<a href="#B76-minerals-13-00833" class="html-bibr">76</a>], Limahe [<a href="#B10-minerals-13-00833" class="html-bibr">10</a>]). All compositions were recalculated to 100% sulphide. (<b>b</b>) Correlation of ∑PGE vs. Cu for Yamaat Uul complex compared to intrusions of the Khangai Mountains (after [<a href="#B32-minerals-13-00833" class="html-bibr">32</a>]).</p>
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4118 KiB  
Article
Modes of Occurrence and Abundance of Trace Elements in Pennsylvanian Coals from the Pingshuo Mine, Ningwu Coalfield, Shanxi Province, China
by Ning Yang, Shuheng Tang, Songhang Zhang and Yunyun Chen
Minerals 2016, 6(2), 40; https://doi.org/10.3390/min6020040 - 27 Apr 2016
Cited by 21 | Viewed by 4991
Abstract
The Pingshuo Mine is an important coal mine of the Ningwu coalfield in northern Shanxi Province, China. To investigate the mineralogy and geochemistry of Pingshuo coals, core samples from the mineable No. 4 coals were collected. The minerals, major element oxides, and trace [...] Read more.
The Pingshuo Mine is an important coal mine of the Ningwu coalfield in northern Shanxi Province, China. To investigate the mineralogy and geochemistry of Pingshuo coals, core samples from the mineable No. 4 coals were collected. The minerals, major element oxides, and trace elements were analyzed by scanning electron microscopy (SEM), LTA-XRD in combination with Siroquant software, X-ray fluorescence (XRF), inductively coupled plasma mass spectrometry (ICP-MS) and ICP-CCT-MS (As and Se). The minerals in the Pennsylvanian coals from the Pingshuo Mine dominantly consist of kaolinite and boehmite, with minor amounts of siderite, anatase, goyazite, calcite, apatite and florencite. Major-element oxides including SiO2 (9.54 wt %), Al2O3 (9.68 wt %), and TiO2 (0.63 wt %), as well as trace elements including Hg (449.63 ng/g), Zr (285.95 μg/g), Cu (36.72 μg/g), Ga (18.47 μg/g), Se (5.99 μg/g), Cd (0.43 μg/g), Hf (7.14 μg/g), and Pb (40.63 μg/g) are enriched in the coal. Lithium and Hg present strong positive correlations with ash yield and SiO2, indicating an inorganic affinity. Elements Sr, Ba, Be, As and Ga have strong positive correlations with CaO and P2O5, indicating that most of these elements may be either associated with phosphates and carbonates or have an inorganic–organic affinity. Some of the Zr and Hf may occur in anatase due to their strong positive correlations with TiO2. Full article
(This article belongs to the Special Issue Minerals in Coal)
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<p>Location of the Pingshuo Mine in the Ningwu Coalfield, Shanxi Province, China.</p>
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<p>Generalized stratigraphic column: (<b>a</b>) of the Late Pennsylvanian-Permian coal measures in the Ningwu coalfield and sampling profiles; and (<b>b</b>) of the No. 4 Coal in the Pingshuo Coal Mine.</p>
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<p>Variation of total sulfur and proximate analysis through the Pingshuo coal section.</p>
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<p>XRD patterns of coal samples (PS4-9).</p>
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<p>Minerals in the Pingshuo coals (SEM, secondary electron images): (<b>a</b>) kaolinite in thin-layered forms; and (<b>b</b>) flocculent kaolinite.</p>
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<p>Concentration coefficients (CC) of trace elements in the Pingshuo coals.</p>
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<p>Cluster analysis of the geochemical data of the Pennsylvanian Pingshuo coal samples.</p>
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<p>Correlations between Fe<sub>2</sub>O<sub>3</sub> and total sulfur in the Pingshuo coals.</p>
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<p>Correlations between Li and ash yield (Ad), SiO<sub>2</sub> and Al<sub>2</sub>O<sub>3</sub>.</p>
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<p>Correlations between Hg and total sulfur.</p>
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<p>Correlations of Sr and Ba with: P<sub>2</sub>O<sub>5</sub> (<b>a</b>); and CaO (<b>b</b>).</p>
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<p>Vertical variation of Zr and Hf in the profile of the Pingshuo coals.</p>
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<p>Correlations of Zr and Hf with: TiO<sub>2</sub> (<b>a</b>); and K<sub>2</sub>O (<b>b</b>).</p>
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3433 KiB  
Article
Mineralogical and Geochemical Compositions of the No. 5 Coal in Chuancaogedan Mine, Junger Coalfield, China
by Ning Yang, Shuheng Tang, Songhang Zhang and Yunyun Chen
Minerals 2015, 5(4), 788-800; https://doi.org/10.3390/min5040525 - 25 Nov 2015
Cited by 20 | Viewed by 4565
Abstract
This paper reports the mineralogy and geochemistry of the Early Permian No. 5 coal from the Chuancaogedan Mine, Junger Coalfield, China, using optical microscopy, scanning electron microscopy (SEM), Low-temperature ashing X-ray diffraction (LTA-XRD) in combination with Siroquant software, X-ray fluorescence (XRF), and inductively [...] Read more.
This paper reports the mineralogy and geochemistry of the Early Permian No. 5 coal from the Chuancaogedan Mine, Junger Coalfield, China, using optical microscopy, scanning electron microscopy (SEM), Low-temperature ashing X-ray diffraction (LTA-XRD) in combination with Siroquant software, X-ray fluorescence (XRF), and inductively coupled plasma mass spectrometry (ICP-MS). The minerals in the No. 5 coal from the Chuancaogedan Mine dominantly consist of kaolinite, with minor amounts of quartz, pyrite, magnetite, gypsum, calcite, jarosite and mixed-layer illite/smectite (I/S). The most abundant species within high-temperature plasma-derived coals were SiO2 (averaging 16.90%), Al2O3 (13.87%), TiO2 (0.55%) and P2O5 (0.05%). Notable minor and trace elements of the coal include Zr (245.89 mg/kg), Li (78.54 mg/kg), Hg (65.42 mg/kg), Pb (38.95 mg/kg), U (7.85 mg/kg) and Se (6.69 mg/kg). The coal has an ultra-low sulfur content (0.40%). Lithium, Ga, Se, Zr and Hf present strongly positive correlation with ash yield, Si and Al, suggesting they are associated with aluminosilicate minerals in the No. 5 coal. Arsenic is only weakly associated with mineral matter and Ge in the No. 5 coals might be of organic and/or sulfide affinity. Full article
(This article belongs to the Special Issue Minerals in Coal)
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<p>Location of the Chuancaogedan Mine in the Junger Coalfield, northern China (modified after Dai <span class="html-italic">et al.</span> [<a href="#B10-minerals-05-00525" class="html-bibr">10</a>]).</p>
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<p>Stratigraphic sequence of the Junger Coalfield [<a href="#B9-minerals-05-00525" class="html-bibr">9</a>].</p>
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<p>Variation of total sulfur and proximate analysis through the No. 5 Coal section.</p>
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<p>Minerals in the No. 5 Coal (reflected light): (<b>A</b>) kaolinite in dispersed form; (<b>B</b>) kaolinite in-filling cells; (<b>C</b>) kaolinite with organic matter; and (<b>D</b>) pyrite in vitrinite.</p>
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<p>Minerals in the No. 5 Coal (SEM, secondary electron images): (<b>A</b>) kaolinite as thin-layered forms; (<b>B</b>) flocculent kaolinite; (<b>C</b>) pyrite aggregates; and (<b>D</b>) columnar gypsum.</p>
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<p>X-ray diffraction (XRD) patterns of coal samples (ZG509).</p>
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