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Minerals
Volume 12
Issue 9
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Minerals, Volume 12, Issue 9 (September 2022) – 118 articles

Cover Story (view full-size image): The Dinaridic Ozren ophiolite complex in Bosnia and Herzegovina contains troctolites replacing dunite layers in harzburgite. Troctolite is crosscut by doleritic and plagioclase(Pl)-rich dykes and veins. The secondary Pl enrichment of dunite (relic black pods) reflets a Pl-clinopyroxene(Cpx) melt impregnation of dunite. Microscopic and back-scattered-electron images from troctolite document newly formed plagioclase Pl and Cpx enclosing olivine (Ol) and spinel (Spl) of dunite. The secondary phases are amphibole (Amp), phlogopite (Phl), albite (Ab) and strontianite (Str). The percolating melt was likely formed by decompression and partial melting of a refractory peridotite in the asthenosphere and via a reaction of this melt with peridotite at the base of the thinning thermal lithosphere. View this paper
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17 pages, 5756 KiB  
Article
Chlorellestadite (Synth): Formation, Structure, and Carbonate Substitution during Synthesis of Belite Clinker from Wastes in the Presence of CaCl2 and CO2
by Krassimir Garbev, Angela Ullrich, Günter Beuchle, Britta Bergfeldt and Peter Stemmermann
Minerals 2022, 12(9), 1179; https://doi.org/10.3390/min12091179 - 19 Sep 2022
Cited by 4 | Viewed by 1974
Abstract
The synthesis of low-temperature belite (C2S) clinker from wastes of autoclaved aerated concrete and limestone was studied in the presence of CaCl2 as a mineralizing agent. Synthetic chlorellestadite (SCE; Ca10(SiO4)3(SO4)3Cl [...] Read more.
The synthesis of low-temperature belite (C2S) clinker from wastes of autoclaved aerated concrete and limestone was studied in the presence of CaCl2 as a mineralizing agent. Synthetic chlorellestadite (SCE; Ca10(SiO4)3(SO4)3Cl2) forms in experiments at temperatures between 700 and 1200 °C. Samples were investigated by X-ray diffraction and Raman spectroscopy. In general, the amount of SCE depends mainly on the sulfate content and to a lesser extent on the synthesis temperature. At lower temperatures of formation, a non-stoichiometric SCE seems to crystallize in a monoclinic symmetry similar to hydroxylellestadite. Rietveld refinements revealed the presence of chlorine and calcium vacancies. Raman spectroscopy proved the partial substitution of sulfate by CO32− groups in ellestadites formed at 800 °C and 900 °C in air. Incorporation of CO3 results in a shorter unit cell parameters and smaller cell volume similar to CO3−apatite. At low temperatures, SCE coexists with spurrite intermixed on a very fine nm scale. At temperatures above 900 °C in air, ellestadite is carbonate-free and above 1000 °C chlorine loss starts in all samples. Full article
(This article belongs to the Special Issue Cement Related Minerals—in Memory of Herbert Pöllmann)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Synthetic crystalline phase contents in samples D2 and P after thermal treatment at 700–1200 °C. Only phase contents &gt; 2 wt% are shown. (<b>a</b>) Consumption of raw materials (quartz + calcite + anhydrite) and formation of main products C2S (<span class="html-italic">β</span>-C2S + <span class="html-italic">α</span>′H-C2S) and ellestadite; (<b>b</b>) Chlorine-containing intermediate phases (chlormayenite and rusinovite);(<b>c</b>) Intermediate phases (spurrite, wollastonite and lime; lime in P &lt; 0.5 wt%, wollastonite in D2 &lt; 1.5 wt%); (<b>d</b>) Minor phases (chlorine free) formed at high temperatures: ternesite, bredigite, melilite, and rankinite, ternesite in P &lt; 0.5 wt%, rankinite &lt; 1 wt.%, and melilite &lt; 1.5 wt% in D2.</p> Full article ">Figure 2
<p>(<b>a</b>) Hexagonal structure of Ca<sub>9.82</sub>(SiO<sub>4</sub>)<sub>3</sub>(SO<sub>4</sub>)<sub>3</sub>Cl<sub>1.64</sub> (ICSD: 262245: [<a href="#B20-minerals-12-01179" class="html-bibr">20</a>]); (<b>b</b>) monoclinic structure of Ca<sub>9.94</sub>(SiO<sub>4</sub>)<sub>3</sub>(SO<sub>4</sub>)<sub>3</sub>(O H)<sub>1.2</sub>O<sub>0.5</sub>Cl<sub>0.32</sub> (ICSD: 39775, [<a href="#B19-minerals-12-01179" class="html-bibr">19</a>]). For explanation see text.</p> Full article ">Figure 3
<p>XRD patterns of sample D2 calcined at different temperatures. (<b>a</b>) 21–23° 2 theta range, splitting of the hexagonal 020 reflection (1000 °C) to 002, 200, −202 monoclinic reflections (sample 800 °C). The decreasing intensity ratio of the 111/020 reflections in the samples from 1000 to 800 °C corresponds to incorporation of CO<sub>3</sub> instead of SO<sub>4</sub> groups; (<b>b</b>) 30.5–33.5° 2 theta range. Samples treated at 800, 900, and 950 °C, show very broad peaks pointing to lower symmetry and/or very small size of coherent scattering domains. The integral breadth of the doublet 211 and −312 with three additional reflections with low intensity (monoclinic) is 0.235° 2 theta in the 800 °C sample, whereas the corresponding hexagonal reflection 121 shows 0.135° 2 theta in the 1000 °C sample.</p> Full article ">Figure 4
<p>Structural parameters of ellestadite as a function of synthesis temperature (hex = hexagonal, mcl = monoclinic): (<b>a</b>) variation of the unit-cell volume of hexagonal and monoclinic ellestadite in sample series D2 and P. For comparison, literature data of Ca<sub>9.82</sub>(SiO<sub>4</sub>)<sub>3</sub>(SO<sub>4</sub>)<sub>3</sub>Cl<sub>1.64</sub> [<a href="#B20-minerals-12-01179" class="html-bibr">20</a>,<a href="#B21-minerals-12-01179" class="html-bibr">21</a>] is shown; (<b>b</b>) atoms per formula unit for sulfur and chlorine in ellestadite; and (<b>c</b>,<b>d</b>) variation of a-, b- and c-axes in ellestadite with synthesis temperature (700–950 °C: mcl and 1000–1200 °C: hex). The γ-angle in the monoclinic structure varies between 119.94 and 120.05°.</p> Full article ">Figure 5
<p>Fragment of the structure of monoclinic Ca<sub>10</sub>(SiO<sub>4</sub>)<sub>3</sub>(SO<sub>4</sub>)<sub>3</sub>Cl<sub>2</sub> according to the structure of Ca<sub>9.94</sub>(SiO<sub>4</sub>)<sub>3</sub>(SO<sub>4</sub>)<sub>3</sub>(O H)<sub>1.2</sub>O<sub>0.5</sub>Cl<sub>0.32</sub> determined by Organova et al. [<a href="#B19-minerals-12-01179" class="html-bibr">19</a>]. T (S) and T (Si,S) tetrahedral sites can partially accommodate CO<sub>3</sub> groups. Ca (3) is the site with Ca deficiency.</p> Full article ">Figure 6
<p>Raman spectra of SCE D2 samples calcined at temperatures 800, 900, 1000, and 1100 °C (from bottom to top) In addition, the Raman spectrum of SCE obtained from calcination of the P sample at 1200 °C is shown (top). Samples 800 and 900 °C proof CO<sub>3</sub> groups in the ellestadite structure.</p> Full article ">Figure 7
<p>Raman spectra at different spots of the sample HT[D2]_800 showing different degrees of intermixing of calcite (bottom), spurrite, and ellestadite. The bands due to the ν<sub>1</sub> CO<sub>3</sub> vibration of calcite (1086 cm<sup>−1</sup>), spurrite (1080 cm<sup>−1</sup>), and ellestadite (1070 cm<sup>−1</sup>), can be clearly distinguished.</p> Full article ">Figure 8
<p>Selected Raman spectra of HT[D2]_800 presenting different degrees of intermixing between spurrite (bottom) and CO<sub>3</sub>-ellestadite (top).</p> Full article ">Figure 9
<p>Basis Raman spectra used for Raman imaging of HT[D2]_800. From top to bottom: ellestadite, spurrite, calcite, <span class="html-italic">β</span>-C<sub>2</sub>S, anhydrite.</p> Full article ">Figure 10
<p>Electron microphotographs showing SE images of an aggregate of the sample HT[D2]_800 (<b>a</b>), the elemental distribution of Ca (<b>b</b>), S (<b>c</b>), Cl (<b>d</b>), and C (<b>e</b>). Superimposed Raman and SE image of the phase distribution of spurrite, ellestadite, calcite, and anhydrite (<b>f</b>).</p> Full article ">Figure 11
<p>Top: overlay of an electron micrograph (SE) of an aggregate of sample D2 calcined at 800 °C with a corresponding Raman image of the phase distribution in false colors (red: calcite; blue: spurrite; green: ellestadite; light blue: anhydrite C<span>$</span>). Bottom: a 3D image of the same aggregate (same color scheme). Right: clipped 3D image of the cube marked as a yellow cube (rotated at 90°). Presence of <span class="html-italic">β</span>-C<sub>2</sub>S crystal (purple) formed at the interface between spurrite (Sp), ellestadite (Ell), and calcite (Cc).</p> Full article ">
20 pages, 23764 KiB  
Article
Exploring High-Resolution Chemical Distribution Maps of Incompatible and Scarce Metals in a Nepheline Syenite from the Massif of “Serra de Monchique” (Portugal, Iberian Peninsula)
by Sofia Barbosa, António Dias, Diogo Durão, José Grilo, Gonçalo Baptista, Jonhsman Cagiza, Sofia Pessanha, Joaquim Simão and José Almeida
Minerals 2022, 12(9), 1178; https://doi.org/10.3390/min12091178 - 19 Sep 2022
Cited by 1 | Viewed by 1728
Abstract
In this case study, 2D micro energy dispersive X-ray fluorescence (µ-EDXRF) surveys were performed in the nepheline syenite (NS) of “Serra de Monchique” located in the southwest region of Portugal (Algarve, Iberian Peninsula). The results allow the identification in the mineral matrix of [...] Read more.
In this case study, 2D micro energy dispersive X-ray fluorescence (µ-EDXRF) surveys were performed in the nepheline syenite (NS) of “Serra de Monchique” located in the southwest region of Portugal (Algarve, Iberian Peninsula). The results allow the identification in the mineral matrix of certain elements classified as critical raw materials (CRMs). Due to substitution effects, some scarce transition elements, such as Zn and Ni, are present and camouflaged in alkali silicate minerals, while others, such as Co, are included in ferromagnesian mineral phases. As expected, incompatible elements are preferably distributed on the surface of aluminosilicate mineral phases such as Rb and Ga, or exclusively in K-bearing feldspar phases, as it is the case of Sr. Interesting CRMs such as Ti, Zr, and Nb are well individualized in oxides, as well as in sphene and apatite. The detected antagonistic chemical distribution between Ti and Fe, and the good spatial relation between Ti and Ca confirms that Ti is present as sphene and, in areas with absent Si, probably occurs as rutile. Nb has a distribution pattern quite similar to Zr and occurs due to substitution effects. It was possible to conclude that there is probable co-existence of Zr-REE-Nb in specific mineral phases such as apatite, zircon, and other Zr-oxides. These results evidence and confirm NS as a potential source of multiple industrial minerals and distinct scarce elements which are incorporated in oxide or phosphate phases that can be more effectively separated in the beneficiation process. Full article
(This article belongs to the Section Crystallography and Physical Chemistry of Minerals & Nanominerals)
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Figure 1

Figure 1
<p>(<b>a</b>) Lithostratigraphic units in Serra the Monchique massif and its surroundings and main geological structures (adapted from “Geological Map of the Algarve Region (Portugal), scale 1/100000”, source of information: <a href="https://geoportal.lneg.pt/" target="_blank">https://geoportal.lneg.pt/</a> (accessed on 25 July 2022)); (<b>b</b>) Localization of the “Serra de Monchique” massif in the context of southwestern Europe and Iberia; and (<b>c</b>) tested sample of the “Serra the Monchique” nepheline syenite (polished surface with indication of the area selected for µ- EDXRF surveys) with the indication of some of the occurrences of mineral phases nepheline (N), K-felspar (K-F), and aegirine-augite (Ae-Au). Mineral superficial alteration (SA) is also indicated.</p> Full article ">Figure 2
<p>Original mineral sample, µ-EDXRF and interpretative maps: (<b>a</b>) Image of mineral matrix (sample), (<b>b</b>) Si µ-EDXRF map; (<b>c</b>) K µ-EDXRF map, (<b>d</b>) Al µ-EDXRF map, (<b>e</b>) interpretative K map, (<b>f</b>) Na µ-EDXRF map, and (<b>g</b>) Cl µ-EDXRF map.</p> Full article ">Figure 3
<p>P (green) and Cl (orange) µ-EDXRF maps.</p> Full article ">Figure 4
<p>Spatial distribution and correspondence between (<b>a</b>) Rb and Si, Al, and K, (<b>b</b>) Sr and K, and (<b>c</b>) Ga and Al.</p> Full article ">Figure 5
<p>Spatial distribution and correspondence between Ba and Si, Al, K, and Na.</p> Full article ">Figure 6
<p>(<b>a</b>) Image of original mineral sample (mineral matrix), (<b>b</b>) Zn µ-EDXRF map, (<b>c</b>) Zn distribution in the mineral matrix (overlap of images (<b>a</b>,<b>b</b>)). Zn distribution and its correlations with (<b>d</b>) Fe, (<b>e</b>) S, (<b>f</b>) K, and (<b>g</b>) Al.</p> Full article ">Figure 7
<p>(<b>a</b>) Image of original mineral sample (mineral matrix), (<b>b</b>) Ni µ-EDXRF map, (<b>c</b>) Ni distribution in the mineral matrix (overlap of images (<b>a</b>)), and Ni distribution and its correlations with (<b>d</b>) K, (<b>e</b>) Al, (<b>f</b>) Zn, and (<b>g</b>) Fe.</p> Full article ">Figure 8
<p>(<b>a</b>) Image of original minera sample (mineral matrix). Interpretative maps with evidence of (<b>b</b>) areas without Si and without K or (<b>c</b>) areas without Al and without K. Distributions of (<b>d</b>) Fe, and (<b>e</b>) Mn relative to Si.</p> Full article ">Figure 9
<p>Elemental spatial micrometric distribution of Ca, Mg, Fe, Mn, and Co in the mineral matrix.</p> Full article ">Figure 10
<p>Interpretative overlap of spatial micrometric distribution maps of Ti with Fe and Ca.</p> Full article ">Figure 11
<p>Elemental spatial micrometric distributions between Zr&amp;Si and Zr&amp;Si&amp;Ca.</p> Full article ">Figure 12
<p>Elemental spatial micrometric distribution of (<b>a</b>) Ti, (<b>b</b>) Ti&amp;Zr, (<b>c</b>) Ti&amp;Fe, (<b>d</b>) Nb, (<b>e</b>) Nb&amp;Zr, and (<b>f</b>) Nb&amp;Fe.</p> Full article ">Figure 13
<p>Nb and Zr µ-EDXRF maps and their co-localization statistics. (<b>a</b>) Pixel correlation scatter plot, (<b>b</b>) pixel frequency distribution, and (<b>c</b>) Pearson’s coefficient correlation (PCC) and Manders overlap coefficient (MOC).</p> Full article ">Figure 14
<p>Elemental spatial micrometric distributions of P&amp;Ca and Nb&amp;Ca.</p> Full article ">Figure 15
<p>Nb, Zr, and Ca spatial micrometric distributions in mineral matrix; Nb and Zr estimated occurrence as a percentage of area (%) through the method “Two colors—spheric search radius criteria” as described in <a href="#sec2dot3-minerals-12-01178" class="html-sec">Section 2.3</a>.</p> Full article ">
23 pages, 3630 KiB  
Review
Advances in Pulsed Power Mineral Processing Technologies
by Valentine A. Chanturiya and Igor Zh. Bunin
Minerals 2022, 12(9), 1177; https://doi.org/10.3390/min12091177 - 19 Sep 2022
Cited by 6 | Viewed by 2805
Abstract
In Russia and globally, pulsed power technologies have been proposed based on the conversion of energy into a short-pulsed form and exposing geomaterials (minerals, rocks, and ores) to strictly dosed high-power pulsed electric and magnetic fields, beams of charged particles, microwave radiation, neutrons [...] Read more.
In Russia and globally, pulsed power technologies have been proposed based on the conversion of energy into a short-pulsed form and exposing geomaterials (minerals, rocks, and ores) to strictly dosed high-power pulsed electric and magnetic fields, beams of charged particles, microwave radiation, neutrons and X-ray quanta, and low-temperature plasma flows. Such pulsed energy impacts are promising methods for the pretreatment of refractory mineral feeds (refractory ores and concentration products) to increase the disintegration, softening, and liberation performance of finely disseminated mineral complexes, as well as the contrast between the physicochemical and process properties of mineral components. In this paper, we briefly review the scientific foundations of the effect of both high-power nanosecond electromagnetic pulses (HPEMP) and dielectric barrier discharge (DBD) in air on semiconductor ore minerals (sulfides, rare metals minerals) and rock-forming dielectric minerals. The underlying mechanisms of mineral intergrowth disintegration and changes in the structural and chemical states of the mineral surface when exposed to HPEMP and DBD irradiation are discussed. The high performance and potential limitations of pulsed energy impact and low-temperature plasma produced by DBD treatment of geomaterials are discussed in terms of the directional change in the process properties of the minerals to improve the concentration performance of refractory minerals and ores. Full article
(This article belongs to the Special Issue Selective Disintegration of Ores and Physicochemical Properties of Minerals Under High-Power Electromagnetic Pulses and Other High Pulsed Powers Effects)
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Figure 1
<p>Schemes of (<b>a</b>) electropulse and (<b>b</b>) electrohydraulic technologies; presented in the paper [<a href="#B36-minerals-12-01177" class="html-bibr">36</a>]: 1—high-voltage pulse generator, 2—switchboard, 3—discharge chamber filled with liquid, 4—electrode system, 5—technology specimen. Adapted with permission from Ref. [<a href="#B36-minerals-12-01177" class="html-bibr">36</a>]. Copyright 2019, Publishing House of the Ural University.</p> Full article ">Figure 2
<p>Electrohydraulic installations of the ElectroHydroDynamika Group (St. Petersburg, Russia): (<b>a</b>) laboratory installation EGDL-10 and (<b>b</b>) industrial modular installation EGD-10 [<a href="#B79-minerals-12-01177" class="html-bibr">79</a>]: <span class="html-italic">1</span>—feed unit, <span class="html-italic">2</span>—reactor, <span class="html-italic">3</span>—pulse current generators, <span class="html-italic">4</span>—air discharger, <span class="html-italic">5</span>—capacitor unit, <span class="html-italic">6</span>—material sampling unit, <span class="html-italic">7</span>—water buffer tank, <span class="html-italic">8</span>—water supply pump, <span class="html-italic">9</span>—slurry pump. Reprinted with permission from Ref. [<a href="#B79-minerals-12-01177" class="html-bibr">79</a>]. Copyright 2017–2021, ElectroHydroDynamics.</p> Full article ">Figure 3
<p>Damaged pyrite surface as a result of exposure to HPEMP. SEM; scale bars: (<b>a</b>) 90 μm, (<b>b</b>) 40 μm, and (<b>c</b>) 30 μm.</p> Full article ">Figure 4
<p>Modular installations for the treatment of mineral products by high-power nanosecond electromagnetic pulses with a capacity of (<b>a</b>) 20 kg/h, (<b>b</b>) 100–120 kg/h; (<b>c</b>) generator of high-voltage nanosecond pulses (U<sub>A</sub> up to 70 kV), and (<b>d</b>) structural scheme of the installation with a capacity of 1 ton/h: <span class="html-italic">1</span>—block for receiving and forming the flow of ore, <span class="html-italic">2</span>—conveyor for moving the ore flow, <span class="html-italic">3</span>—electrode system, <span class="html-italic">4</span>—support plate for electrode system, <span class="html-italic">5</span>—high-voltage pulse generator with a sharpener block, <span class="html-italic">6</span>—core and mineral treatment unit, <span class="html-italic">7</span>—receiver-accumulator for mineral raw materials after HPEMP treatment, <span class="html-italic">8</span>—conveyor drive.</p> Full article ">Figure 5
<p>(<b>a</b>) Distribution of condensed matter at the late stage of iron vapor outflow from the nanosecond breakdown channel of sulfide minerals (pyrite); presented in the paper [<a href="#B117-minerals-12-01177" class="html-bibr">117</a>]. (<b>b</b>,<b>c</b>) New formations of the iron oxides (hydroxides) on the surface of (<b>b</b>) pyrite and (<b>c</b>) arsenopyrite after treatment by HPEMP (<span class="html-italic">t</span><sub>treat</sub> = 10–30 s). SEM−EDX; scale bars: (<b>b</b>,<b>c</b>) 20 μm.</p> Full article ">Figure 6
<p>(<b>a</b>,<b>b</b>) Eudialyte and (<b>c</b>) perovskite surface after treatment by HPEMP (<span class="html-italic">t</span><sub>treat</sub> = 30–90 s). SEM; scale bars: (<b>a</b>) 70, (<b>b</b>) 80, (<b>c</b>) 50 μm.</p> Full article ">Figure 7
<p>(<b>a</b>) Schematic representation of a cell of a dielectric barrier discharge: 1—flat metal electrodes of plate form, 2—layer of the ground mineral, 3—plate of dielectric, 4—high voltage power supply. Reprinted with permission from Ref. [<a href="#B125-minerals-12-01177" class="html-bibr">125</a>]. Copyright 2019, Andreev V.V. (<b>b</b>) Galena and (<b>c</b>) perovskite surface after treatment by DBD (<span class="html-italic">t</span><sub>treat</sub> = 50 s). SEM; scale bars: (<b>b</b>) 300, (<b>c</b>) 40 μm.</p> Full article ">
14 pages, 8442 KiB  
Article
The Analysis of Bio-Precursor Organic Matter Compositions and Its Significance for Gas Shale Reservoir of Wufeng–Longmaxi Formation from Dingshan Area, Sichuan Basin
by Zhihong Wang, Xiaomin Xie, Zhigang Wen, Yaohui Xu and Yan Liu
Minerals 2022, 12(9), 1176; https://doi.org/10.3390/min12091176 - 19 Sep 2022
Cited by 1 | Viewed by 1331
Abstract
In order to analyze the organic matter (OM) composition, this study carefully identified the OM types of 66 samples from Well A in the Dingshan area under microscope, and made an effort to obtain the semi-quantitative statistics contents of different bio-precursor derived OM. [...] Read more.
In order to analyze the organic matter (OM) composition, this study carefully identified the OM types of 66 samples from Well A in the Dingshan area under microscope, and made an effort to obtain the semi-quantitative statistics contents of different bio-precursor derived OM. The results of OM content obtained under microscope showed a strong positive relationship (R2 = 0.85) with the TOC content analyzed by carbon–sulfur analyzer. The OM contained bethic algae debris, phytoplankton amorphous organic matter (AOM), acritarch, vitrinite-like particles, zooplankton (including graptolite, chitinozoa and others) and solid bitumen which was secondary formation OM. The phytoplankton AOM, graptolite and solid bitumen were the dominated OM in this interval. Solid bitumen (8%~11%) was filled at the bottom of the Wufeng Formation, which could be one reason for the high shale gas production in the lower part of this shale interval. N2 adsorption results showed that micropores and mesopores were predominant in this shale gas system, while pore volumes illustrated better positive relationships with organic matter than minerals, especially AOM content. Thus, both solid bitumen and AOM kerogen were the main sources for shale gas generation in this shale gas system. Full article
(This article belongs to the Special Issue Shale and Tight Reservoir Characterization and Resource Assessment)
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Figure 1
<p>The location of Sichuan Basin (<b>a</b>), the Dingshan area (DSA) (<b>b</b>), and the geological column of Sichuan Basin (<b>c</b>) (modified from Wang et al. [<a href="#B14-minerals-12-01176" class="html-bibr">14</a>]).</p> Full article ">Figure 2
<p>The geological column, TOC and sulfur contents, and main mineral compositions of samples from Well A in the Dingshan area, Sichuan Basin.</p> Full article ">Figure 3
<p>The micro-photos of graptolite. (<b>a</b>) Graptolite along the bedding (arrows), transmitted polarized light, ×50. (<b>b</b>,<b>c</b>) Graptolite along the bedding (arrows), showing the silica content surrounding the graptolite under transmitted polarized light (<b>b</b>) and orthogonal light (<b>c</b>), ×100. (<b>d</b>–<b>i</b>) Graptolite showing the silica content surrounding the graptolite under transmitted polarized light (<b>d</b>,<b>g</b>), orthogonal light (<b>e</b>,<b>h</b>) and reflect light (<b>f</b>,<b>i</b>), oil immersion, ×500.</p> Full article ">Figure 4
<p>Micro-photos of bio-precursor organic matter. (<b>a</b>–<b>d</b>) Debris of multicellular benthic algae, showing multicellular structure of algae. (<b>e</b>–<b>h</b>) Acritarch, with (<b>e</b>) showing the acritarch in the rocks, while (<b>f</b>–<b>h</b>) were acritarchs in the isolated kerogen, including species <span class="html-italic">Multiplicisphaeridium</span> sp (<b>f</b>), <span class="html-italic">Goniosphaeridium</span> sp (<b>g</b>) and <span class="html-italic">Buedingiisphaeridium</span> sp (<b>h</b>). (<b>i</b>,<b>j</b>) Multicellular benthic algae debris in the isolated kerogen. (<b>k</b>) Chitinozoa in the isolated kerogen. Transmitted polarized light, ×500. Scale bar= 50 µm (<b>a</b>–<b>e</b>), =10 µm (<b>f</b>–<b>k</b>).</p> Full article ">Figure 5
<p>Micro-photos of solid bitumen (arrows). (<b>a</b>–<b>d</b>) Solid bitumen filled in the intergranular pore. (<b>e</b>,<b>f</b>) Solid bitumen filled in the micro-fractures along the bedding. (<b>a</b>,<b>c</b>,<b>e</b>) were micro-photos under transmitted polarized light; (<b>b</b>,<b>d</b>,<b>f</b>) were micro-photos under reflected light. Oil immersion, ×500. Scale bar = 50 µm.</p> Full article ">Figure 6
<p>The plots of porosity vs. depth (<b>a</b>) and porosity vs. TOC (<b>b</b>) of core samples from Well A in Sichuan Basin, with both showing positive relationships.</p> Full article ">Figure 7
<p>Nitrogen adsorption-desorption isotherms for samples from Well A in the Dingshan area of Sichuan Basin, showing similar type and the volume adsorbed decreased with TOC content.</p> Full article ">Figure 8
<p>The relative (<b>a</b>) and quantitative (<b>b</b>) bio-precursor organic matter composition.</p> Full article ">Figure 9
<p>(<b>a</b>) The plots of TOC and organic matter content measured under microscope. (<b>b</b>) Quantitative organic matter composition varied with depth. Note: Quantitative composition = organic matter content × relative percentage of organic matter.</p> Full article ">Figure 10
<p>(<b>a</b>) The plots of TOC and S contents. (<b>b</b>,<b>c</b>) The micro-photos of A-36 (3697.1 m), showing pyrite agglomerate developed in this sample, reflect light. (<b>d</b>,<b>e</b>) The micro-photos of A-4 (3727.5), showing much solid bitumen filled (red oval in <a href="#minerals-12-01176-f010" class="html-fig">Figure 10</a>a, and arrows) in the micropore surrounding the mineral particles.</p> Full article ">Figure 11
<p>Microphotos under scanning electron microscope (SEM), showing abundant pores with nanometers to micrometers developed in organic matter. (<b>a</b>–<b>e</b>): Pores in original kerogen organic matter residues (A type), (<b>a1</b>) showing that pores were irregular and small. (<b>f</b>–<b>i</b>): Pores (B type, elliptical and near circular) in the migrated solid bitumen which filled in the holes among mineral particles, micro-fractures along bedding or interlayer fractures in clay minerals (e.g., illite, <a href="#minerals-12-01176-f011" class="html-fig">Figure 11</a>f).</p> Full article ">Figure 12
<p>The plots of total pore volume from N<sub>2</sub> adsorption and pore volume calculated by porosity. Total pore volume = Micropores + Mesopores + Macropores; Calculated pore volume = (1/ρ<sub>rock</sub>) × Porosity.</p> Full article ">Figure 13
<p>The plots of pores characterizations and minerals. (<b>a</b>) Porosity vs. Organic matter composition; (<b>b</b>) Pore volume vs. TOC; (<b>c</b>) Pore volume vs. AOM; (<b>d</b>) Pore volume vs. Graptolite; (<b>e</b>) Pore volume vs. Solid bitumen; (<b>f</b>) Mineral composition vs. Porosity; (<b>g</b>) Pore volume vs. Clay; (<b>h</b>) Pore volume vs. Quartz; (<b>i</b>) Pore volume vs. Carbonate.</p> Full article ">
15 pages, 4094 KiB  
Article
Evaluation of the Shrinkage Produced with the Use of Cements with Pozzolanic Additions in the Production of Concrete
by Maria Betania Diaz-Garcia, Yosvany Diaz-Cardenas, Juan Ribalta-Quesada and Fernando Martirena-Hernandez
Minerals 2022, 12(9), 1175; https://doi.org/10.3390/min12091175 - 19 Sep 2022
Cited by 1 | Viewed by 1384
Abstract
Early age cracking in concrete is caused by a combination of the chemical and autogenous shrinkage caused by the exhaustion of the water in the pores during the hydration of cement phases. Generally, this process takes place in the first 72 h of [...] Read more.
Early age cracking in concrete is caused by a combination of the chemical and autogenous shrinkage caused by the exhaustion of the water in the pores during the hydration of cement phases. Generally, this process takes place in the first 72 h of concrete casting. The use of supplementary cementitious materials (SCMs) can mitigate cracking due to several factors, among them: dilution effect, provision of extra nucleation sites due to the high specific surface of the SCMs, and the increased water retention associated with the presence of fine SCMs. This paper compares the impact of two SCMs systems on early age cracking of the following concretes: (i) pozzolanic cement with natural pozzolan (zeolite) and (ii) a ternary binder limestone-calcined clay cement (LC3). The study was Carried out on cement paste and concrete. The addition of calcined clay and limestone decreases early age cracking better than in any other system, including the Portland-pozzolan system. It is related to a lower clinker factor and improved hydration of the system, and a better-developed microstructure at early ages due to the energetic reaction of the alumina phase C3A, enhanced by the extra alumina (Al2O3) provided by the calcined clay. Full article
(This article belongs to the Special Issue Blended Cements Incorporating Calcined Clay and Limestone)
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<p>Effect of type of binder on volume changes in paste: (<b>a</b>) LC3 binder, (<b>b</b>) Pozzolanic cement containing 15% of natural pozzolan binder.</p> Full article ">Figure 2
<p>Effect of water/cement ratio on volume changes in paste: (<b>a</b>) combinations of OPC and LC2 binder, (<b>b</b>) pozzolanic cement containing 15% of natural pozzolan binder (PPC).</p> Full article ">Figure 3
<p>Effect of chemical admixtures on volume changes in paste: (<b>a</b>) combinations of OPC and LC2 binder, (<b>b</b>) pozzolanic cement containing 15% of natural pozzolan (PPC) binder.</p> Full article ">Figure 4
<p>Impact of cement type on hydration in cementitious systems. (<b>a</b>) LC3 binder, (<b>b</b>) Pozzolanic cement containing 15% of natural pozzolan binder.</p> Full article ">Figure 5
<p>Effect of calcined clay addition on Slump.</p> Full article ">Figure 6
<p>Effect of calcined clay addition on compressive strength.</p> Full article ">Figure 7
<p>Effect of binder type on concrete shrinkage 24 h.</p> Full article ">Figure 8
<p>Relationship between shrinkage in concrete and hydration of cement: (<b>a</b>) combinations of OPC and LC2, and (<b>b</b>) pozzolanic cement containing 15% of natural pozzolan binder (PPC).</p> Full article ">Figure 9
<p>Impact of the water–cement ratio on volume change in concrete.</p> Full article ">Figure 10
<p>Long term shrinkage in concrete prisms.</p> Full article ">Figure 11
<p>Strength vs. strain.</p> Full article ">Figure 12
<p>Effective Porosity vs. strain.</p> Full article ">
14 pages, 4302 KiB  
Article
Three-Dimensional Mineral Prospectivity Modeling for Delineation of Deep-Seated Skarn-Type Mineralization in Xuancheng–Magushan Area, China
by Fandong Meng, Xiaohui Li, Yuheng Chen, Rui Ye and Feng Yuan
Minerals 2022, 12(9), 1174; https://doi.org/10.3390/min12091174 - 18 Sep 2022
Cited by 5 | Viewed by 2349
Abstract
The Middle–Lower Yangtze River Metallogenic Belt is an important copper and iron polymetallic metallogenic belt in China. Today’s economic development is inseparable from the support of metal mineral resources. With the continuous exploitation of shallow and easily identifiable mines in China, the prospecting [...] Read more.
The Middle–Lower Yangtze River Metallogenic Belt is an important copper and iron polymetallic metallogenic belt in China. Today’s economic development is inseparable from the support of metal mineral resources. With the continuous exploitation of shallow and easily identifiable mines in China, the prospecting work of deep and hidden mines is very important. Mineral prospectivity modeling (MPM) is an important means to improve the efficiency of mineral exploration. With the increase in resource demands and exploration difficulty, the traditional 2DMPM is often difficult to use to reflect the information of deep mineral deposits. More large-scale deposits are needed to carry out 3DMPM research. With the rise of artificial intelligence, the combination of machine learning and geological big data has become a hot issue in the field of 3DMPM. In this paper, a case study of 3DMPM is carried out based on the Xuancheng–Magushan area’s actual data. Two machine learning methods, the random forest and the logistic regression, are selected for comparison. The results show that the 3DMPM based on random forest method performs better than the logistic regression method. It can better characterize the corresponding relationship between the geological structure combination and the metallogenic distribution, and the accuracy in the test set reaches 96.63%. This means that the random forest model could provide more effective and accurate support for integrating predictive data during 3DMPM. Finally, five prospecting targets with good metallogenic potential are delineated in the deep area of the Xuancheng–Magushan area for future exploration. Full article
(This article belongs to the Special Issue 3D/4D Geological Modeling for Mineral Exploration)
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<p>Workflow of three-dimension prospectivity mapping.</p> Full article ">Figure 2
<p>The location of Xuancheng–Magushan Area, volcanic basins, and ore concentration areas (OCAs) within the middle and lower Yangtze River Metallogenic Belt as well as the location of major settlements, faults, and major tectonic features. (Modified from Chang et al. [<a href="#B41-minerals-12-01174" class="html-bibr">41</a>], Mao et al. [<a href="#B42-minerals-12-01174" class="html-bibr">42</a>], and Ye. [<a href="#B43-minerals-12-01174" class="html-bibr">43</a>]).</p> Full article ">Figure 3
<p>Geological map of Magushan Cu-Mo deposit. (Modified from Bian. [<a href="#B19-minerals-12-01174" class="html-bibr">19</a>], Ye. [<a href="#B43-minerals-12-01174" class="html-bibr">43</a>], and Hong et al. [<a href="#B44-minerals-12-01174" class="html-bibr">44</a>]).</p> Full article ">Figure 4
<p>Gravity and magnetic inversion interpretation and profile-verification flow chart.</p> Full article ">Figure 5
<p>3D model of the Xuancheng–Magushan Area. (Modified from Ye. [<a href="#B43-minerals-12-01174" class="html-bibr">43</a>] and Hu et al. [<a href="#B45-minerals-12-01174" class="html-bibr">45</a>]).</p> Full article ">Figure 6
<p>Block model of Xuancheng–Magushan Area.</p> Full article ">Figure 7
<p>Standard Deviation maps of random forest algorithm under different parameters.</p> Full article ">Figure 8
<p>Distribution map of favorable areas, (<b>a</b>) Random forest model results; (<b>b</b>) Logistic regression model results.</p> Full article ">Figure 9
<p>Comparison of ROC curves.</p> Full article ">Figure 10
<p>Capture efficiency curves.</p> Full article ">Figure 11
<p>Delineation of prospecting target areas.</p> Full article ">
33 pages, 9288 KiB  
Article
Construction and Application of a Knowledge Graph for Gold Deposits in the Jiapigou Gold Metallogenic Belt, Jilin Province, China
by Yao Pei, Sheli Chai, Xiaolong Li, Jofrisse Cremilda Samuel, Chengyou Ma, Haonan Chen, Renxing Lou and Yu Gao
Minerals 2022, 12(9), 1173; https://doi.org/10.3390/min12091173 - 17 Sep 2022
Cited by 3 | Viewed by 2135
Abstract
Over the years, many geological exploration reports and considerable geological data have been accumulated during the prospecting and exploration of the Jiapigou gold metallogenic belt (JGMB). It is very important to fully utilize these geological and mineralogical big data to guide future gold [...] Read more.
Over the years, many geological exploration reports and considerable geological data have been accumulated during the prospecting and exploration of the Jiapigou gold metallogenic belt (JGMB). It is very important to fully utilize these geological and mineralogical big data to guide future gold exploration. This work collects the original textual data of different gold deposits in JGMB and constructs a knowledge graph (KG) for deposits based on deep learning (DL) and natural language processing (NLP). Based on the metallogenic geological characteristics of deposits, a visual construction method of a KG for deposits and a calculation of the similarity between deposits are proposed. In this paper, 20 geological entities and 24 relationship categories are considered. By condensing the key KG information, the metallogenic geological conditions and factors controlling the ore in 14 typical deposits in the JGMB are systematically analyzed, and the metallogenic regularity is summarized. By calculating the deposits’ cosine similarities based on the KG, the mineralization types of deposits can be divided into two categories according to the industrial types of ore bodies. The results also show that the KG is a cutting-edge technology that can extract the rich information of ore-forming regularity and prospecting criteria contained in the textual data to help researchers quickly analyze the mineralization information. Full article
(This article belongs to the Special Issue Application of Big Data Mining, Machine Learning and Artificial Intelligence in Ore Deposits)
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Graphical abstract
Full article ">Figure 1
<p>(<b>a</b>) Location of NE China with respect to the main tectonic units of China and Russia [<a href="#B9-minerals-12-01173" class="html-bibr">9</a>,<a href="#B12-minerals-12-01173" class="html-bibr">12</a>,<a href="#B13-minerals-12-01173" class="html-bibr">13</a>], ‘A’ and ‘M’ represent the ‘Altaids’ and ‘Manchurides’, respectively. (<b>b</b>) Tectonic units of NE China [<a href="#B9-minerals-12-01173" class="html-bibr">9</a>,<a href="#B12-minerals-12-01173" class="html-bibr">12</a>,<a href="#B13-minerals-12-01173" class="html-bibr">13</a>]. (<b>c</b>) Regional geological map of the JGMB and distribution of major gold deposits [<a href="#B14-minerals-12-01173" class="html-bibr">14</a>,<a href="#B15-minerals-12-01173" class="html-bibr">15</a>]. Gold deposits: 1. Songjianghe; 2. Liupiye; 3. Bajiazi; 4. Jiapigou; 5. Erdaogou; 6. Sidaocha; 7. Sandaocha; 8. Xiaobeigou; 9. Daxiangou; 10. Laoniugou; 11. Caiqiangzi; 12. Banmiaozi; 13. Damiaozi; 14. Yuanchaogou. Main faults in (<b>a</b>,<b>b</b>): ① Mudanjiang Fault; ② Dunhua–Mishan Fault; ③ Yilan−Yitong Fault; ④ Xar Moron–Changchun Fault; ⑤ Hegenshan–Heihe Fault; ⑥ Tayuan–Xiguitu Fault. Reproduced with permission from Elsevier, Journal of Asian Earth Sciences; published by Elsevier, 2016. Reproduced with permission from Elsevier, Gondwana Research; published by Elsevier, 2013. Reproduced with permission from Elsevier, Journal of Asian Earth Sciences; published by Elsevier, 2007.</p> Full article ">Figure 2
<p>The neural network architectures of Bi-LSTM and CRF [<a href="#B48-minerals-12-01173" class="html-bibr">48</a>].</p> Full article ">Figure 3
<p>The bidirectional LSTM model with attention [<a href="#B67-minerals-12-01173" class="html-bibr">67</a>].</p> Full article ">Figure 4
<p>The KG construction framework.</p> Full article ">Figure 5
<p>The construction structure of the KG for gold deposits. A1 is the node representing the secondary fault. A2 is the node representing the fault character.</p> Full article ">Figure 6
<p>The performance of the α coefficient on the proposed method.</p> Full article ">Figure 7
<p>The relationship between the deposits and geological entities.</p> Full article ">Figure 8
<p>A subgraph for the plutons, intrusive rocks, and ore deposits.</p> Full article ">Figure 9
<p>A subgraph for the dykes and ore deposits.</p> Full article ">Figure 10
<p>A subgraph for metamorphic rocks, extrusive rocks, sedimentary rocks, and ore deposits.</p> Full article ">Figure 11
<p>A subgraph for the regional fault, secondary fault, fault character, and ore deposits.</p> Full article ">Figure 12
<p>The MSE deviation of the <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values among different datasets.</p> Full article ">Figure 13
<p>The accuracy of different similarity calculation methods: (<b>a</b>) the recognition accuracy of the cosine similarity using all geological entities with their <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values; (<b>b</b>) the recognition accuracy of the Jaccard coefficient using all geological entities; (<b>c</b>) the recognition accuracy of the cosine similarity using the geological entities with the top ten <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values; (<b>d</b>) the recognition accuracy of the Jaccard coefficient using the geological entities with the top ten <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values; (<b>e</b>) the recognition accuracy of the cosine similarity after removing the geological entities with the top ten <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values; (<b>f</b>) the recognition accuracy of the cosine similarity after removing the geological entities with the top ten <span class="html-italic">TF</span>-<span class="html-italic">IDF</span> values.</p> Full article ">Figure 14
<p>The distribution of the geological characteristic entities in the KG for each deposit.</p> Full article ">Figure 15
<p>The clustering effect between typical deposits calculated by similarity. Colors of the connecting lines: green indicates similarity values ≥ 0.7, red indicates similarity values from 0.6–0.69, and gray indicates similarity values &lt; 0.6.</p> Full article ">Figure 16
<p>The accuracy comparison between the proposed method and the already studied methods: (<b>a</b>) the proposed method; (<b>b</b>) cosine similarity; (<b>c</b>) Jaccard coefficient; (<b>d</b>) TransE.</p> Full article ">Figure 17
<p>Visualization of the Songjiang gold deposit metallogenic model based on the KG.</p> Full article ">Figure 18
<p>A comparison of the geological entities of the Songjianghe, Liupiye, and Jiapigou gold deposits based on the KG.</p> Full article ">Figure 19
<p>The geological model for the prospecting prediction of typical deposits in the JGMB based on the KG.</p> Full article ">
18 pages, 3925 KiB  
Article
Numerical Simulation Study on the Relationships between Mineralized Structures and Induced Polarization Properties of Seafloor Polymetallic Sulfide Rocks
by Caowei Wu, Changchun Zou, Cheng Peng, Yang Liu, Tao Wu, Jianping Zhou and Chunhui Tao
Minerals 2022, 12(9), 1172; https://doi.org/10.3390/min12091172 - 17 Sep 2022
Cited by 2 | Viewed by 1597
Abstract
The induced polarization (IP) method plays an important role in the detection of seafloor polymetallic sulfide deposits. Numerical simulations based on the Poisson–Nernst–Planck equation and the Maxwell equation were performed. The effects of mineralized structures on the IP and electrical conductivity properties of [...] Read more.
The induced polarization (IP) method plays an important role in the detection of seafloor polymetallic sulfide deposits. Numerical simulations based on the Poisson–Nernst–Planck equation and the Maxwell equation were performed. The effects of mineralized structures on the IP and electrical conductivity properties of seafloor sulfide-bearing rocks were investigated. The results show that total chargeability increases linearly as the volume content of disseminated metal sulfides increases when the volume content is below 20%. However, total chargeability increases nonlinearly with increasing volume content in vein and massive metal sulfides when the volume content is below 30%. The electrical resistivity of disseminated metal sulfides mainly depends on the conductivity of pore water. The electrical resistivity of vein and massive sulfides mainly depends on the volume content and the length of sulfides. Increase in the aspect ratio (0.36 to 0.93) of seafloor massive sulfides causes relaxation time constants and total chargeability to decrease. Relaxation time constants and total chargeability also decrease with increase in the tortuosity of seafloor vein sulfides from 1.0 to 1.38. This study is of great value for the electrical survey of seafloor polymetallic sulfide deposits. Full article
(This article belongs to the Special Issue Development Methods and Technologies Used in Deep-Sea Mining)
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<p>Representative mineralization structures in a seafloor polymetallic sulfide deposit. (<b>a</b>) Cross-sectional view of the distribution of the mineralized zones of a seafloor polymetallic sulfide deposit, modified from Fouquet et al. (2013) [<a href="#B28-minerals-12-01172" class="html-bibr">28</a>]. (<b>b</b>) Photographs of drill cores from seafloor sulfide deposits corresponding to the three kinds of mineralization. The photographs of the drill cores are from Marques et al. (2007) [<a href="#B29-minerals-12-01172" class="html-bibr">29</a>], Zierenberg et al. (1998) [<a href="#B30-minerals-12-01172" class="html-bibr">30</a>], and Anderson et al. (2019) [<a href="#B31-minerals-12-01172" class="html-bibr">31</a>]. (<b>c</b>) Schematic of three representative mineralized sulfide-bearing rocks. (<b>d</b>) Numerical models of seafloor sulfide-bearing rocks with various mineralized structures together with the finite-element mesh for the 2D numerical simulations. The grey circles denote basalt, the yellow zones denote metal sulfides, and the blue zones denote NaCl solution with a salinity close to that of seawater.</p> Full article ">Figure 2
<p>Sketch of TDIP measurement and the IP phenomenon. (<b>a</b>) Time-domain induced polarization measurement. (<b>b</b>) Induced polarization effect of a metal sulfide grain and basaltic/clay grain in the electrolyte.</p> Full article ">Figure 3
<p>Flow chart of the numerical simulation process based on the Poisson–Nernst–Planck equation.</p> Full article ">Figure 4
<p>The relationship between chargeability and volume content in seafloor metal sulfides. The simulation data (vein sulfide models, massive sulfide models, and disseminated sulfide models) are from the present study. The experimental data for natural seafloor sulfide rocks are from Chen et al. (2021) [<a href="#B37-minerals-12-01172" class="html-bibr">37</a>] and Komori et al. (2017) [<a href="#B10-minerals-12-01172" class="html-bibr">10</a>]. The type of sulfides used in Chen et al. (2021) was disseminated and the Komori study included disseminated and massive sulfides. The experimental data for synthetic seafloor sulfide rocks are from Wu et al. (2021) [<a href="#B15-minerals-12-01172" class="html-bibr">15</a>]. The red line denotes the prediction of the models proposed by Revil et al. (2015) [<a href="#B18-minerals-12-01172" class="html-bibr">18</a>]. In this model, the value of total chargeability was equal to 4.5 times the value of the volume content of disseminated metal sulfides.</p> Full article ">Figure 5
<p>Dependence of the total chargeabilities and relaxation time constants of seafloor sulfide-bearing rocks on the aspect ratios and tortuosities of metal sulfides. (<b>a</b>) The total chargeabilities, M, and the relaxation time constants, τ, for the seafloor massive metal sulfide models with various aspect ratios. (<b>b</b>) The total chargeabilities, M, and relaxation time constants, τ, for the seafloor vein metal sulfide models with various tortuosities.</p> Full article ">Figure 6
<p>Relaxation time distributions for the seafloor disseminated metal sulfide models with sulfide particles with various grain radii. The blue line denotes models containing fine sulfide particles with a grain radius of 1 mm; the red line denotes models containing coarse sulfide particles with a grain radius of 4 mm; the yellow line denotes models containing both fine and coarse sulfide particles in equal proportions.</p> Full article ">Figure 7
<p>Dependence of the relaxation time distributions of seafloor sulfide-bearing rocks on the aspect ratios and tortuosities of metal sulfides. (<b>a</b>) The relaxation time distributions for seafloor massive metal sulfide models with various aspect ratios. (<b>b</b>) The relaxation time distributions for seafloor vein metal sulfide models with various tortuosities.</p> Full article ">Figure 8
<p>Dependence of the resistivities of seafloor sulfide-bearing rocks on the volume contents of metal sulfides and the electrical conductivity of seawater. (<b>a</b>) Resistivity versus volume content for the metal sulfides. (<b>b</b>) Resistivity versus electrical conductivity for seawater.</p> Full article ">Figure 9
<p>Electric-current density distributions of models of seafloor sulfide-bearing rocks under a horizontal electric field. (<b>a</b>) Disseminated sulfide models with various sulfide contents of 4%, 12%, and 20%. (<b>b</b>) Vein sulfide models with various sulfide contents of 10%, 20%, and 30%. (<b>c</b>) Massive sulfide models with various sulfide contents of 10%, 20%, and 30%. The red zones denote a high electric-current density, which means that more current flows through these areas.</p> Full article ">Figure 10
<p>Dependence of relaxation time constants on the square of half of the length and half of the length of seafloor massive sulfides. (<b>a</b>) Relaxation time constants versus the squares of half of the lengths. (<b>b</b>) Relaxation time constants versus half of the lengths.</p> Full article ">Figure 11
<p>Influence of the tortuosities of vein metal sulfides on the migration of electrons during the induced polarization. (<b>a</b>) The numerical simulation results for the concentration distributions of electrons inside the vein metal sulfide models with various tortuosities just after the cutoff. (<b>b</b>) Schematic representation of the surface charge distributions around polarized vein metal sulfides with different tortuosities.</p> Full article ">
3 pages, 225 KiB  
Editorial
First-Principles Calculations of Minerals and Related Materials
by Jordi Ibáñez-Insa
Minerals 2022, 12(9), 1171; https://doi.org/10.3390/min12091171 - 16 Sep 2022
Viewed by 1173
Abstract
As stated in their announcements and accompanying information, Special Issues published in scientific journals are usually aimed at compiling recent progress on highly specialized topics [...] Full article
(This article belongs to the Special Issue First Principles Calculations of Minerals and Related Materials)
16 pages, 4112 KiB  
Article
The Challenge of Grinding Ternary Blends Containing Calcined Clays and Limestone
by Juan Francisco Garces-Vargas, Yosvany Díaz-Cardenas, Franco Zunino, Juan Ribalta-Quesada, Karen Scrivener and Fernando Martirena
Minerals 2022, 12(9), 1170; https://doi.org/10.3390/min12091170 - 16 Sep 2022
Cited by 4 | Viewed by 2365
Abstract
The inclusion of high specific surface materials such as calcined clays in cementitious systems enhances the hydration of clinker products at very early ages, but it may also increase water demand; thus, the pursuit of a flowing concrete may demand an increase in [...] Read more.
The inclusion of high specific surface materials such as calcined clays in cementitious systems enhances the hydration of clinker products at very early ages, but it may also increase water demand; thus, the pursuit of a flowing concrete may demand an increase in the dosage of superplasticizers. The grinding regime can have a major influence on the properties of the cementitious system and could help mitigate the problem of water demand. This paper discusses the impact of grinding alternatives for the production of a binder consisting of clinker, calcined clay, limestone and gypsum. Two main target products will be discussed: (i) LC3, a binder with a formulation of 50% clinker, 30% calcined clay, 15% limestone and 5% gypsum, co-ground all together, and (ii) LC2, a mineral addition with a formulation of 60% calcined clay, 35% limestone and 5% gypsum, ground separately and further blended with Portland cement on a 1:1 basis (mass). The experimental program is carried out in several stages: (i) the binder, (ii) cement pastes and (iii) standard mortars, and concrete grinding aids from the family TEA are used to enhance grinding, and their impact is also be assessed. Full article
(This article belongs to the Special Issue Blended Cements Incorporating Calcined Clay and Limestone)
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<p>Particle size distributions of the aggregates, (<b>a</b>) coarse aggregate (CA), (<b>b</b>) fine aggregate (FA).</p> Full article ">Figure 2
<p>Influence of grinding time on PSD of calcined clay.</p> Full article ">Figure 3
<p>Impact of grinding calcined clay with limestone.</p> Full article ">Figure 4
<p>Comparison of co-grinding LC3 with separate grinding LC2.</p> Full article ">Figure 5
<p>Comparison of compressive strength results between co-grinding LC3 with separate grinding LC2.</p> Full article ">Figure 6
<p>Impact of the use of grinding aids on co-grinding LC3.</p> Full article ">Figure 7
<p>Impact of the use of grinding aids on the hydration of LC3.</p> Full article ">Figure 8
<p>Impact of the use of grinding aids on compressive strength.</p> Full article ">Figure 9
<p>Impact of the use of grinding aids on separate grinding LC2.</p> Full article ">Figure 10
<p>Impact of the use of grinding aids on the hydration of a blend of 50% OPC + 50% LC2.</p> Full article ">Figure 11
<p>Summary of the impact of the grinding strategy on strength in standard mortars.</p> Full article ">Figure 12
<p>Slump in concrete made for testing.</p> Full article ">Figure 13
<p>Measurement of trapped air in the concrete produced.</p> Full article ">Figure 14
<p>Compressive strength in concrete.</p> Full article ">
30 pages, 12290 KiB  
Article
The Evolution of Permian Source-to-Sink Systems and Tectonics Implications in the NW Junggar Basin, China: Evidence from Detrital Zircon Geochronology
by Xingyu Chen, Zhijie Zhang, Xuanjun Yuan, Li Wan, Chuanmin Zhou, Yinhe Liu and Dawei Cheng
Minerals 2022, 12(9), 1169; https://doi.org/10.3390/min12091169 - 15 Sep 2022
Cited by 2 | Viewed by 1642
Abstract
The basin type of the Junggar Basin changed during the Permian, but the time constraint of the tectonic evolution remains unclear. Besides, the fan deltas developed in the Permian in the Mahu Sag in the northwestern of the oil-rich basin. However, the provenances [...] Read more.
The basin type of the Junggar Basin changed during the Permian, but the time constraint of the tectonic evolution remains unclear. Besides, the fan deltas developed in the Permian in the Mahu Sag in the northwestern of the oil-rich basin. However, the provenances of the sedimentary systems remain unclear. Based on petrology and detrital zircon U-Pb ages, this study investigates the source-to-sink systems evolution and tectonics implications. Abundant lithic clasts in sandstones with low compositional and textural maturity imply proximal sources. The dating results showed a dominant peak (310–330 Ma) and a secondary peak (400–440 Ma) in the northern Mahu Sag, only one peak at 295–325 Ma in the central Mahu Sag, several peaks at 270–350 Ma in the southern Mahu Sag, and multiple peaks at 370–450 Ma in the Zhongguai Uplift. Thus, the north-western Junggar Basin was divided into four major source-to-sink systems, with adjacent central West Junggar as the main provenance and northern and southern West Junggar as the secondary provenance. The proportion of sediment supply from the southern and northern West Junggar is higher during the Middle-Late Permian. It suggests that the source-to-sink systems show inheritance and evolve from a single provenance into a complex provenance, indicating the uplift of West Junggar. The tectonic inversion may occur early in the Middle Permian and the response to tectonic activity is stronger in the southern West Junggar than in the northern West Junggar. Full article
(This article belongs to the Section Mineral Geochemistry and Geochronology)
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<p>(<b>a</b>) Structural diagram of West Junggar and adjacent areas [<a href="#B53-minerals-12-01169" class="html-bibr">53</a>]. (<b>b</b>) Topographic map of West Junggar and adjacent areas, showing the main faults in the periphery of the basin [<a href="#B44-minerals-12-01169" class="html-bibr">44</a>]. (<b>c</b>) Geological map of West Junggar [<a href="#B54-minerals-12-01169" class="html-bibr">54</a>] and the tectonic unit division map of the northwestern margin of the Junggar Basin (modified according to Xinjiang Oilfield Company). The area inside the orange box is the study area. WJ = West Junggar. The red dashed box in subpanel (<b>b</b>) is magnified in subpanel (<b>c</b>).</p> Full article ">Figure 2
<p>Generalized stratigraphic columns of the studied Permian series. See text for series descriptions and zircon geochronology [<a href="#B72-minerals-12-01169" class="html-bibr">72</a>,<a href="#B73-minerals-12-01169" class="html-bibr">73</a>].</p> Full article ">Figure 3
<p>Core characteristics of (<b>a</b>) alluvial fan (JL42, 2892.52–2895.34 m), (<b>b</b>) fan delta plain (MH25, 3695.36–3697.36 m), (<b>c</b>) proximal fan delta front (J206, 4068.55–4070.44 m), (<b>d</b>) distal fan delta front (MH20, 4241–4242.86 m) and (<b>e</b>) shallow lake (JL49, 4547.84–4549.5 m) deposits.</p> Full article ">Figure 4
<p>Representative photomicrographs of textures and minerals of the lithic clasts and detrital grains under plane-polarized light. The sandstone from the (<b>a</b>) Jiamuhe Formation (Sample ID: G15-04, sandstone clastic component: Q16%, F10%, L74%), (<b>b</b>) Fengcheng Formation (Sample ID: B25-01, Q11%, F22%, L67%), (<b>c</b>) Xiazijie Formation (Sample ID: 817-01, Q22%, F28%, L50%), (<b>d</b>) Lower Wuerhe Formation (Sample ID: MH012-2, Q6%, F29%, L65%) and (<b>e</b>) Upper Wuerhe Formation (Sample ID: JT1-2, Q9%, F21%, L70%). (<b>f</b>) The conglomerate with the pebbles of sedimentary and volcanic rocks from the Lower Wuerhe Formation (Sample ID: C73). Abbreviations of minerals: F, feldspar; FLv, felsic volcanic clasts; Ls, sedimentary lithic fragment; MLv, mafic volcanic clasts; Q, quartz; T, tuff.</p> Full article ">Figure 5
<p>(<b>a</b>) The plot of Th/U ratios versus zircon U-Pb ages of detrital zircons from detrital samples in Permian deposits from the Mahu-Zhongguai area, northwestern Junggar Basin. (<b>b</b>) The chondrite-normalized REE patterns for zircons of magmatic origin for typical Permian samples from the Mahu-Zhongguai area, northwestern Junggar Basin.The values of chondrite are from [<a href="#B79-minerals-12-01169" class="html-bibr">79</a>].</p> Full article ">Figure 6
<p>U-Pb age probability density plots of Permian detrital zircons from detrital samples in the Mahu-Zhongguai area, northwestern Junggar Basin. The age distribution is shown by a pie chart on the left for each sample. The cathodoluminescence images of some detrital zircon samples are shown in the rightmost column. The locations and details of detrital zircon samples are shown in <a href="#minerals-12-01169-f001" class="html-fig">Figure 1</a> and listed in <a href="#minerals-12-01169-t001" class="html-table">Table 1</a>.</p> Full article ">Figure 7
<p>Zircon age distributions of magmatic and metamorphic rocks in northern West Junggar (NWJ), including the Zharma-Saur arc and Boshchekul-Chingiz arc, central West Junggar (CWJ), southern West Junggar (SWJ), and the Junggar Basin, shown as histograms, probability density plots, and pie charts. Data from Xu et al. [<a href="#B31-minerals-12-01169" class="html-bibr">31</a>], Chen et al. [<a href="#B40-minerals-12-01169" class="html-bibr">40</a>], Yang et al. [<a href="#B45-minerals-12-01169" class="html-bibr">45</a>], Li et al. [<a href="#B80-minerals-12-01169" class="html-bibr">80</a>], Li et al. [<a href="#B81-minerals-12-01169" class="html-bibr">81</a>], Jian et al. [<a href="#B82-minerals-12-01169" class="html-bibr">82</a>], Han et al. [<a href="#B83-minerals-12-01169" class="html-bibr">83</a>], Zhou et al. [<a href="#B84-minerals-12-01169" class="html-bibr">84</a>], Geng et al. [<a href="#B85-minerals-12-01169" class="html-bibr">85</a>], Chen et al. [<a href="#B86-minerals-12-01169" class="html-bibr">86</a>], Feng et al. [<a href="#B87-minerals-12-01169" class="html-bibr">87</a>,<a href="#B88-minerals-12-01169" class="html-bibr">88</a>], Shang et al. [<a href="#B89-minerals-12-01169" class="html-bibr">89</a>], Tang et al. [<a href="#B90-minerals-12-01169" class="html-bibr">90</a>], Yang et al. [<a href="#B91-minerals-12-01169" class="html-bibr">91</a>], Tian et al. [<a href="#B92-minerals-12-01169" class="html-bibr">92</a>], Xiang et al. [<a href="#B93-minerals-12-01169" class="html-bibr">93</a>], Zhang et al. [<a href="#B94-minerals-12-01169" class="html-bibr">94</a>], Jin et al. [<a href="#B95-minerals-12-01169" class="html-bibr">95</a>], Chen et al. [<a href="#B96-minerals-12-01169" class="html-bibr">96</a>], Tang et al. [<a href="#B97-minerals-12-01169" class="html-bibr">97</a>], Yin et al. [<a href="#B98-minerals-12-01169" class="html-bibr">98</a>], Yin et al. [<a href="#B99-minerals-12-01169" class="html-bibr">99</a>], Duan et al. [<a href="#B100-minerals-12-01169" class="html-bibr">100</a>].</p> Full article ">Figure 8
<p>Spatial distribution of the zircon-tourmaline-rutile (ZTR) index of the Lower Wuerhe Formation in the Mahu-Zhongguai area.</p> Full article ">Figure 9
<p>(<b>a</b>) Distributions of U-Pb ages of detrital zircons in the Lower Wuerhe Formation in the Mahu-Zhongguai area, northwestern Junggar Basin. (<b>b</b>) Multidimensional scaling diagram. The samples were classified according to the similarity of age distribution characteristics and geographical location. The multi-dimensional scaling diagrams can measure the similarity of multiple samples in different locations but in the same period. The locations and details of detrital zircon samples are shown in <a href="#minerals-12-01169-f001" class="html-fig">Figure 1</a> and listed in <a href="#minerals-12-01169-t001" class="html-table">Table 1</a>.</p> Full article ">Figure 10
<p>(<b>a</b>) Diagram of U-Pb detrital zircon age distribution in the Upper Wuerhe Formation in the Mahu-Zhongguai area, northwestern Junggar Basin. (<b>b</b>) Multidimensional scaling diagram. The samples were grouped according to the similarity in age distribution characteristics and geographical location. The multi-dimensional scaling diagram shows the similarity of multiple samples in different locations but in the same period. The locations and details of detrital zircon samples are shown in <a href="#minerals-12-01169-f001" class="html-fig">Figure 1</a> and listed in <a href="#minerals-12-01169-t001" class="html-table">Table 1</a>.</p> Full article ">Figure 11
<p>Schematic diagram of the distribution of the source-to-sink systems during the (<b>a</b>) Early Permian, (<b>b</b>) Middle Permian and (<b>c</b>) Late Permian in the Mahu-Zhongguai area, northwestern Junggar Basin. CWJ + NWJ→NMS: The source-to-sink system with central West Junggar (CWJ) and northern West Junggar (NWJ) as the main provenances and the northern Mahu Sag (NMS) as the depositional area. CWJ→CMS: The source-to-sink system with CWJ as the provenance and the central Mahu Sag (CMS) as the depositional area. CWJ + NWJ→SMS: The source-to-sink system with CWJ and NWJ as the main provenances and the southern Mahu Sag (SMS) as the depositional area. CWJ + SWJ→ZU: The source-to-sink system with CWJ and southern West Junggar (SWJ) as the provenances and the Zhongguai Uplift (ZU) as the depositional area. The green capital letters indicate the potential parent rock ages in each unit; the red capital letters indicate the possible stratigraphic age to provide the sediments in the area. The distribution map of sedimentary facies was prepared by the Xinjiang Oilfield Company. Note: The Upper Permian series in the NMS was eroded, and relevant data of the lower Permian series was lacking. Therefore, the CWJ + NWJ→NMS systems in the Early and Late Permian were all results speculated according to the inheritance of the source-to-sink systems and are represented by dashed lines in the figure.</p> Full article ">Figure 12
<p>Distribution of the U-Pb ages of Permian detrital zircons over time. (<b>a</b>) The source-to-sink system CWJ→CMS in the central Mahu Sag (CMS). (<b>b</b>) The source-to-sink system CWJ + NWJ→SMS in the southern Mahu Sag (SMS). (<b>c</b>) The source-to-sink system CWJ + SWJ→ZU in the Zhongguai uplift (ZU). The strata become younger from bottom to top.</p> Full article ">
17 pages, 5965 KiB  
Article
Macro-Microscopic Deterioration Behavior of Gypsum Rock after Wetting and Its Constitutive Model Based on Acoustic Emission
by Xiaoding Xu, Yuejin Zhou, Weiqiang Chen, Yubing Gao, Qiang Fu, Xue Liu and Chundi Feng
Minerals 2022, 12(9), 1168; https://doi.org/10.3390/min12091168 - 15 Sep 2022
Cited by 8 | Viewed by 1929
Abstract
Gypsum rock is highly sensitive to a water environment due to its unique physical and chemical properties, such as high solubility. After wetting, the internal microstructure of gypsum rock is damaged, and the mechanical properties deteriorate accordingly, leading to serious engineering problems for [...] Read more.
Gypsum rock is highly sensitive to a water environment due to its unique physical and chemical properties, such as high solubility. After wetting, the internal microstructure of gypsum rock is damaged, and the mechanical properties deteriorate accordingly, leading to serious engineering problems for gypsum-bearing geotechnical structures. Therefore, it is particularly necessary to investigate the mechanical deterioration behavior of gypsum rock after wetting. In this paper, the mechanical behavior of gypsum rocks with different water contents were studied. The relationship between the rock water content and the water immersion time was established through the water content test. The scanning electron microscope (SEM) images of the gypsum rock after the water immersion showed that the internal microstructure of the gypsum rock became looser and more complex as the immersion time increased. The fractal dimensions of the SEM images were calculated to quantify the degree of damage to the gypsum rocks after wetting. These images showed that the degree of damage increased with the increasing immersion time, but the increase rate tended to be slow. The relationship between the rock water content and the mechanical responses of gypsum rock were established by triaxial compression tests, and the concomitant acoustic emission (AE) characteristics in the loading processes showed that the immersion time had a positive correlation with the AE frequency and a negative correlation with the AE cumulative count. Based on the AE characteristics, a damage constitutive model of gypsum rock as a function of immersion time was developed and this can reproduce the mechanical responses of gypsum rock after wetting. Full article
(This article belongs to the Topic Support Theory and Technology of Geotechnical Engineering)
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<p>A standard sample of gypsum rock.</p> Full article ">Figure 2
<p>The rock sample under triaxial compression and the microscopic element, where <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mn>1</mn> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mn>2</mn> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mn>3</mn> </msub> </mrow> </semantics></math> are the three principal stresses, and <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>c</mi> </msub> </mrow> </semantics></math> is the applied circumferential confining pressure.</p> Full article ">Figure 3
<p>The relationship between the rock water content and the immersion time.</p> Full article ">Figure 4
<p>SEM images of the rock samples with different water immersion times: (<b>a</b>) Natural, (<b>b</b>) 7 days, (<b>c</b>) 15 days, and (<b>d</b>) 30 days.</p> Full article ">Figure 5
<p>The analysis procedure of the fractal dimension of the SEM image.</p> Full article ">Figure 6
<p>The calculation of the fractal dimension for the gypsum rock with different soak times: (<b>a</b>) Natural, (<b>b</b>) 7 days, (<b>c</b>) 15 days, and (<b>d</b>) 30 days.</p> Full article ">Figure 7
<p>(<b>a</b>) The relationship between the fractal dimension/degree of damage and the water immersion time. (<b>b</b>) The relationship between the fractal dimension/degree of damage and the water content.</p> Full article ">Figure 8
<p>The stress-strain curves of the gypsum rocks after immersion in water for different durations.</p> Full article ">Figure 9
<p>The relationship between the triaxial compressive strength and the rock water content.</p> Full article ">Figure 10
<p>The relationship between the elastic modulus and the rock water content.</p> Full article ">Figure 11
<p>The relationship between the Poisson’s ratio and the rock water content.</p> Full article ">Figure 12
<p>The stress-time-AE count curves of the gypsum rocks with the different immersion times: (<b>a</b>) Natural, (<b>b</b>) 1 day, (<b>c</b>) 7 days, (<b>d</b>) 15 days, and (<b>e</b>) 30 days.</p> Full article ">Figure 13
<p>The stress-time-AE cumulative count curves of the gypsum rocks with the different water immersion durations, where <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mrow> <mi>ci</mi> </mrow> </msub> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mrow> <mi>ci</mi> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mrow> <mi>cd</mi> </mrow> </msub> </mrow> </semantics></math> indicate the crack initiation stress, the secondary crack stress, and the crack damage stress: (<b>a</b>) Natural, (<b>b</b>) 1 day, (<b>c</b>) 7 days, (<b>d</b>) 15 days, and (<b>e</b>) 30 days.</p> Full article ">Figure 14
<p>The experimental and simulated curves of the gypsum rocks under triaxial compressions after immersion in water for different durations: (<b>a</b>) 1 day, (<b>b</b>) 7 days, (<b>c</b>) 15 days, and (<b>d</b>) 30 days.</p> Full article ">
18 pages, 5518 KiB  
Article
The Effects of Hydrochloric Acid Pretreatment on Different Types of Clay Minerals
by Bin Hu, Chunxia Zhang and Xiaoyan Zhang
Minerals 2022, 12(9), 1167; https://doi.org/10.3390/min12091167 - 15 Sep 2022
Cited by 9 | Viewed by 3533
Abstract
Clay minerals are common in geological samples and are useful paleoclimate and sediment provenance proxies. Acid pretreatment is the most common method for the separation and purification of clay minerals. Given that hydrochloric acid (HCl) can dissolve chlorite and distinguish it from kaolinite, [...] Read more.
Clay minerals are common in geological samples and are useful paleoclimate and sediment provenance proxies. Acid pretreatment is the most common method for the separation and purification of clay minerals. Given that hydrochloric acid (HCl) can dissolve chlorite and distinguish it from kaolinite, the HCl digestion method is used to simplify the routine method of clay mineral analysis. However, there have been few studies of the effects of acid digestion on different clay minerals in the context of extracting paleoclimate indicators. In this study, we used illite, chlorite, kaolinite, and two types of smectite to assess the effects of pretreatment with different HCl concentrations at variable temperatures. Our results show that chlorite is the most soluble clay mineral in HCl and can be effectively dissolved in HCl with concentrations of >1 N. The variable crystal structure of smectite affects its solubility in HCl. Ca-rich smectite, which has more cation substitution of octahedral Al, can be dissolved with HCl. However, Na-rich smectite, which has less cation substitution for octahedral Al, is hardly dissolved in HCl of any concentration or at any temperature. Illite can be partly dissolved in HCl, and the threshold beyond which dissolution occurs is 5 N HCl at 70 °C. Kaolinite is relatively difficult to dissolve in HCl. Given that the HCl digestion method uses the peak intensity of the bulk sample X-ray diffraction (XRD) analysis, whereas the routine method uses the peak area of clay particles, we compared the results of clay mineral quantification and the paleoclimate proxy obtained using the two methods for synthetically prepared mixed and natural clay samples. The results obtained with the HCl digestion method are less accurate than those obtained with the routine method because of the dissolution of illite and smectite in HCl. Therefore, the HCl pretreatment method is not suitable for clay mineral analysis in paleoclimate studies. The present results provide reference data for future studies that employ the acid dissolution pretreatment of clay mineral samples to acquire and quantify paleoclimate proxies. Full article
(This article belongs to the Section Clays and Engineered Mineral Materials)
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<p>X-ray diffraction (XRD) patterns of the individual clay mineral samples after different pretreatments with HCl. Black curves are the original standard samples; dark blue curves indicate 21 °C and red curves indicate 70 °C. (<b>A</b>) Ca-smectite (Ca-sme), (<b>B</b>) Na-smectite (Na-sme), (<b>C</b>) chlorite (Chl), (<b>D</b>) illite (Ill), and (<b>E</b>) kaolinite (Kao).</p> Full article ">Figure 2
<p>Ratios of the XRD pattern parameters (i.e., intensity and full width at half maximum (FWHM)) after different pretreatments for Ca-smectite, Na-smectite, chlorite, illite, and kaolinite for each reflection. The y-axis (Y/Y<sub>0</sub>) is the ratio of the reflection after pretreatment to that with no pretreatment, which is intensity/intensity<sub>0</sub> and FWHM/FWHM<sub>0</sub>. The x-axis is the concentration of HCl. (<b>A</b>) Ca-smectite and Na-smectite, (<b>B</b>) chlorite, (<b>C</b>) illite, and (<b>D</b>) kaolinite.</p> Full article ">Figure 3
<p>TEM images of the clay minerals (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>,<b>I</b>,<b>K</b>) without pretreatment and (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>,<b>J</b>,<b>L</b>) after pretreatment with 12 N HCl at 70 °C. Ca-smectite (Ca-Sm) (<b>A</b>) before and (<b>B</b>) after HCl pretreatment; Na-smectite (Na-Sm) (<b>C</b>) before and (<b>D</b>) after HCl pretreatment; chlorite (Chl) (<b>E</b>) before and (<b>F</b>) after HCl pretreatment; talc (<b>G</b>) before and (<b>H</b>) after HCl pretreatment; illite (<b>I</b>) before and (<b>J</b>) after HCl pretreatment; kaolinite (Kao) (<b>K</b>) before and (<b>L</b>) after HCl pretreatment. The red stars mark the sites where EDS data were obtained.</p> Full article ">Figure 3 Cont.
<p>TEM images of the clay minerals (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>,<b>I</b>,<b>K</b>) without pretreatment and (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>,<b>J</b>,<b>L</b>) after pretreatment with 12 N HCl at 70 °C. Ca-smectite (Ca-Sm) (<b>A</b>) before and (<b>B</b>) after HCl pretreatment; Na-smectite (Na-Sm) (<b>C</b>) before and (<b>D</b>) after HCl pretreatment; chlorite (Chl) (<b>E</b>) before and (<b>F</b>) after HCl pretreatment; talc (<b>G</b>) before and (<b>H</b>) after HCl pretreatment; illite (<b>I</b>) before and (<b>J</b>) after HCl pretreatment; kaolinite (Kao) (<b>K</b>) before and (<b>L</b>) after HCl pretreatment. The red stars mark the sites where EDS data were obtained.</p> Full article ">Figure 4
<p>Quantification of the mixed clay samples after different pretreatments.</p> Full article ">Figure 5
<p>Results of clay mineral analysis obtained with the two methods and the actual clay contents of the 24 mixed standard samples. The orange dashed lines are the linear correlations between the height of the main XRD reflection after HCl pretreatment and the actual clay contents. The blue dashed lines are the linear correlations between the results obtained from the routine method and the actual clay contents. (<b>A</b>) Illite, (<b>B</b>) chlorite and kaolinite, (<b>C</b>) kaolinite, and (<b>D</b>) smectite.</p> Full article ">Figure 6
<p>Comparison of the XRD patterns and data obtained for the natural red clay samples versus depth using the HCl pretreatment and routine methods. The orange curves are the ratios of the main XRD reflection height with pretreatment of 1 N HCl at 70 °C (smectite at 14.33 Å, illite at 10.00 Å, chlorite and kaolinite at 7.10 Å before HCl pretreatment; kaolinite at 7.10 Å after HCl pretreatment) to the height of the quartz peak at 3.33 Å. The blue curves are the relative contents of each clay mineral obtained with the routine method. (<b>A</b>) XRD pattern of a representative natural red clay sample. Sme = smectite, Chl = chlorite, Ill = illite, Kao = kaolinite, Qua = quartz, and Alb = albite. (<b>B</b>) Depth changes of the main XRD peak height ratio of Ill (001)/Qua (011) and relative content of Ill. (<b>C</b>) Depth change of the main XRD peak height ratio of Chl (002) + Kao (001)/Qua (011) and relative content of Chl. (<b>D</b>) Depth change of the main XRD peak height ratio of Kao (001)/Qua (011) and relative content of Kao. (<b>E</b>) Depth change of the main XRD peak height ratio of Sme (001)/Qua (011) and relative content of Sme. (<b>F</b>) Depth change of the paleoclimate proxy Sme (001)/(Ill (001) + Chl (002) + Kao (001) and Sme/(Ill + Chl + Kao) ratio.</p> Full article ">
28 pages, 54990 KiB  
Article
Spatio-Temporal Evolution of the Crustal Uplift in Eastern NE China: Constraint from Detrital Zircon Ages of Late Mesozoic Clastic Rocks in the Boli Basin
by Song He, Hong Cheng, Shuangqing Li, Cong Cao, Jun He and Fukun Chen
Minerals 2022, 12(9), 1166; https://doi.org/10.3390/min12091166 - 15 Sep 2022
Cited by 1 | Viewed by 1760
Abstract
Detrital zircon of clastic rocks has been widely recognized as a powerful tool for the study of crustal uplift, which is of great significance for understanding multi-sphere interaction. However, young detrital zircons can only roughly constrain the depositional time of the strata, and [...] Read more.
Detrital zircon of clastic rocks has been widely recognized as a powerful tool for the study of crustal uplift, which is of great significance for understanding multi-sphere interaction. However, young detrital zircons can only roughly constrain the depositional time of the strata, and commonly used zircon age probability density and kernel density estimations cannot provide sufficient evidence to reveal spatio-temporal differences in tectonic uplift. The basins developed in active continental margins usually contain abundant magmatic rocks, which can provide insights into basin evolution and crustal deformation when combined with sedimentary characteristics. In this study, we report detrital zircon ages of Late Mesozoic clastic rocks from the Boli Basin, being part of the Great Sanjiang Basin Group in eastern NE China, which is strongly affected by the Paleo-Pacific subduction. In conjunction with the age data of coeval magmatic rocks and potential sedimentary sources of basement rocks adjacent to the basin, the geochronologic results of this study provide solid evidence for the formation of the Boli Basin and the spatio-temporal evolution of the crustal uplift in northeastern China. The Boli Basin went through multi-phase tectonic evolution of syn-rift and post-rift stages, based on the zircon age data of clastic and igneous rocks. When the geographical distribution characteristics of potential sedimentary sources and their percentages of contribution are taken into account, two stages of eastward migration of the crustal uplift and two episodes of basin destruction caused by the tectonic extension and subsequent compression can be proposed for the Boli Basin. These processes were caused successively by the rolling back of the subducted Paleo-Pacific slab, the docking of the Okhotomorsk block along the eastern continental margin of East Asia, and the transition of the subduction zone by the collision of the Okhotomorsk block. Full article
(This article belongs to the Special Issue Geological Evolution of The Cretaceous and Associated Mineralization)
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<p>Geological map of (<b>a</b>) eastern segment of the Central Asian Orogenic Belt; (<b>b</b>) basin groups in NE China; (<b>c</b>) Great Sanjiang Basin Group; (<b>d</b>,<b>e</b>) stratigraphy and geological map of the Boli Basin, showing distribution of Late Mesozoic clastic rocks and sample localities; (<b>f</b>) seismic profile in the Boli Basin (<b>a</b>,<b>b</b>,<b>f</b> modified after Zhang et al. (2017) [<a href="#B55-minerals-12-01166" class="html-bibr">55</a>]). ①: Xinlin-Xiguitu fault; ②: Hegenshan-Heihe fault; ③: Mudanjiang fault; ④: Yilan-Yitong fault; ⑤: Dunhua-Mishan fault; ⑥: Yuejinshan fault; EB-Erlian Basin, GB-Genhe Basin, SLB-Songliao Basin, HGB-Hegang Basin, SJB-Sanjiang Basin, JMSB-Jiamusi Basin, SYSB-Shuangyashan Basin, SHB-Shuanghua Basin, BLB-Boli Basin, JXB-Jixi Basin, HLB-Hulin Basin; HNU-Huanan uplift, MSU-Mishan uplift, HSU-Hengshan uplift, LXR-Lesser Xing’an Range, ZGCR-Zhuangguangcai Range.</p> Full article ">Figure 2
<p>Photographs of outcrops and micro-photos of Late Mesozoic clastic rocks of the Boli Basin: (<b>a,b</b>) sandstone from the Muling and Didao formations (K<sub>1</sub>m, JX12-11; K<sub>1</sub>d, JX12-10) in the southwestern basin; (<b>c</b>,<b>d</b>) sandstone with fossil from the Muling and Chengzihe formations (K<sub>1</sub>m, HL15; K<sub>1</sub>ch, HL11) in the middle basin; (<b>e</b>,<b>f</b>) pebbly sandstone and mudstone (K<sub>2</sub>h, JX12-7, -8, -4) from the Houshigou Formation. Abbreviation: Q-quartz; Pl-plagioclase; Bi-biotite.</p> Full article ">Figure 3
<p>Zircon U-Pb concordia diagrams of Late Mesozoic clastic rocks from the Boli Basin.</p> Full article ">Figure 4
<p>Zircon CL images and U-Pb probability density diagrams of clastic rocks from the Boli Basin.</p> Full article ">Figure 5
<p>Geological map showing distribution map of the potential provenances for the basin filling. Ⅰ-Hegang Basin, Ⅱ-Jiamusi Basin, III-Shuangyashan Basin, Ⅳ-Shuanghua Basin; ①: Xunke-tieli-shangzhi fault, ②: Jiayi fault, ③: Mudanjiang fault, ④: Xilamulunhe suture, ⑤: Dunmi fault, ⑥: Yuejinshan fault,⑦: Arsen’evsky fault, ⑧: Central Sikhote-Alin fault, ⑨: Fourmanovsky fault; LXR-Lesser Xing’an Range, ZGCR-Zhangguangcai Range, JMSM-Jiamusi massif.</p> Full article ">Figure 6
<p>Probability density diagrams of potential provenances for sedimentary strata of the Boli Basin.</p> Full article ">Figure 7
<p>Time frame of the Great Sanjiang Basin Group, constrained by the dating results of clastic and magmatic rocks. (<b>a</b>–<b>e</b>) time frame of Hegang, Sanjiang, Shuangyashan, Boli and Jixi basins, respectively. ①: clastic rocks from the Hegang Basin [<a href="#B71-minerals-12-01166" class="html-bibr">71</a>]; ②: clastic rocks from the Sanjiang Basin [<a href="#B72-minerals-12-01166" class="html-bibr">72</a>]; ③: clastic rocks of the Muling Formation (K<sub>1</sub>m) from the Jixi Basin [<a href="#B160-minerals-12-01166" class="html-bibr">160</a>]; ④: tuff sandstone and andesite of the Dongshan Formation (K<sub>1</sub>dn) from the Boli Basin [<a href="#B74-minerals-12-01166" class="html-bibr">74</a>]; ⑤: dacite and rhyolite of the Didao Formation (K<sub>1</sub>d) and Peide Formation from the Boli Basin [<a href="#B156-minerals-12-01166" class="html-bibr">156</a>]; ⑥: tephra of the Chengzihe (K<sub>1</sub>ch) and Muling (K<sub>1</sub>m) formations from the Jixi Basin [<a href="#B73-minerals-12-01166" class="html-bibr">73</a>]; *: authors’ unpublished data.</p> Full article ">Figure 8
<p>Line charts of contribution percentage of potential provenances to the Late Mesozoic clastic rocks in the Boli Basin. Variation in contribution percentage of potential provenances from (<b>a</b>) early to middle syn-rift stage, (<b>b</b>) middle syn-rift stage, (<b>c</b>) middle to late syn-rift stage, (<b>d</b>) late syn-rift stage to early post-rift stage and (<b>e</b>) early to late post-rift stage, respectively.</p> Full article ">Figure 9
<p>Sketch model of the crustal uplift and migration in the area of eastern NE China: (<b>a</b>) early syn-rift stage, Zhangguangcai Range uplift; (<b>b</b>,<b>c</b>) early to middle syn-rift stage, uplift areas migrated eastwards beginning from the region near the Mudanjiang fault to the Nadanhada massif; (<b>d</b>) late syn-rift stage, uplift of the Jiamusi massif; (<b>e</b>) early post-rift stage, uplift of the Zhangguangcai Range; (<b>f</b>) late post-rift stage, uplift of the eastern Coastal Ranges.</p> Full article ">
14 pages, 1716 KiB  
Article
Distribution of Trace Elements (Ag, Pd, Cd, and Mn) between Pyrite and Pyrrhotite and Selectivity of Surficial Nonautonomous Phases in a Hydrothermal System
by Sergey Lipko, Vladimir Tauson, Nikolay Smagunov, Dmitriy Babkin and Irina Parkhomenko
Minerals 2022, 12(9), 1165; https://doi.org/10.3390/min12091165 - 15 Sep 2022
Cited by 4 | Viewed by 1434
Abstract
The dual distribution coefficients (D) that are related to structurally and superficially bound trace element (TE) in pyrite (Py) and pyrrhotite (Po) associations, crystallized hydrothermally at 400 °C and 1 kbar pressure, were determined. Three independent methods were used to estimate [...] Read more.
The dual distribution coefficients (D) that are related to structurally and superficially bound trace element (TE) in pyrite (Py) and pyrrhotite (Po) associations, crystallized hydrothermally at 400 °C and 1 kbar pressure, were determined. Three independent methods were used to estimate the structural and surficial TE contents (Cstr and Csur) and the corresponding D Py/Po values (Dstr and Dsur), which were found, on average, to be 12.4, 0.8, 0.9, and 0.06 (Dstr) and 2.6, 0.7, 2.0, and 0.07 (Dsur) for Ag, Pd, Cd, and Mn, respectively. The coincidence of a dual D for several elements was a result of coupled changes in Csur and Cstr. The selectivity (S) of the surficial nonautonomous phases (NAPs) that were responsible for TE accumulation (which is the ratio of TE concentrations in surficial and structural modes) was determined. It was shown that the interpretation of TE uptake by surficial phases was adequate and that this phenomenon is common in nature, independently of the system where it occurs—i.e., in experimental autoclaves or in hydrothermal ore deposits. Studies of NAPs selectivity can help in evaluating the total element compatibility in minerals and the maximum possible contents of structurally bound admixtures of the element (solubility) in minerals under given conditions. A significant surficial impurity accumulation effect is most important and well-pronounced for incompatible micro-elements with concentrations of less than ~0.1 wt%. The surficial mode may be a source of Pd and other platinum group elements and more abundant and easily refined than the structurally bound mode. Full article
(This article belongs to the Special Issue Mineralogical and Geochemical Characterization of Arsenopyrite and Pyrite)
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<p>Crystals of associated pyrite and pyrrhotite displaying a prevailing crystal habit (synthesis conditions—400 °C, 1 kbar, 10 % NH<sub>4</sub>Cl solution).</p> Full article ">Figure 2
<p>Dependence of the average concentrations of evenly distributed TEs in pyrite (Py) and pyrrhotite (Po) on the specific surface area of an average crystal of crystal-size fractions. The expressions for the approximate curves and concentrations of structurally and superficially bound modes are shown (see <a href="#minerals-12-01165-t001" class="html-table">Table 1</a> for details).</p> Full article ">Figure 3
<p>Dependence of the average concentrations of evenly distributed Cd and Mn in pyrite on the specific surface area of an average crystal of crystal-size fractions. See <a href="#minerals-12-01165-f002" class="html-fig">Figure 2</a> for explanations.</p> Full article ">Figure 4
<p>Absorbance–temperature curves of Cd release from pyrite (Py) and pyrrhotite (Po) samples. The NAP-related surficial mode with a maximum release temperature T<sub>m</sub> of ~600 °C dominates over the structural mode with T<sub>m</sub> ~800 °C.</p> Full article ">Figure 5
<p>Palladium distribution coefficient between pyrite and pyrrhotite as a function of temperature.</p> Full article ">
13 pages, 3938 KiB  
Article
Experimental Study and Numerical Simulation on Dust Concentration Distribution of Chute at Enclosed Stockyard of Steel Works
by Hongtao Wang, Xuesong Wang, Shengfa Xia and Lei Li
Minerals 2022, 12(9), 1164; https://doi.org/10.3390/min12091164 - 15 Sep 2022
Cited by 1 | Viewed by 1260
Abstract
To clarify the dust concentration distribution of chute at the enclosed stockyard in steel works during the discharging process of materials, the experimental model based on the similarity principle was established in the laboratory, and the effects of the moisture content of materials, [...] Read more.
To clarify the dust concentration distribution of chute at the enclosed stockyard in steel works during the discharging process of materials, the experimental model based on the similarity principle was established in the laboratory, and the effects of the moisture content of materials, the height of chute, as well as the discharging amount of materials on the dust concentration of the selected four materials (MLG-S, ONM-N-F, MLC-N, and ONM-N) were experimentally investigated. Simultaneously, the dust concentration distribution and the motion trajectory of particles were numerically simulated by FLUENT software based on the gas-solid two-phase flow theory. The results showed that a large amount of dust are generated during the discharging process of materials at the enclosed stockyard, and the dust concentration is negatively depended on the moisture content of materials, while that is positively correlated with the height of chute. As the height of chute is increased from 2.2 m to 3.1 m, the concentration of dust generated by the MLG-S is accelerated from 7335.1 mg/m3 to 8881.1 mg/m3, and the concentration of dust produced by the ONM-N is increased from 1286.7 mg/m3 to 1964.3 mg/m3. Meanwhile, the higher dust concentration is from the materials with smaller particle sizes and more fine particles. Furthermore, the dust concentration in the chute space is gradually increased from the top to the bottom, and the bottom of the chute is the key area for controlling dust pollution. Full article
(This article belongs to the Topic Iron Concentrate Particles)
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<p>Optical microstructure of the four materials used in the tests: (<b>a</b>) MLG-S; (<b>b</b>) ONM-N-F; (<b>c</b>) MLC-N; (<b>d</b>) ONM-N.</p> Full article ">Figure 2
<p>Schematic diagram of the experimental device established in laboratory.</p> Full article ">Figure 3
<p>Three dimensional model and section of simulated chute: (<b>a</b>) three dimensional model; (<b>b</b>) section.</p> Full article ">Figure 4
<p>Effects of the moisture content of materials on the average dust concentration of chute at the three measuring points.</p> Full article ">Figure 5
<p>Effects of the height of chute on the average dust concentration of chute at the three measuring points.</p> Full article ">Figure 6
<p>Concentration distribution of dust in the chute under different chute heights and different moistures: (<b>a</b>) MLG-S; (<b>b</b>) MLC-N; (<b>c</b>) ONM-N-F; (<b>d</b>) ONM-N.</p> Full article ">Figure 7
<p>Effects of the discharging amount of materials on the average dust concentration of chute at the three measuring points.</p> Full article ">Figure 8
<p>Concentration distribution of dust at different measuring points inside the chute.</p> Full article ">Figure 9
<p>Concentration distribution of dust along the height of chute.</p> Full article ">Figure 10
<p>Cloud image of the dust concentration distribution in the chute system running from the start to the end: (<b>a</b>) MLG-S 0.5 s; (<b>b</b>) MLG-S, 0.6 s; (<b>c</b>) MLG-S, 0.7 s; (<b>d</b>) MLG-S, 0.8 s; (<b>e</b>) MLC-N, 0.5 s; (<b>f</b>) MLC-N, 0.6 s; (<b>g</b>) MLC-N, 0.7 s; (<b>h</b>) MLC-N, 0.8 s.</p> Full article ">Figure 11
<p>Cloud image of motion trajectories of particles in the chute system running from the start to the end: (<b>a</b>) MLG-S 0.5 s; (<b>b</b>) MLG-S, 0.6 s; (<b>c</b>) MLG-S, 0.7 s; (<b>d</b>) MLG-S, 0.8 s; (<b>e</b>) MLC-N, 0.5 s; (<b>f</b>) MLC-N, 0.6 s; (<b>g</b>) MLC-N, 0.7 s; (<b>h</b>) MLC-N, 0.8 s.</p> Full article ">
26 pages, 7407 KiB  
Article
Late Cretaceous Activity Record of the Guangsan Fault—Insights from Zircon U-Pb and Apatite Fission-Track Thermochronology
by Ruxin Ding, Weihao Chen, Cleber Soares, Weisheng Hou, Zilong Li, Yangshijia Li, Rongli Huang and Heping Zou
Minerals 2022, 12(9), 1163; https://doi.org/10.3390/min12091163 - 14 Sep 2022
Cited by 2 | Viewed by 1466
Abstract
The timing of fault activity is a concern for geologists. This study used zircon U-Pb and apatite fission-track dating of fault breccia to determine the upper and lower limits for the time of faulting. The Guangsan fault in South China was taken as [...] Read more.
The timing of fault activity is a concern for geologists. This study used zircon U-Pb and apatite fission-track dating of fault breccia to determine the upper and lower limits for the time of faulting. The Guangsan fault in South China was taken as an example, and zircon U-Pb and apatite fission-track thermochronology were applied to the surrounding rock and fault breccia. The surrounding rock and fault breccia demonstrated 74.9–91.8 Ma and 73.9–93.5 Ma zircon U-Pb dates, respectively, indicating that the breccia formed after 73.9 Ma. They also demonstrated 71.6 ± 7.3 Ma and 85.9 ± 8.2–65.5 ± 6.5 Ma fission-track dates, implying that the fault breccia samples likely formed before ~70 Ma. Their thermal histories were highly consistent: both showed rapid cooling during 70–65 Ma and slow cooling during 65–0 Ma, implying that the fault was likely still active during 70–65 Ma, resulting in the rapid exhumation. Full article
(This article belongs to the Special Issue Fission Track Analysis and Its Application in Mineralogy)
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<p>Geological map of the study area. (<b>a</b>) Location map of Gaoyao–Huilai fault in Guangdong province, China (modified from [<a href="#B24-minerals-12-01163" class="html-bibr">24</a>,<a href="#B25-minerals-12-01163" class="html-bibr">25</a>]). <a href="#minerals-12-01163-f001" class="html-fig">Figure 1</a>b indicated to geological map of the study area. GF: Guangsan fault; SF: Shougouling fault. (<b>b</b>) Geological map of the study area (modified from [<a href="#B26-minerals-12-01163" class="html-bibr">26</a>]).</p> Full article ">Figure 2
<p>Zircon dating U-Pb concordia diagrams for this study. (<b>a</b>) sample #2, (<b>b</b>) sample TTL-23 and (<b>c</b>) sample #4 are country rock. (<b>d</b>) sample #1, (<b>e</b>) sample #3, (<b>f</b>) sample MKZ2-A90 are fault rock and (<b>g</b>) sample #7.</p> Full article ">Figure 2 Cont.
<p>Zircon dating U-Pb concordia diagrams for this study. (<b>a</b>) sample #2, (<b>b</b>) sample TTL-23 and (<b>c</b>) sample #4 are country rock. (<b>d</b>) sample #1, (<b>e</b>) sample #3, (<b>f</b>) sample MKZ2-A90 are fault rock and (<b>g</b>) sample #7.</p> Full article ">Figure 3
<p>Radial plots of the single-grain AFT ages made using RadialPlotter [<a href="#B35-minerals-12-01163" class="html-bibr">35</a>]. (<b>a</b>) sample TTL-23 is country rock. (<b>b</b>) sample #1, (<b>c</b>) sample #3 and (<b>d</b>) sample MKZ2-90 are fault rock.</p> Full article ">Figure 4
<p>Confined track length distributions.</p> Full article ">Figure 5
<p>Thermal history models of samples TTL-23 and #3. The Low-T Thermo computer code [<a href="#B34-minerals-12-01163" class="html-bibr">34</a>] was used for the modelling. The 1,000,000 t-T paths were randomly generated using the Monte Carlo method. The blue indicates the substantial range used to search for reheating. The mean of all good t-T paths (i.e., goodness-of-fit (GOF) ≥ 0.5) was calculated and assumed to be the most likely t-T path of the sample. The blue boxes were defined to constrain the reheated model during the modeling moderation. The black solid lines represent the mean thermal histories (MTHs) used as the final thermal history modelling result. The magenta areas define the envelopes of good fit (GOF ≥ 0.5). The green areas define the envelopes of acceptable fit (GOF ≥ 0.05).</p> Full article ">Figure A1
<p>Photos of sample locations in the deep subway excavation at Jiangtai Road subway station. (<b>A1</b>) Cretaceous sediments on the left and volcanic rocks on the right; (<b>A2</b>) fault plane (the plane dips to the south with a dip angle of 52°).</p> Full article ">Figure A2
<p>Photos of samples in this study. (<b>a</b>) sample #2; (<b>b</b>) sample #1; (<b>c</b>) sample #4; (<b>d</b>) sample #3; (<b>e</b>) sample TTL-23; (<b>f</b>) sample MKZ2-A90; (<b>g</b>) sample #7.</p> Full article ">Figure A2 Cont.
<p>Photos of samples in this study. (<b>a</b>) sample #2; (<b>b</b>) sample #1; (<b>c</b>) sample #4; (<b>d</b>) sample #3; (<b>e</b>) sample TTL-23; (<b>f</b>) sample MKZ2-A90; (<b>g</b>) sample #7.</p> Full article ">Figure A3
<p>Zircon CL images. The red circle in all figures indicate the spot position of Zircon U-Pb dating.</p> Full article ">Figure A3 Cont.
<p>Zircon CL images. The red circle in all figures indicate the spot position of Zircon U-Pb dating.</p> Full article ">
10 pages, 1777 KiB  
Article
Using Waste Brine from Desalination Plant as a Source of Industrial Water in Copper Mining Industry
by Constanza Cruz, Sebastián Herrera-León, Daniel Calisaya-Azpilcueta, Ruth Salazar, Luis A. Cisternas and Andrzej Kraslawski
Minerals 2022, 12(9), 1162; https://doi.org/10.3390/min12091162 - 14 Sep 2022
Cited by 5 | Viewed by 2694
Abstract
One of the main challenges of seawater desalination is a large volume of waste brine production that is commonly discharged into the sea and may threaten the marine ecosystem. This is critical in regions where conventional water resources are scarce and desalinated seawater [...] Read more.
One of the main challenges of seawater desalination is a large volume of waste brine production that is commonly discharged into the sea and may threaten the marine ecosystem. This is critical in regions where conventional water resources are scarce and desalinated seawater is an alternative to meet water demand. Especially in regions where the mining industry is a key player in the economic development. The novelty of this research consists in the determination of the potential use of waste brine, discharged from the reverse osmosis process, as a source of industrial water in copper mining industry. To enable the waste brine applicability, there should be reduced calcium and magnesium ions concentration for improving copper recovery in the froth flotation process. The flotation tests were conducted in a batch cell with synthetic minerals composed of chalcopyrite, kaolinite, and quartz using different water qualities. The results showed that treated waste brine significantly improved copper recovery compared to untreated waste brine and seawater. Similar copper recovery was achieved when flotation test was performed with tap water and treated waste brine. Therefore, treated waste brine could provide a suitable water quality required in the froth flotation process as an alternative non-conventional water resource. Full article
(This article belongs to the Special Issue Seawater Flotation)
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<p>Experimental unit used in the waste brine treatment.</p> Full article ">Figure 2
<p>Experimental unit used in the froth flotation tests.</p> Full article ">Figure 3
<p>Removal rate of magnesium ions from waste brine at a pH above 11.</p> Full article ">Figure 4
<p>Removal rate of calcium ions from waste brine at a pH above 11.</p> Full article ">Figure 5
<p>Schematic illustration of the interaction mechanism between kaolinite and chalcopyrite using seawater or waste brine at pH 11. Adapted from [<a href="#B32-minerals-12-01162" class="html-bibr">32</a>].</p> Full article ">
18 pages, 3881 KiB  
Article
Mineralogical and Geochemical Implications of Weathering Processes Responsible for Soil Generation in Mănăila Alpine Area (Tulgheş 3 Unit—Eastern Carpathians)
by Doina Smaranda Sirbu-Radasanu, Ramona Huzum, Delia-Georgeta Dumitraş and Cristina Oana Stan
Minerals 2022, 12(9), 1161; https://doi.org/10.3390/min12091161 - 14 Sep 2022
Cited by 2 | Viewed by 2148
Abstract
In the Mănăila alpine area, the soil layer developed in situ on top of the sericite-schists, which belong to the Tulghes 3 metamorphic unit. The aim of the present work was to determine the degree of soil formation using both mineralogical and geochemical [...] Read more.
In the Mănăila alpine area, the soil layer developed in situ on top of the sericite-schists, which belong to the Tulghes 3 metamorphic unit. The aim of the present work was to determine the degree of soil formation using both mineralogical and geochemical exploration methods. XRD, FTIR and SEM-EDS results showed that the soil constituents were dioctahedral 2:1 minerals, quartz, chlorite, Na-feldspar, rutire and ilmenite. Mainly illite and secondarily mixed-layer minerals were considered to be the most likely minerals resulting from the transformation of sericite and chlorite under acidic alpine conditions. Geochemical modeling inferred the dominance of illite and the presence of smectite as a chlorite alteration product. The weathering indices supported the moderate stage of the soil development agreeing with mineralogical observations. Because of the abundance of sericite and quartz in the parent material, the soil formation was retarded, and its present composition is still related to the bedrocks. Full article
(This article belongs to the Special Issue Soil Mineralogy on Ecosystem Functioning)
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<p>The Mănăila open-pit exploitation (<b>a</b>) geological map of the area, modified after [<a href="#B21-minerals-12-01161" class="html-bibr">21</a>] and (<b>b</b>) soil samples location using Google Map as base maps [<a href="#B22-minerals-12-01161" class="html-bibr">22</a>].</p> Full article ">Figure 2
<p>An X-ray powder pattern for a representative sample of soil from Mănăila.</p> Full article ">Figure 3
<p>FTIR spectra for the representative sample of soil from Mănăila.</p> Full article ">Figure 4
<p>(<b>a</b>) K/Al:Si/Al molar ratio correlations (<b>b</b>) K/Mg:Al/Mg molar ratio correlation.</p> Full article ">Figure 5
<p>The A-CN-K ternary system [<a href="#B15-minerals-12-01161" class="html-bibr">15</a>] (Ms-mucovie, Plg-plagioclase, KFs-potassium feldspar; dashed line–rhyolite weathering trend).</p> Full article ">Figure 6
<p>The A-CNK-FM diagram for parent material and soil.</p> Full article ">Figure 7
<p>A M<sup>+</sup>-4Si-R<sup>2+</sup>diagram for rock and soil from the Mănăila area.</p> Full article ">Figure 8
<p>The M<sup>+</sup>-4Si-R<sup>2+</sup> system for the illite and smectite composition (Bei—beidellite; Cel—celadonite; Ilt—illite; Kln—kaolinite; Sme—smectite).</p> Full article ">
15 pages, 2559 KiB  
Article
Stable Isotopic, Micro-FTIR, and Geochemical Characteristics of the Permian Madzaringwe Shale of Tuli Basin, South Africa: Implications for Organic-Rich Shale Provenance
by George Oluwole Akintola, Francis Amponsah-Dacosta, Steven Rupprecht and Sphiwe Emmanuel Mhlongo
Minerals 2022, 12(9), 1160; https://doi.org/10.3390/min12091160 - 14 Sep 2022
Viewed by 1892
Abstract
The paleo-environmental setting of an organic-rich shale remains an essential controlling factor for shale reservoir distribution. The scarcity of generalised data on paleo-environment settings has been spurred using a simple investigative approach to decipher the provenance of organic-rich shale in various regions. This [...] Read more.
The paleo-environmental setting of an organic-rich shale remains an essential controlling factor for shale reservoir distribution. The scarcity of generalised data on paleo-environment settings has been spurred using a simple investigative approach to decipher the provenance of organic-rich shale in various regions. This study investigates the organic-rich Madzaringwe shale of the Tuli Basin to reconstruct the provenance of the organic material for shale gas generation potential. Representative shale core samples were analysed for the stable isotopic fractions, functional groups, and major and trace compositions. The carbon isotopic composition, δ13C value, ranging from −21.01 to −24.0‰, averaging at −22.4‰. Inference from the stable isotopic compositions and functional group analysis indicate Type-III kerogen prone to gas generation in the studied Madzaringwe shale. The micro-Fourier transformed infrared (micro-FTIR) analysis reveals infrared absorption peaks between 2800 and 3300 cm−1 wavelengths corresponding to gaseous hydrocarbon. The x-ray fluorescence (XRF) result reveals major elements comprising Al2O3 (29.25–29.11%), CaO (0.29–0.28%), Fe2O3 (1.16–1.09%), K2O (0.97–0.98%), MgO (0.13–0.12%), Na2O (0.12–0.09%), P2O5 (0.22–0.21%), SiO2 (52.50–52.30%), and TiO2 (1.20–1.18%). The major element ratio of Al2O3/TiO2 values ≥ 25 indicates felsic and intermediate provenance from a terrigenous paleo-environment. In addition, laser ablation inductively coupled plasma mass spectrometry (LAICP-MS) reveals the trace elements in which elemental proxy of V/(V + Ni) with a value greater than 0.5 represent reducing environments. Furthermore, the geochemical proxies and isotopic compositions have revealed an anoxic paleo-environment for the non-marine-derived organic matter in the studied carbonaceous shale. Full article
(This article belongs to the Special Issue Reservoir and Geochemistry Characteristics of Black Shale)
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<p>Study area 9 (<b>a</b>) Tuli Basin (<b>b</b>) organic-rich formation (<b>c</b>) organic-rich shale core sample.</p> Full article ">Figure 2
<p>Organic-rich shale core samples from the study area.</p> Full article ">Figure 3
<p>Geochemical proxies (<b>a</b>) V(V + Ni) vs U/Th (<b>b</b>) v/(v + Ni) vs Ni/Co after [<a href="#B27-minerals-12-01160" class="html-bibr">27</a>].</p> Full article ">Figure 4
<p>Micro-FTIR spectra are showing functional groups corresponding to organic molecules in studied shale.</p> Full article ">Figure 5
<p>Cross-plot of δ<sup>18</sup>O vs δ<sup>13</sup>C values for the studied organic-rich shale modified after [<a href="#B35-minerals-12-01160" class="html-bibr">35</a>].</p> Full article ">Figure 6
<p>Carbon isotopic compositions of studied Madzaringwe samples show kerogen-type domains [<a href="#B37-minerals-12-01160" class="html-bibr">37</a>].</p> Full article ">Figure 7
<p>Plot of Discrimination functions using major elements index for felsic and mafic provenance and quartzose sedimentary provenance (Note: Discrimination Function 1: −1.733 TiO<sub>2</sub> + 0.607 Al<sub>2</sub>O<sub>3</sub> + 0.76 Fe<sub>2</sub>O<sub>3</sub> (t) −1.5 MgO + 0.616 CaO + 0.509 Na<sub>2</sub>O − 1.224 K<sub>2</sub>O − 0.909. Discrimination Function 2: 0.445 TiO<sub>2</sub> + 0.07 Al<sub>2</sub>O<sub>3</sub> − 0.25 Fe<sub>2</sub>O<sub>3</sub> (t) − 1.142 MgO + 0.438 CaO + 1.475 Na<sub>2</sub>O + 1.426 K<sub>2</sub>O − 6.861) [<a href="#B38-minerals-12-01160" class="html-bibr">38</a>].</p> Full article ">Figure 8
<p>Zn-Ni-Co hydrothermal diagram of the represented studied shale samples [<a href="#B27-minerals-12-01160" class="html-bibr">27</a>].</p> Full article ">Figure 9
<p>Paleo-geographic reconstruction of the Southern Gondwana Permian Basins [<a href="#B78-minerals-12-01160" class="html-bibr">78</a>].</p> Full article ">
15 pages, 3387 KiB  
Article
On a Unified Core Characterization Methodology to Support the Systematic Assessment of Rare Earth Elements and Critical Minerals Bearing Unconventional Carbon Ores and Sedimentary Strata
by Scott N. Montross, Davin Bagdonas, Thomas Paronish, Andrew Bean, Andrew Gordon, C. Gabriel Creason, Burt Thomas, Erin Phillips, James Britton, Scott Quillian and Kelly Rose
Minerals 2022, 12(9), 1159; https://doi.org/10.3390/min12091159 - 14 Sep 2022
Cited by 3 | Viewed by 2599
Abstract
A significant gap exists in our understanding and ability to predict the spatial occurrence and extent of rare earth elements (REE) and certain critical minerals (CM) in sedimentary strata. This is largely due to a lack of existing, systematic, and well-distributed REE and [...] Read more.
A significant gap exists in our understanding and ability to predict the spatial occurrence and extent of rare earth elements (REE) and certain critical minerals (CM) in sedimentary strata. This is largely due to a lack of existing, systematic, and well-distributed REE and CM samples and analyses in United States sedimentary basins. In addition, the type of sampling and characterization performed to date has generally lacked the resolution and approach required to constrain geologic and geographic heterogeneities typical of subsurface, mineral resources. Here, we describe a robust and systematic method for collecting core scale characterization data that can be applied to studies on the contextual and spatial attributes, the geologic history, and lithostratigraphy of sedimentary basins. The methods were developed using drilled cores from coal bearing sedimentary strata in the Powder River Basin, Wyoming (PRB). The goal of this effort is to create a unified core characterization methodology to guide systematic collection of key data to achieve a foundation of spatially and geologically constrained REEs and CMs. This guidance covers a range of measurement types and methods that are each useful either individually or in combination to support characterization and delineation of REE and CM occurrences. The methods herein, whether used in part or in full, establish a framework to guide consistent acquisition of geological, geochemical, and geospatial datasets that are key to assessing and validating REE and CM occurrences from geologic sources to support future exploration, assessment, and techno-economic related models and analyses. Full article
(This article belongs to the Special Issue Characterization of Rare Earth Elements and Critical Minerals in Geologic and Engineered Materials)
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<p>Core characterization workflow steps and methods for collection and analysis of data from sedimentary rock cores. 1. Core collection at Brook Mine, Sheridan Wyoming. 2. MSIL core logging and pXRF analysis of cores in the NETL laboratory. 3. SEM imaging and EDS mapping of elements. 4. Compiled core log detailing the Mining-plus suite elemental results; (from left to right) CT images, dual energy density, mean density (black), standard error (red) (gm/cc), light elements (up to silicon) (LE) (%), silicon (Si) (%), aluminum (Al) (%), iron (Fe) (%), calcium (Ca) (%), sulfur (S) (%), remaining elements (%).</p> Full article ">Figure 2
<p>Example of sample spacing in coal core with sediment variances and expected REE and CM anomalies around those variances. Comparison is given to tradition channel sampling of the same stratigraphic sequence. Modified from CEGR sample plans provided by Coalgeo. LLC.</p> Full article ">Figure 3
<p>Cross plots (<b>left</b>) total REE in ppm on ash basis and (<b>right</b>) HREE/LREE ratios versus ash content.</p> Full article ">Figure 4
<p>Plots of REE anomalies Ce (<b>left</b>) and Eu (<b>right</b>) from core samples. Ce<span class="html-italic"><sub>N</sub></span> is the ratio of the concentration of Ce in the sample to Ce in the upper continental crust (UCC). Ce<span class="html-italic"><sub>N</sub></span>* and Eu<span class="html-italic"><sub>N</sub></span>* are calculated using the equation(s) from Dai and others, 2016 [<a href="#B5-minerals-12-01159" class="html-bibr">5</a>] where Ce<span class="html-italic"><sub>N</sub></span>* = 0.5La<span class="html-italic"><sub>N</sub></span> + 0.5Pr<span class="html-italic"><sub>N</sub></span> and Eu<span class="html-italic"><sub>N</sub></span>* = 0.5Sm<span class="html-italic"><sub>N</sub></span> + 0.5Gd<span class="html-italic"><sub>N</sub>.</span></p> Full article ">Figure 5
<p>Plots of Ce<span class="html-italic"><sub>N</sub>*</span> versus HREE/LREE ratio (<b>left</b>) and total REE in ppm (<b>right</b>).</p> Full article ">
26 pages, 8709 KiB  
Article
Occurrence Characteristics of Magnetite and Aeromagnetic Prospecting Northeast of Hebei Province
by Yan-Xu Liu, Wen-Yong Li, Zhi-Yuan Liu, Jia-Wei Zhao, An-Qi Cao, Shan Gao, Li-Jie Wang and Cheng Yang
Minerals 2022, 12(9), 1158; https://doi.org/10.3390/min12091158 - 14 Sep 2022
Cited by 2 | Viewed by 1969
Abstract
The occurrence characteristics of magnetite and the methods to quickly and effectively explore are important topics for ore prospecting in the new era. Taking northeast of Hebei Province of China as an example, this article aimed at an important strategic mineral of magnetite, [...] Read more.
The occurrence characteristics of magnetite and the methods to quickly and effectively explore are important topics for ore prospecting in the new era. Taking northeast of Hebei Province of China as an example, this article aimed at an important strategic mineral of magnetite, then discussed its distribution characteristics and aeromagnetic exploration methods of it. First of all, we discuss the occurrence characteristics of sedimentary metamorphic and magmatic magnetite. Then, using the latest high-precision aeromagnetic data, combined with the geological outcrops, known iron deposits, ground magnetic surveys, and verification, we studied the relationship between the aeromagnetic anomalies and iron deposits through potential field conversion processing of the reduction to the pole, vertical derivative, upward continuation and residual anomaly, and the forward modeling and inversion methods of 2.5 D optimization fitting. Next, we summarize the metallogenic conditions and attributes of aeromagnetic prospecting and make magnetite predictions. In addition, it has suitable magnetite prospecting potential in the Laochenjia, Dabai, Jiuwuying, Beierying, Sidaogoumen, and Wuyingzi aeromagnetic anomaly regions. In conclusion, these regions have aeromagnetic anomalies with high amplitudes, large scales, and favorable metallogenic backgrounds for magmatic rocks, strata, and structures caused by concealed magnetite. In addition, they have great prospecting potential. Eventually, we hope this research method in this article can provide a reference for magnetite exploration in other areas with similar geological conditions. Full article
(This article belongs to the Special Issue Applications of Gravity and Magnetics to Mineral Exploration)
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<p>Geological map of the study region.</p> Full article ">Figure 2
<p>Aeromagnetic ∆T of the study region.</p> Full article ">Figure 3
<p>Reduction to the pole of aeromagnetic ∆T and depth by Euler deconvolution of the study region.</p> Full article ">Figure 4
<p>Aeromagnetic anomaly and its conversion of a sedimentary metamorphic magnetite in the study area: (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T.</p> Full article ">Figure 5
<p>Aeromagnetic anomaly and its conversion of some magmatic rock magnetite in the study area: (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T.</p> Full article ">Figure 6
<p>Reduction to the pole of aeromagnetic data ∆T and magnetite prediction region in northeast Hebei: I-1: Ore prediction region of iron polymetallic in Laochenjia, I-2: Iron ore prediction region of Dabai-Henan, I-3: Iron ore prediction region of Jiuwuying-baiyingzi, I-4: Ore prediction region of iron polymetallic in Beierying, I-5: Ore prediction region of iron polymetallic in Sidaogoumen, I-6: Ore prediction region of iron polymetallic in Wuyingizi.</p> Full article ">Figure 7
<p>Aeromagnetic anomaly JDB-4 and its corresponding magnetite deposit: (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T, (<b>d</b>) reduction to the pole of aeromagnetic anomaly (upwards extending 3 km), (<b>e</b>) depth by Euler deconvolution, (<b>f</b>) photograph of iron deposit mined. A–B are the locations of the section shown in <a href="#minerals-12-01158-f008" class="html-fig">Figure 8</a>.</p> Full article ">Figure 8
<p>Magnetic data ∆T profile of the ground survey (line NO. 223). The location of the line is shown in <a href="#minerals-12-01158-f007" class="html-fig">Figure 7</a>a.</p> Full article ">Figure 9
<p>Aeromagnetic anomaly JDB-7 and its corresponding magnetite deposit: (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T, (<b>d</b>) photograph of iron deposit mined.</p> Full article ">Figure 10
<p>Aeromagnetic anomaly JDB-8 and its conversion: (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T, (<b>d</b>) depth by Euler deconvolution.</p> Full article ">Figure 11
<p>Integrated geophysical profiles of ground surveying of anomaly JDB-8: (<b>a</b>) anomalies of Ag and Pb from soil measurements, (<b>b</b>) curve of IP central gradient method of ground surveying line 2, (<b>c</b>) forward fitting profile to magnetic data ΔT of ground surveying line 2, (<b>d</b>) profile of ηs relative intensity by fixed–source sounding for ground surveying line 2, (<b>e</b>) CSAMT inversion resistivity profile.</p> Full article ">Figure 12
<p>Aeromagnetic anomaly JDB-10 and its corresponding magnetite deposit. (<b>a</b>) Aeromagnetic data ∆T, (<b>b</b>) reduction to the pole of aeromagnetic data ∆T, (<b>c</b>) the first vertical derivative of reduction to the pole of aeromagnetic data ∆T, (<b>d</b>) depth by Euler deconvolution, (<b>e</b>) photograph of iron deposit mined. E-F are the locations of the section shown in <a href="#minerals-12-01158-f013" class="html-fig">Figure 13</a>.</p> Full article ">Figure 13
<p>Magnetic data ΔT profile of the ground survey (line NO. 227).</p> Full article ">
21 pages, 4859 KiB  
Article
Genesis of Cambrian Dolomites in the Bachu Area, Tarim Basin, NW China: Constraints from Petrology, Geochemistry, and Fluid Inclusions
by Zhipeng Chen, Yanfei Yang, Caiyuan Dong, Ningxi Li, Pengtao Wang, Shaohua Zhang, Wei Dang and Yun Liao
Minerals 2022, 12(9), 1157; https://doi.org/10.3390/min12091157 - 14 Sep 2022
Cited by 1 | Viewed by 1587
Abstract
The dolomitization of carbonate rocks has always been a hot topic in the study of the dolomite reservoir. In this study, the genesis of Cambrian dolomite in the Bachu area, Tarim Basin, was assessed through petrographic examinations, isotope compositions (C, O, and Sr), [...] Read more.
The dolomitization of carbonate rocks has always been a hot topic in the study of the dolomite reservoir. In this study, the genesis of Cambrian dolomite in the Bachu area, Tarim Basin, was assessed through petrographic examinations, isotope compositions (C, O, and Sr), trace and rare earth elements, and fluid inclusion microthermometry. Microscopic analysis revealed three types of dolomites: very fine-crystalline, nonplanar dolomite (D1); fine-crystalline, nonplanar to planar-s dolomite (D2); and medium- to coarse-crystalline, planar-e to planar-s dolomite (D3). D1 dolomite exhibits well-preserved original sedimentary features, such as algal laminae, stromatolite, and evaporite streak, and is characterized by the 87Sr/86Sr value and δ18O value in equilibrium with the coeval seawater, its high Sr and Na content, and its low Mn content. This indicates that D1 dolomite is primarily a penecontemporaneous dolomite in tidal flat or lagoon environments, and its dolomitizing fluid is mainly evaporated mesosaline to penesaline seawater. D2 dolomite shows ghosts of precursor particles; features δ13C values in equilibrium with the coeval seawater, high 87Sr/86Sr values, low Sr content, and positive Eu anomaly; and is widely distributed close to stylolite. This illustrates that D2 dolomite was principally formed by seepage–reflux dolomitization, and is closely related to hydrothermal activity and pressure dissolution. D3 dolomite displays a crystal texture with a cloudy core and compositional zoning, and the original sedimentary fabrics cannot be identified. It has similar δ13C values and REE patterns to the calcite precipitated from coeval seawater, high 87Sr/86Sr values, low Sr contents and high Mn/Sr ratios, which suggests that D3 dolomite is chiefly related to the recrystallization of the precursor dolomite during the deep burial stage, and the deep circular brine provides Mg ions through the fluid–rock reaction. This study shows that the Cambrian dolomite in the Bachu area is mainly formed in the coeval seawater environment during the penecontemporaneous and shallow burial stages, and has extensively suffered from recrystallization and burial diagenesis due to long-term deep burial, which was further strengthened in the fracture-enriched area. Full article
(This article belongs to the Special Issue Carbonate Biomineralization, Environmental, and Diagenetic Significance)
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<p>(<b>A</b>) Sketch map showing the geotectonic components of the Tarim Basin (modified from Du et al. (2017) [<a href="#B28-minerals-12-01157" class="html-bibr">28</a>]); (<b>B</b>) generalized diagram showing the stratigraphy and lithofacies of the Cambrian successions in the Bachu area (modified from Hu et al. (2019) [<a href="#B22-minerals-12-01157" class="html-bibr">22</a>]).</p> Full article ">Figure 2
<p>Burial history of the Cambrian succession in the Bachu area based on well HT1 (modified from Qiu et al. (2012) [<a href="#B32-minerals-12-01157" class="html-bibr">32</a>]).</p> Full article ">Figure 3
<p>D1 dolomite: (<b>A</b>) very fine-crystalline dolomite with horizontal bedding, well BT5, 4742.29 m, Є<sub>3</sub>x, under plane-polarized light (PPL). (<b>B</b>) Micritic dolomite laminae interbedded with salt and anhydrite laminae (arrows), well HT5, 6162 m, Є<sub>2</sub>a, under PPL. (<b>C</b>) Cryptocrystalline pyrites (arrows) disseminated within intercrystalline pores, well HT1, 6433 m, Є<sub>2</sub>a, under PPL. (<b>D</b>) Precursor limestone ooid (arrows) replaced by dolomicrite, well BT5, 4742 m, Є<sub>3</sub>x, under PPL. (<b>E</b>) Microcrystalline dolomite with a stromatolitic structure, well XH1, 5436 m, Є<sub>1</sub>w, under PPL. (<b>F</b>) Diatom chondrite (arrows) in microcrystalline dolomite, well XH1, 5442 m, Є<sub>1</sub>x, under scanning electron microscope-second electron (SEM-SE).</p> Full article ">Figure 4
<p>D2 dolomite: (<b>A</b>) Core photograph of fine-crystalline arenite dolomite, well HT1, 6437.30 m, Є<sub>2</sub>a. (<b>B</b>) Tightly packed dolomite crystals with curved surfaces show fuzzy allochem ghost (arrows), well BT5, 4802.66 m, Є3x, under PPL. (<b>C</b>) Ooid grains with cloudy cores and clear rims (arrows), well HT1, 6161.40 m, Є<sub>2</sub>a, under PPL. (<b>D</b>) Precursor deposit structure (granule ghost, arrows), well HT1, 6162.60 m, Є<sub>1</sub>x, under PPL. (<b>E</b>) Very fine-crystalline dolomite and fine-crystalline dolomite are distributed on different sides of the stylolite, well BT5, 5644.24 m, Є<sub>1</sub>w, under PPL. (<b>F</b>) Fine-crystalline dolomite crystals distributed around dissolution fractures, which are partially filled with calcite and pyrite (arrows), well BT5, 5787.63 m, Є<sub>1</sub>w, under PPL.</p> Full article ">Figure 5
<p>D3 dolomite: (<b>A</b>) rhombohedral-shaped crystals with cloudy cores and well-defined edges, well BT5, 4742.29 m, Є<sub>3</sub>x, under PPL. (<b>B</b>) Coarse dolomite crystals with compositional zoning, well T1, 3181 m, Є<sub>3</sub>x, under PPL. (<b>C</b>) Floating dolomite crystals, well BT5, 4810.65 m, Є<sub>3</sub>x, under PPL. (<b>D</b>) D3 dolomite with curved crystal planes and a tightly packed texture, well XH1, 5436.00 m, Є<sub>1</sub>x, under PPL. (<b>E</b>) Intercrystalline pores occluded by calcite, well T1, 3678.15 m, Є<sub>3</sub>x, under PPL. (<b>F</b>) Pores among the coarse dolomite crystal, well XH1, 5442 m, Є<sub>1</sub>x, under SEM-SE.</p> Full article ">Figure 6
<p>(<b>A</b>) Cross-plot of Mn versus Sr abundances in the Cambrian dolomites. (<b>B</b>) Cross-plot of Mn versus Fe abundance in the Cambrian dolomites.</p> Full article ">Figure 7
<p>PAAS-normalized REE patterns of D1 dolomite (<b>A</b>), D2 dolomite (<b>B</b>), D3 dolomite (<b>C</b>), and limestone of Lower Ordoviciao (<b>D</b>) in the Bachu area, Tarim Basin. The PAAS data were obtained from McLennan (1989) [<a href="#B37-minerals-12-01157" class="html-bibr">37</a>]). The REE compositions of limestone of Lower Ordovician in Tarim Basin were obtained from Du et al. (2017) [<a href="#B28-minerals-12-01157" class="html-bibr">28</a>].</p> Full article ">Figure 8
<p>Cross-plot of δ<sup>18</sup>O versus δ<sup>13</sup>C values for D1, D2, and D3 dolomites in the Cambrian successions, Bachu area, Tarim Basin. The δ<sup>18</sup>O and δ<sup>13</sup>C values of Cambrian calcite are derived from Ngia et al. (2019) [<a href="#B31-minerals-12-01157" class="html-bibr">31</a>]. The isotope ranges of Cambrian marine calcite (red bars) and the δ<sup>18</sup>O range of coeval evaporative dolomites (solid double arrow) are present for comparison [<a href="#B45-minerals-12-01157" class="html-bibr">45</a>,<a href="#B46-minerals-12-01157" class="html-bibr">46</a>,<a href="#B48-minerals-12-01157" class="html-bibr">48</a>]. The estimated coeval marine dolomite and calcite are calculated using the δ<sup>18</sup>O<sub>dolomite</sub> − δ<sup>18</sup>O <sub>calcite</sub> of +3‰VPDB (dashed double arrow) [<a href="#B18-minerals-12-01157" class="html-bibr">18</a>,<a href="#B47-minerals-12-01157" class="html-bibr">47</a>].</p> Full article ">Figure 9
<p>Cross-plot of <sup>87</sup>Sr/<sup>86</sup>Sr versus Sr abundance for D1, D2, and D3 dolomites in the Cambrian successions, Bachu area, Tarim Basin. The strontium isotope range of coeval seawater marked in gray refers to Veizer et al. (1999) [<a href="#B45-minerals-12-01157" class="html-bibr">45</a>,<a href="#B46-minerals-12-01157" class="html-bibr">46</a>].</p> Full article ">Figure 10
<p>(<b>A</b>) T<sub>h</sub> of fluid inclusions in D2 and D3 dolomites, and vein calcite. (<b>B</b>) Cross-plot of T<sub>h</sub> versus salinity. The salinity was calculated from T<sub>m</sub> of fluid inclusions in D2 and D3 dolomites, and vein calcite.</p> Full article ">Figure 11
<p>Cross-plot of δ<sup>18</sup>O values (VPDB) versus homogenization temperatures of D2 and D3 dolomites. Curved lines are isopleths for δ<sup>18</sup>O<sub>fluid</sub> calculated using the dolomite–fluid oxygen isotope fractionation equations [<a href="#B5-minerals-12-01157" class="html-bibr">5</a>].</p> Full article ">
13 pages, 3701 KiB  
Article
On the Cobalt Content Upgrade in Nickeliferous Laterites Using Iron (III) Sulfate: A Study Based on Thermodynamics Simulations
by Rodrigo F. M. Souza, Mariana A. A. Tavares, Luiz E. C. Cruz, Víctor A. A. Oliveira, Iranildes D. Santos, Francisco J. Moura and Eduardo A. Brocchi
Minerals 2022, 12(9), 1156; https://doi.org/10.3390/min12091156 - 13 Sep 2022
Cited by 2 | Viewed by 2003
Abstract
Nickel (Ni) and cobalt (Co) are relevant technological metals for the future of the lithium-ion battery (LIB) industry. Based on the current and projected demand for these, an increased interest in developing processing routes to exploit lateritic occurrences has been observed, as these [...] Read more.
Nickel (Ni) and cobalt (Co) are relevant technological metals for the future of the lithium-ion battery (LIB) industry. Based on the current and projected demand for these, an increased interest in developing processing routes to exploit lateritic occurrences has been observed, as these are reported as critical raw materials for future mineral–metallurgical industry. However, the content of Ni and Co in such ores is minimal and requires impracticable mineral-processing operations for concentration before metal extraction. It was identified that information regarding the sulfation roasting of this material is scarce on what concerns the iron sulfates interaction as a function of the temperature. Based on that context, the present work has its purposes associated with the proposition of an alternative chemical pretreatment to upgrade the content of metals of technological interest in lateritic ores through a simple roast–leach process. Thus, the chemical interactions between the mineral sample and iron (III) sulfate (Fe2(SO4)3) through thermodynamic simulations and experimental procedures were explored. The latter included specific water leaching practices for the selective concentration of metals. The equilibrium calculations indicate that Fe2(SO4)3 and FeSO4 tend to decompose at lower temperatures, and considering the higher stability of other metal sulfates, it could be an interesting reagent in this type of process. Regarding the experimental results, the characterization of materials indicates a recovery of Co as high as 73.4 wt.% after sulfation roasting at 500 °C followed by water leaching, with the full content of Iron (Fe) being reported in the insoluble phase. Based on these findings, the present development could be an interesting alternative to consider within operations for the chemical upgrade of cobalt in such types of mineralogical occurrences. Full article
(This article belongs to the Special Issue Thermodynamics, Mechanism and Kinetics of Metallurgical Processes)
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<p>XRD mineralogical analysis of the laterite sample: Observed and Calculated Spectra.</p> Full article ">Figure 2
<p>Calculated equilibrium compositions of SR using Fe<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub> with NiO, CoO, MgO, and CaO at stoichiometric proportions.</p> Full article ">Figure 3
<p>Equilibrium compositions as function of temperature and amount of SR reagent for sulfates formation: (<b>a</b>) NiSO<sub>4</sub>; (<b>b</b>) CoSO<sub>4</sub>; (<b>c</b>) MgSO<sub>4</sub>; (<b>d</b>) CaSO<sub>4</sub>.</p> Full article ">Figure 4
<p>SR and WL mass variation results: (<b>a</b>) at Stoichiometric Condition; (<b>b</b>) at 10 wt.% Excess Condition; (<b>c</b>) at 20 wt.% Excess Condition; (<b>d</b>) at 30 wt.% Excess Condition.</p> Full article ">Figure 5
<p>TGA and DTG behavior of the sample with 30 wt.% excess of Fe<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub> as SR reagent.</p> Full article ">Figure 6
<p>XRD mineralogical analysis of the roasted material: Observed and Calculated Spectra for the samples processed at (<b>a</b>) 500 °C and (<b>b</b>) 700 °C.</p> Full article ">Figure 6 Cont.
<p>XRD mineralogical analysis of the roasted material: Observed and Calculated Spectra for the samples processed at (<b>a</b>) 500 °C and (<b>b</b>) 700 °C.</p> Full article ">Figure 7
<p>XRD mineralogical analysis of the insoluble material after leaching followed by filtration: Observed and Calculated Spectra for the samples processed at (<b>a</b>) 500 °C and (<b>b</b>) 700 °C.</p> Full article ">
13 pages, 4703 KiB  
Article
Subsidence Management and Prediction System: A Case Study in Potash Mining
by Nor Sidki-Rius, Lluís Sanmiquel, Marc Bascompta and David Parcerisa
Minerals 2022, 12(9), 1155; https://doi.org/10.3390/min12091155 - 13 Sep 2022
Cited by 14 | Viewed by 2046
Abstract
Subsidence is an important environmental and safety issue in the mining sector, yet there remain voids in knowledge in terms of management and prediction. This study aims to improve knowledge on the impact of mining operations on the surface, reducing their effect on [...] Read more.
Subsidence is an important environmental and safety issue in the mining sector, yet there remain voids in knowledge in terms of management and prediction. This study aims to improve knowledge on the impact of mining operations on the surface, reducing their effect on the environment, increasing the safety of mining operations, monitoring stress behavior and predicting rock mass. Therefore, an analysis was carried out to process and analyze the measured subsidence data and, subsequently, create a numerical model to predict the surface subsidence of a case study mine. The model was developed based on a finite element method (FEM). It was achieved by considering the geological characteristics of the area, the design features of the mine, the surface subsidence measured over twelve years and the time-dependent behavior of the geological layers. The correlation obtained between the measured subsidence and the modelling results was very satisfactory, with a 90% confidence level, over the years analyzed. Hence, the efficiency of the system was confirmed, enabling the evaluation and the prediction of potential surface effects, and therefore improving the safety and environmental levels of the mining area. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
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<p>The mining area, with the two different perimeters, the five profiles and the twelve selected zones shown. The numbers on the left show the ID of each profile (from 01 to 05). The numbers enclosed in the orange perimeter show the ID of each analysed zone (01 to 12).</p> Full article ">Figure 2
<p>The targeted area used for the study and localization of the profiles.</p> Full article ">Figure 3
<p>The methodology followed to reach the average surface subsidence profile.</p> Full article ">Figure 4
<p>Example of an RS2 model with the geological and drifts characteristics.</p> Full article ">Figure 5
<p>Example of the seven stages and their associated Young’s modulus (E).</p> Full article ">Figure 6
<p>The methodology followed to define Young’s modulus decrease.</p> Full article ">Figure 7
<p>Relative subsidence values in MP 03.</p> Full article ">Figure 8
<p>Maximum subsidence values of MP 03.</p> Full article ">Figure 9
<p>Average subsidence profile together with a 90% confidence level.</p> Full article ">Figure 10
<p>Example of the FEM post-processing stage achieved using RS2.</p> Full article ">Figure 11
<p>Average subsidence profile with the results of the sections analyzed.</p> Full article ">
51 pages, 10601 KiB  
Review
Metalliferous Coals of Cretaceous Age: A Review
by Shifeng Dai, Sergey I. Arbuzov, Igor Yu. Chekryzhov, David French, Ian Feole, Bruce C. Folkedahl, Ian T. Graham, James C. Hower, Victor P. Nechaev, Nicola J. Wagner and Robert B. Finkelman
Minerals 2022, 12(9), 1154; https://doi.org/10.3390/min12091154 - 13 Sep 2022
Cited by 11 | Viewed by 4719
Abstract
Critical elements in coal and coal-bearing sequences (e.g., Li, Sc, V, Ga, Ge, Se, Y and rare earth elements, Zr, Nb, Au, Ag, platinum group elements, Re, and U) have attracted great attention because their concentrations in some cases may be comparable to [...] Read more.
Critical elements in coal and coal-bearing sequences (e.g., Li, Sc, V, Ga, Ge, Se, Y and rare earth elements, Zr, Nb, Au, Ag, platinum group elements, Re, and U) have attracted great attention because their concentrations in some cases may be comparable to those of conventional ore deposits. The enrichment of critical elements in coals, particularly those of Carboniferous-Permian and Cenozoic ages, have generally been attributed to within-plate (plume-related) volcanism and associated hydrothermal activity. However, Cretaceous coals are not commonly rich in critical elements, with the exception of some (e.g., Ge and U) in localised areas. This paper globally reviewed metalliferous coals from Siberia, the Russian Far East, Mongolia, South America, the United States and Mexico, Canada (Alberta and British Columbia), China, Africa, and Australasia (Victoria, Queensland, New South Wales, South Australia, Northern Territory, New Zealand, Nelson, West Coast, Canterbury, Otago, and Southland). The world-class Ge-U or Ge deposits in North China, Mongolia, and Siberia are the only commercially significant representatives of the Cretaceous metalliferous coals, which are related to bio-chemical reduction of oxidized meteoric, hydrothermal, or sea waters by organic matter of the peat bogs. The common Cretaceous coals worldwide are generally not rich in critical elements because intensive igneous activity led to extensive acidification of terrestrial and marine waters, which are responsible for the low coal metallogenesis during the Cretaceous period, especially the Early Cretaceous time. Full article
(This article belongs to the Special Issue Geological Evolution of The Cretaceous and Associated Mineralization)
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<p>Global distribution of coal basins and LIPs in the Early Cretaceous. Coal basins and LIPs are shown after Ziegler et al. [<a href="#B29-minerals-12-01154" class="html-bibr">29</a>] and Ernst et al. [<a href="#B28-minerals-12-01154" class="html-bibr">28</a>], respectively. The names in black indicate locations of mineralized coals discussed below. The Benue Trough is shown after Akiniemy et al. [<a href="#B30-minerals-12-01154" class="html-bibr">30</a>]. The names in red and white indicate LIPs.</p> Full article ">Figure 2
<p>Geological map of the Tarbagatai deposit area [<a href="#B33-minerals-12-01154" class="html-bibr">33</a>]. Note: 1—Quaternary system., alluvial sand, gravel, and loam.; 2—Upper Jurassic—Lower Cretaceous, Zugmar Formation, sandstone, siltstone, mudstone, conglomerates, and coal; 3—Upper Jurassic—Lower Cretaceous, Badin Formation, sandstone, siltstone, conglomerates, and basaltic-trachyandesite; 4—Cretaceous system, Kulevskaya Formation, siltstone, mudstone, sandstone, and coal; 5—Proterozoic, Berezovaya Formation, biotite, biotite-amphibole crystalline schist and gneiss; 6—Carboniferous system, fine-grained, leucocratic granites; 7—Lower Paleozoic, diorite; 8—Proterozoic, granite, gneissic granite; 9—Coal seams: (a) hidden under alluvial quaternary deposits, (b) traced on the surface; 10—Fractures: (a) found, (b) assumed.</p> Full article ">Figure 3
<p>Geological map showing the location of the Nizhne-Kas germaniferous lignite area [<a href="#B38-minerals-12-01154" class="html-bibr">38</a>]. Note: 1—Upper Cretaceous system, Campanian–Maastrichian stages, Symskaya Formation, upper subformation, Vari-grained quartz sand kaolinized with interlayers of kaolin clay and lignite; 2—Upper Cretaceous system, Cognac–Santonian stages.; Symskaya Formation, lower subformation., Vari-grained quartz sand with interlayers of kaolin clay; 3—Lower-Upper Cretaceous system, Albian-Cenomanian-Turonian stages, Simonovskaya Formation, Lake-alluvial deposits, Quartz sand with interlayers of clay and poorly lithified sandstone, germaniferous lignite; 4—Lower Cretaceous system, Valanginian–Barremian stages, Ilek Formation, Variegated clay and clayey sand with interlayers of siltstone, mudstone, sandstone, and inclusions of plant residue; 5—Riphean-Cambrian crystalline basement., Metasedimentary rock including granitoid, gabbroid, and ultrabasic bodies metamorphosed to amphibolite and greenschist facies; 6—The Serchanskoe Ge deposit; 7—Outlines of the Nizhne-Kas lignite deposit.</p> Full article ">Figure 4
<p>Schematic geological section of the lignite-bearing deposits along the Kas River [<a href="#B41-minerals-12-01154" class="html-bibr">41</a>]. Note: 1—Neogene–Quaternary undifferentiated systems, Sand, gravel-pebble, and loam with pebble; 2—Upper Cretaceous system, Symskaya Formation, Lake-alluvial deposits, Quartz sand with bands of clay and poorly lithified sandstone, lignite; 3—Lower–Upper Cretaceous system, Albian-Cenomanian–Turonian stages, Simonovskaya Formation, Gray sand with bands of clay, siltstone, and mudstone, lignite; 4—Lower Cretaceous system, Valanginian–Barremian stages, Ilek Formation, Variegated clay and clayey sand with bands of siltstone, mudstone, sandstone, and inclusions of charred plant residue; 5—Jurassic system, middle–upper divisions, Interbedded gray sandstone, siltstone, clay with lignite seams, and inclusions of charred plant remains; 6—lignite-bearing horizons; 7—Ge content in ppm of ash; 8—exploration well: its number above, depth in meters below.</p> Full article ">Figure 5
<p>The Upper Continental Crust (UCC)-normalized REE distribution in lignite of the Nizhne-Kas area.</p> Full article ">Figure 6
<p>The location and geological map of the study area [<a href="#B65-minerals-12-01154" class="html-bibr">65</a>]. Note: 1—Quaternary gray-colored sandy rubble deposits; 2—Paleogene–Neogene gray-colored terrigenous (clayey siltstone, occasionally clayey sand) deposits; 3—Lower Cretaceous coal-bearing molasse; 4—Upper Jurassic–Lower Cretaceous basalt, basaltic andesite, and andesite; 5—Upper Jurassic–Lower Cretaceous basalt–trachybasalt, trachyandesite; 6—Middle–Upper Permian rhyodacite, rhyolite; 7—Upper Permian rhyolite, trachyrhyolite; 8—Triassic–Lower Jurassic granite, leucogranite; 9—Tectonic dislocations: (a) found, (b) assumed; 10—The developed area with the coal mine.</p> Full article ">Figure 7
<p>The sampling scheme in the Aduunchuluun coal mine (photo by Sergey Arbuzov).</p> Full article ">Figure 8
<p>REE distribution patterns of weakly oxidized coal (ACh-4), oxidized coal (ACh-5), and sooty coal at the contact with the roof conglomerates (ACh-6); normalized for UCC according to Taylor and McLennan [<a href="#B71-minerals-12-01154" class="html-bibr">71</a>].</p> Full article ">Figure 9
<p>Map of South America with the approximate locations of the coalfields mentioned in the text shown.</p> Full article ">Figure 10
<p>Location of Eagle Pass, Maverick Co., Texas, USA, and Peidras Negras, Coahuila, Mexico.</p> Full article ">Figure 11
<p>Upper Continental Crust normalized REE spider plots (after Taylor and McLennan [<a href="#B71-minerals-12-01154" class="html-bibr">71</a>]) for the Eagle Pass coal and clay lithologies.</p> Full article ">Figure 12
<p>Western USA states with Cretaceous coals mentioned in this section (Alaska is on a separate figure. The counties with coal deposits are numbered on the key).</p> Full article ">Figure 13
<p>Location of Alaska with respect to the Canadian provinces of Alberta and British Columbia (coalfields discussed below) and Yukon Territory. The North Slope coal deposits are outlined by Corwin Bluff, the Brooks Range, Prudhoe Bay, and the Arctic Ocean (to the north).</p> Full article ">Figure 14
<p>General locations of Cretaceous coalfields in British Colombia and Alberta.</p> Full article ">Figure 15
<p>Upper Continental Crust normalization (after Taylor and McLennan [<a href="#B71-minerals-12-01154" class="html-bibr">71</a>]) for basin averages of Cretaceous coals from British Columbia [<a href="#B122-minerals-12-01154" class="html-bibr">122</a>].</p> Full article ">Figure 16
<p>Locations of some coalfields in China [<a href="#B127-minerals-12-01154" class="html-bibr">127</a>].</p> Full article ">Figure 17
<p>Location of the Shengli Coalfield and Wulantuga Ge ore deposit in Inner Mongolia, northern China. (<b>A</b>), location of the Shengli Coalfield; (<b>B</b>), geological background of the Shengli Coalfield.</p> Full article ">Figure 18
<p>Ash yield, Ge concentration (whole-coal basis), and REY distribution pattern in the section of the No. 6 Coal. REE plots (after Dai et al. [<a href="#B131-minerals-12-01154" class="html-bibr">131</a>]) normalized to Upper Continental Crust (UCC) [<a href="#B71-minerals-12-01154" class="html-bibr">71</a>]. (<b>A</b>), REY distribution patterns of the upper section of the coal seam including benches C6-11, C6-12, and C6-13; (<b>B</b>), REY distribution patterns of the middle section of the coal seam including benches C6-7 to C6-10; (<b>C</b>), REY distribution patterns of the lower section of the coal seam including benches C6-1 to C6-7.</p> Full article ">Figure 19
<p>REY distribution patterns of Ge-rich coals from the Yimin deposit (based on the data from Li et al. [<a href="#B135-minerals-12-01154" class="html-bibr">135</a>]).</p> Full article ">Figure 20
<p>Distribution and ages of coal deposits in Africa [<a href="#B142-minerals-12-01154" class="html-bibr">142</a>].</p> Full article ">Figure 21
<p>Geological map indicating the major coal occurrences in the Benue Trough of Nigeria (modified after Obaje et al. [<a href="#B150-minerals-12-01154" class="html-bibr">150</a>], extracted from Akinyemi et al. [<a href="#B146-minerals-12-01154" class="html-bibr">146</a>]).</p> Full article ">Figure 22
<p>Concentration coefficients (CC) for trace elements in the Benue Trough coals (using data averaged from <a href="#minerals-12-01154-t008" class="html-table">Table 8</a>). Total hard coal data are from Ketris and Yudovich [<a href="#B70-minerals-12-01154" class="html-bibr">70</a>]: (<b>A</b>) UBT; (<b>B</b>) MBT; (<b>C</b>) LBT.</p> Full article ">Figure 23
<p>New Zealand Cretaceous coalfields (after New Zealand Petroleum and Minerals).</p> Full article ">
33 pages, 23991 KiB  
Article
Mineralogical Properties of the Copper Slags from the SarCheshmeh Smelter Plant, Iran, in View of Value Recovery
by Saeed Mohamadi Nasab, Behnam Shafiei Bafti, Mohamad Reza Yarahmadi, Mohammad Mahmoudi Maymand and Javad Kamalabadi Khorasani
Minerals 2022, 12(9), 1153; https://doi.org/10.3390/min12091153 - 12 Sep 2022
Cited by 7 | Viewed by 2938
Abstract
Annually, hundreds of thousands of tons of slags are involved in the reverberator and flash smelting as well as converting operations of Cu-Fe sulfide concentrates to produce matte in the Sar Cheshmeh copper smelter plant, Iran, disposed in the landfill and cooled in [...] Read more.
Annually, hundreds of thousands of tons of slags are involved in the reverberator and flash smelting as well as converting operations of Cu-Fe sulfide concentrates to produce matte in the Sar Cheshmeh copper smelter plant, Iran, disposed in the landfill and cooled in air. Due to their relatively high average copper content (about 1.5 wt%), a mineral processing plant based on the flotation process has recently been established to produce thousands of tons of Cu-sulfide concentrate after slag crushing and fine grinding operation. In order to make the flotation process more efficient, more knowledge is required on the form and origin of the copper losses in the slag. To achieve this, mineralogical studies of the slags using optical microscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM) methods have been carried out. Mineralogical analyses showed the main part of copper losses into the semi- to fully-crystallized magnetite-rich reverberator and flash slags characterized by crystal–glass matrix ratio ≤ 1 is moderate to coarse particles of Cu-Fe sulfides, i.e., chalcopyrite (CuFeS2) and bornite (Cu5FeS4), that are mainly chemically entrapped. In contrast, the mechanically entrapped fine- to coarse-grain (from 20 up to 200 µm) spherical-shaped of high-grade matte particles with chalcocite (Cu2S) composition containing droplets or veinlets of metallic copper (Cu0) are the dominant forms of copper losses into the converter slags characterized by crystal–glass matrix ratio > 1. From the value recovery point of view, our result show that the fully crystallized slags containing moderate- to coarse-grain copper-bearing particles will result in efficient recovery of a significant amount of entrained copper due to better milling response compared to semi-crystallized ones due to locking the fine- to moderate-grain copper particles in the silicate glassy matrix. Laboratory-scale grinding experiments showed that normal (≤74 μm) to fine (≤44 μm) grinding of high- Cu grade slags lead to a significant increase in the liberation degree of copper particles. in contrast, the increase in fine particle fractions (<37 μm) due to re-grinding or ultra-fine grinding of the originally low-Cu grade slags does not lead to the liberation of copper particles, but it will reduce the efficiency of the flotation process. This study suggests that the highest rate of copper recovery of the slag by the flotation process will be obtained at particle size 80% passing 44 µm which has also reached the optimal liberation degree of copper-bearing particles. Full article
(This article belongs to the Special Issue Metallurgical Solid Waste: Mineralogy, Chemistry and Application/Treatment)
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<p>Stock-pilled slags in SarCheshmeh Copper Complex; (<b>A</b>–<b>C</b>) reverberator furnace slag, (<b>D</b>) converter furnace slag, and (<b>E</b>) flash furnace slag.</p> Full article ">Figure 2
<p>Photographs showing the physical properties of the studied reverberator (<b>A</b>–<b>C</b>), flash (<b>D</b>,<b>E</b>), and converter slags (<b>F</b>). The reverberator furnace slag has a porous surface and is oxidized. Additionally, flash and converter furnaces slags have a metallic luster. In the polished slabs of slags, the copper-bearing phases (i.e., CBP) as shiny droplets and veinlets are observed.</p> Full article ">Figure 3
<p>Comparison of density in the studied slag samples.</p> Full article ">Figure 4
<p>Bulk chemistry of the studied slags.</p> Full article ">Figure 5
<p>Relationship between Cu content (wt%) and density (g/cm<sup>3</sup>) in the studied slags.</p> Full article ">Figure 6
<p>XRD graph of a Cu-rich converter slag (9.35 wt% Cu).</p> Full article ">Figure 7
<p>Magnetite content in the studied slags.</p> Full article ">Figure 8
<p>Microphotographs showing mode occurrence of fayalite phase in the reverberator (<b>A</b>,<b>B</b>,<b>D</b>–<b>F</b>,<b>H</b>,<b>I</b> microphotographs), flash (<b>C</b>,<b>G</b>) microphotographs) and converter ((<b>J</b>) microphotograph) slags. (<b>A</b>,<b>B</b>) microphotographs were taken in transmitted light mode, and others were taken in reflected light mode. See the related text for more details. CBP = copper-bearing phases, Fl = fayalite, Mag = magnetite, Gls = glass.</p> Full article ">Figure 9
<p>Microphotographs showing mode occurrence of magnetite in the reverberator (<b>A</b>,<b>B</b>,<b>D</b>) microphotographs), flash ((<b>F</b>) microphotograph), and converter slags ((<b>C</b>,<b>E</b>) microphotographs). See the related text for more details. CBP: copper-bearing phases, Fl = fayalite, Mag = magnetite, Gls = glass, Qtz = quartz.</p> Full article ">Figure 10
<p>Microphotographs showing mode occurrence of copper-bearing phases in reverberator slag samples. See the related text for more details. Bn = bornite, Cc = chalcocite, Ccp = chalcopyrite, Po = pyrrhotite, Tl = troilite, Cu = metallic copper, Fl = fayalite, Mag = magnetite, Gls = glass.</p> Full article ">Figure 11
<p>Microphotographs showing mode occurrence of copper-bearing phases in flash slag samples. See the related text for more details. Bn = bornite, Cc = chalcocite, Ccp = chalcopyrite, Cu = metallic copper, Fl = fayalite, Mag = magnetite, Gls = glass.</p> Full article ">Figure 12
<p>Microphotographs showing mode occurrence of copper-bearing phases in converter slag samples. See the related text for more details. Bn = bornite, Cc = chalcocite, Ccp = chalcopyrite, Cu = metallic copper, Fl = fayalite, Mag = magnetite, Gls = glass.</p> Full article ">Figure 13
<p>Mineralogical composition of copper-bearing phases in the studied slags based on SEM/EDS elemental determinations of point analyses (n = 43 points). The star symbol represents the theoretical chemical composition of Cu±Fe sulfide minerals.</p> Full article ">Figure 14
<p>(<b>A</b>) Reflected light microphotograph, (<b>B</b>) back scatter electron microphotograph, (<b>C</b>) analytical points map, (<b>D</b>–<b>H</b>) elemental mapping images, and (<b>I</b>) semi-quantitative analytical data of copper-bearing phase in the converter slag sample. The composition of the main copper-bearing phase in this sample (points 1, 3, and 6) falls between chalcocite (Cc.)–yarovite (Yt.) mineral group. Other phases are magnetite (point 2) and fayalite (points 4 and 5).</p> Full article ">Figure 15
<p>(<b>A</b>) Reflected light microphotograph, (<b>B</b>) back scatter electron microphotograph, (<b>C</b>) analytical points map, (<b>D</b>–<b>G</b>) elemental mapping images, and (<b>H</b>) semi-quantitative analytical data of copper-bearing phase (Cc = chalcocite and Yt = yarovite) in the flash slag sample. The composition of the main copper-bearing phase in this sample (points 1, 3, and 4) falls between chalcocite (Cc.)–yarovite (Yt.) mineral group.</p> Full article ">Figure 16
<p>(<b>A</b>) Reflected light microphotograph, (<b>B</b>) back scatter electron microphotograph, (<b>C</b>) analytical points map, (<b>D</b>–<b>H</b>) elemental mapping images, and (<b>I</b>) semi-quantitative analytical data of copper-bearing phase in the reverberator slag sample. The composition of the main copper-bearing phase in this sample (points 3, 5, and 8) falls between bornite (Bn.)–idaite and chalcopyrite–cubanite mineral groups. Other phases are troilite (Tl.)–pyrrhotite (Po.) (point 2), magnetite (Mag.) (point 1), fayalite (Fl.) and pyroxene (points 6 and 7). Point 4 is probably an Sb-Ni-Cu-Fe-Co alloy phase.</p> Full article ">Figure 17
<p>(<b>A</b>) Reflected light microphotograph, (<b>B</b>) back scatter electron microphotograph, (<b>C</b>) analytical points map, (<b>D</b>–<b>I</b>) elemental mapping images, and (<b>J</b>) semi-quantitative analytical data of copper-bearing phase in the converter slag sample. The composition of the main copper-bearing phase in this sample (points 3, 4, and 5) falls between chalcocite (Cc.)–yarovite (Yt.) and bornite–idaite mineral groups. Points 1 and 2 are probably wulfenite (PbMoO4) containing Ni-Cu-W impurities.</p> Full article ">Figure 18
<p>(<b>A</b>) Reflected light microphotograph, (<b>B</b>) back scatter electron microphotograph, (<b>C</b>) analytical point map, (<b>D</b>–<b>G</b>) elemental mapping images, and (<b>H</b>) semi-quantitative analytical data of copper-bearing phase in reverberator slag sample. The composition of the main copper-bearing phase in this sample (point 3) falls between bornite (Bn.)–idaite mineral group. Other phases within copper-bearing phase are magnetite (point 1), troilite (Tl.)–pyrrhotite (Po.) (point 2), and Sb-Mo-Cu-Ni-Fe-Ag-Co alloy (point 4).</p> Full article ">Figure 19
<p>Comparison of particle size distribution in the first mode grinding of the bulk slag samples.</p> Full article ">Figure 20
<p>Copper content variations with decreasing the particle size in the high- and low-Cu grade ground slags.</p> Full article ">Figure 21
<p>Comparative plots showing variations of copper content and liberation degree of the copper-bearing particles in the ground slags containing different percentages of particles &lt; 44 µm.</p> Full article ">Figure 22
<p>Reflected light microphotographs (20× magnification) comparing the particle size and liberation rate of copper-bearing particles in four fractions with different percentage of particles &lt; 44 µm in the high-Cu grade ground samples of the reverberator slag (i.e., HRb = 0.9 wt% Cu). Noted that the copper particles (characterized by yellow in color and a higher reflectance than non-valued phases) are locked in the ground sample containing 50% of particles passing 44 µm (i.e., HRb-50% &lt; 44 µm microphotograph) and their liberation as fine particles in the slag with a higher percentage of particles passing 44 µm (i.e., HRb-60%, HRb-70%, and HRb-80% &lt; 44 µm microphotographs).</p> Full article ">Figure 23
<p>Reflected light microphotographs (20× magnification) comparing the particle size and liberation rate of copper-bearing particles in four fractions with different percentage of particles &lt; 44 µm in the low-Cu grade ground samples of the reverberator slag (i.e., LRb = 0.75 wt% Cu). Noted that the copper particles (characterized by yellow in color and a higher reflectance than non-valued phases) are locked in the ground sample containing 50% and 60% of particles passing 44 µm (i.e., LRb-50% and LRb-60% &lt; 44 µm microphotographs) and their liberation as fine particles in the slag with a higher percentage of particles passing 44 µm (LRb-70% and LRb-80% &lt; 44 µm microphotographs).</p> Full article ">Figure 24
<p>Reflected light microphotographs (20× magnification) comparing the particle size and liberation rate of copper-bearing particles in four fractions with different percentage of particles &lt; 44 µm in the ground samples of the flash slag (i.e., FL = 1.14 wt% Cu). Noted that the copper particles (characterized by yellow in color and a higher reflectance than non-valued phases) are locked in the ground sample containing 50% and 60% of particles passing 44 µm (FL-50% and FL-60% &lt; 44 µm microphotographs) and their liberation as fine particles in the slag with a higher percentage of particles passing 44 µm (FL-70% and FL-80% &lt; 44 µm microphotographs).</p> Full article ">Figure 25
<p>Reflected light microphotographs (20× magnification) comparing the particle size and liberation rate of copper-bearing particles in four fractions with different percentage of particles &lt; 44 µm in the ground samples of the converter slag (i.e., CT = 1.69 wt% Cu). Noted that the copper particles (characterized by yellow in color and a higher reflectance than non-valued phases) are locked in the ground sample containing 50% of particles passing 44 µm (i.e., CT-50% &lt; 44 µm microphotograph) and their liberation as fine particles in the slag with a higher percentage of particles (80%) passing 44 µm (i.e., CT-80% &lt; 44 µm microphotograph).</p> Full article ">
23 pages, 10389 KiB  
Article
Mineral Chemistry of the Lower Cretaceous Jinling Iron Skarn Deposit, Western Shandong Province, North China Craton: Implications for the Iron Skarn Mineralization Process
by Fang-Hua Cui, Chao Zhang, Dai-Tian Jin, Lu-Yuan Wang, Ji-Lei Gao, Ming Ma and Ya-Dong Li
Minerals 2022, 12(9), 1152; https://doi.org/10.3390/min12091152 - 12 Sep 2022
Cited by 2 | Viewed by 2136
Abstract
The source of iron material and the mineralization process of iron skarn deposits within the eastern North China Craton are ambiguous. In this study, we present new mineral chemical data of the Jinling skarn deposit, located in western Shandong Province, east China. Based [...] Read more.
The source of iron material and the mineralization process of iron skarn deposits within the eastern North China Craton are ambiguous. In this study, we present new mineral chemical data of the Jinling skarn deposit, located in western Shandong Province, east China. Based on the petrography study and mineral chemical data, we suggest that the Jinling iron skarn deposit is hydrothermal and the metallogenic iron is enriched by leaching of Fe-rich fluids derived from primitive magmatic melt from the solidified diorites. The Jinling iron skarn deposit formed as a result of several mineralization processes: (1) Fe-rich hydrothermal fluids exsolved from a hydrous parental magma that was characterized by high iron content, oxygen fugacity (fO2), and salinity; (2) the Fe content of the fluids was augmented during the alkali metasomatism stage via the leaching of Fe from the solidified dioritic rocks; (3) diopside and garnet in skarns formed under relatively alkaline and oxidizing conditions during the later prograde skarn stage; (4) during the retrograde skarn stage, amphibole, chlorite, epidote, phlogopite, serpentine, biotite, and chlorite formed under more oxidizing conditions, and subsequent mixing of the Fe-rich fluids with meteoric water triggered the precipitation of the massive magnetite; and (5) the final sulfide–carbonate stage was involved in the formation of carbonate and sulfide minerals as a result of a change in conditions from oxidizing to reducing. Full article
(This article belongs to the Special Issue Mineral Resources in North China Craton)
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<p>Tectonic sketch map of the North China Craton (modified from Zhao [<a href="#B16-minerals-12-01152" class="html-bibr">16</a>]), and distribution of iron skarn deposits (modified from Zhao et al. [<a href="#B2-minerals-12-01152" class="html-bibr">2</a>]) and Lower Cretaceous magmatic rocks (modified from Zhang et al. [<a href="#B17-minerals-12-01152" class="html-bibr">17</a>]).</p> Full article ">Figure 2
<p>(<b>a</b>) Simplified geological map of western Shandong (modified from Lan et al. [<a href="#B22-minerals-12-01152" class="html-bibr">22</a>]). (<b>b</b>) Sketch map of the Jinling pluton and distribution of the Jinling iron skarn deposits (modified from Hao [<a href="#B23-minerals-12-01152" class="html-bibr">23</a>]).</p> Full article ">Figure 3
<p>Cross-section diagram of the Jinling iron deposit (modified from Hao [<a href="#B23-minerals-12-01152" class="html-bibr">23</a>]). (<b>a</b>) Houjiazhuang ore section. (<b>b</b>) Wangwangzhuang ore section.</p> Full article ">Figure 4
<p>Schematic section view of the contact zone between the Jinling dioritic pluton and Ordovician carbonates, including marble, recrystallized limestone, and limestone. The yellow dashed line in this figure is the boundary of geological bodies.</p> Full article ">Figure 5
<p>Petrographic features of plutonic rocks of the Jinling pluton. (<b>a</b>) Intensely albitized diorites show the replacement of plagioclase by albite. (<b>b</b>,<b>c</b>) Small albite and biotite grains have partially replaced hornblende and pyroxene resulting from alkali metasomatism. All photos were taken under crossed polarizers. Abbreviations: Ab = albite, Hb = hornblende, Bt = biotite, Cpx = clinopyroxene, Mag = magnetite, Pl = plagioclase.</p> Full article ">Figure 6
<p>Various types of iron ore and characteristics of wall rocks in the Jinling iron skarn deposit. (<b>a</b>) Disseminated magnetite that is interstitial to early euhedral diopside. (<b>b</b>,<b>c</b>) Massive magnetite crystals coexisted with biotite and chlorite. (<b>d</b>) Banded magnetite. (<b>e</b>) Banded magnetite that has enclosed an early anhedral crystal of diopside that was metasomatized. (<b>f</b>) Massive magnetite crystals coexisted with fibrous serpentine that has completely replaced early diopside. (<b>g</b>) Metasomatic texture formed between early subhedral–euhedral diopside, garnet, and late massive magnetite. (<b>h</b>) The residual metasomatic texture between diopside and fibrous serpentine coexisted with massive magnetite. (<b>i</b>,<b>j</b>) Late calcite has partially replaced euhedral massive magnetite. (<b>k</b>,<b>l</b>) Euhedral pyrite and chalcopyrite veins in iron ore. Photos (<b>a</b>,<b>b</b>,<b>d</b>,<b>e</b>,<b>g</b>,<b>i</b>,<b>j</b>) were taken under open polarizers and (<b>c</b>,<b>f</b>,<b>h</b>) taken under crossed polarizers. Abbreviations: Bt = biotite, Cal = calcite, Chl = chlorite, Ccp = chalcopyrite, Di = diopside, Grt = garnet, Mag = magnetite, Py = pyrite, Srp = serpentine.</p> Full article ">Figure 7
<p>Paragenetic association of minerals from the different stages of mineralization. (<b>a</b>) Two types of euhedral diopside formed during the prograde skarn stage. Light-green diopside, which coexisted with garnet, grew along the margins of the colorless diopside. (<b>b</b>) Subhedral–euhedral Ca-rich amphibole that formed during the retrograde skarn stage. The amphibole replaced the early diopside and was partially replaced by late pyrite and calcite. (<b>c</b>,<b>d</b>) Diopside was replaced by late amphibole and epidote. (<b>e</b>) Early diopside was replaced by late amphibole, both of which were subsequently partially replaced by late pyrite and calcite. (<b>f</b>) Anhedral diopside was metasomatized and partially replaced by biotite and quartz. (<b>g</b>) Epidote, phlogopite, chlorite, calcite, and quartz have partially replaced early diopside. Note the association of phlogopite with Ca-rich amphibole. (<b>h</b>) Diopside was replaced by zoned andradite. (<b>i</b>) Massive magnetite was partially replaced by calcite that was modified by earlier diopside and garnet. (<b>j</b>) Massive magnetite was partially replaced by late anhedral quartz. (<b>k</b>) Euhedral epidote was partially replaced by late anhedral calcite, within which twin lamellae are parallel to the angle bisector of the two heterotropic cleavages. (<b>l</b>) Pyrite associated with calcite that partially replaced euhedral amphibole. Photos (<b>a</b>–<b>d</b>,<b>g</b>,<b>i</b>) were taken under open polarizer, and (<b>e</b>,<b>f</b>,<b>h</b>,<b>j</b>,<b>k</b>) were taken under crossed polarizers. in the figure caption. Abbreviations: Amp = amphibole, Bt = biotite, Calc-amp = calcic amphibole, Cal = calcite, Chl = chlorite, Di = diopside, Di1 = colourless diopside, Di2 = light green diopside, Ep = epidote, Grt = garnet, Mag = magnetite, Phl = phlogopite, Py = pyrite, Qz = quartz.</p> Full article ">Figure 8
<p>Mineral paragenesis for the Jinling iron skarn deposit.</p> Full article ">Figure 9
<p>BSE images (<b>a</b>,<b>b</b>) and compositional (<b>c</b>,<b>d</b>) variation of feldspars from Jinling diorites.</p> Full article ">Figure 10
<p>Classification diagram of clinopyroxenes from Jinling diorites, skarn, and ore (<b>a</b>), modified from Morimoto et al. [<a href="#B24-minerals-12-01152" class="html-bibr">24</a>]) and the compositional fields for garnet in Fe skarn deposits (Meinert et al. [<a href="#B25-minerals-12-01152" class="html-bibr">25</a>]) are shown in the diagram for comparison (<b>b</b>).</p> Full article ">Figure 11
<p>Photomicrographs were taken under open polarizer (<b>a</b>), BSE image (<b>c</b>) and compositional variation (<b>b</b>,<b>d</b>) of garnets from Jinling skarn and ore and the compositional fields for garnet in Fe skarn deposits (Meinert et al. [<a href="#B25-minerals-12-01152" class="html-bibr">25</a>]) are shown in the diagram for comparison.</p> Full article ">Figure 12
<p>Classification diagram of amphiboles from Jinling skarn and ore.</p> Full article ">Figure 13
<p>Variation in FeO content from magmatic, disseminated, banded, and massive magnetites from Jinling diorites, skarn, and ore.</p> Full article ">Figure 14
<p>Fe vs. V/Ti genetic type discrimination diagram for magnetites from the skarn and ore of the Jinling deposit (modified from Wen [<a href="#B40-minerals-12-01152" class="html-bibr">40</a>]).</p> Full article ">Figure 15
<p>FeO vs. MgO diagram (<b>a</b>) and FeO vs. Al<sub>2</sub>O<sub>3</sub> diagram (<b>b</b>) for magnetites from the skarn and ore of the Jinling deposit.</p> Full article ">Figure 16
<p>Sketch model of mineralizing processes of the Jinling deposit, Western Shandong Province. (<b>a</b>) Alkali metasomatism stage along with fluid exsolution. (<b>b</b>) Diopside and garnet formed due to fluid–rock interaction during the prograde skarn stage. (<b>c</b>) Amphibole, chlorite and epidote formed and the precipitation of large quantities of magnetite occurred during the retrograde skarn stage. (<b>d</b>) Carbonate, quartz and small amounts of sulfides formed during the sulfide–carbonate stage.</p> Full article ">
17 pages, 9106 KiB  
Article
Unravelling the Temporal and Chemical Evolution of a Mineralizing Fluid in Karst-Hosted Deposits: A Record from Goethite in the High Atlas Foreland (Morocco)
by Michèle Verhaert, Cécile Gautheron, Augustin Dekoninck, Torsten Vennemann, Rosella Pinna-Jamme, Abdellah Mouttaqi and Johan Yans
Minerals 2022, 12(9), 1151; https://doi.org/10.3390/min12091151 - 11 Sep 2022
Cited by 1 | Viewed by 1781
Abstract
Timing and duration of ore deposit formation are crucial to understanding the mineralization process. To address this, the geochronological (U-Th)/He method, geochemical and H- and O-isotope compositions of pure goethite formed in the Imini karst-hosted Mn district (High Atlas, Morocco) were examined in [...] Read more.
Timing and duration of ore deposit formation are crucial to understanding the mineralization process. To address this, the geochronological (U-Th)/He method, geochemical and H- and O-isotope compositions of pure goethite formed in the Imini karst-hosted Mn district (High Atlas, Morocco) were examined in detail. Two main generations of cavity-filling and fracture-filling goethite are identified, and both precipitated prior to the massive Mn oxide ore. The δD and δ18O values reveal that the mineralizing fluid of cavity and fracture-filling goethite is meteoric-derived but enriched in 18O due to fluid–rock interactions with the host rock dolostone or mixing with O2-rich surface water resident in an open karst system. The cavity-filling goethite precipitated between 95 to 80 Ma, whereas fracture-filling goethite formed between 80 to 50 Ma. Ore deposition occurred discontinuously during the early Atlas doming associated with one or more early compressional events in the Atlas tectonism. The increase in δD values and depletion in U content result from a change in the mineralizing fluid within the karst system. At about 50 Ma, the fluid is notably enriched in U, Cu and trace metals. Full article
(This article belongs to the Special Issue Mineralogy of the Supergene Zone)
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Figure 1

Figure 1
<p>(<b>a</b>) Simplified structural map of Morocco. (<b>b</b>) Geological map of the Cretaceous sediments, Neogene volcanism and Mn occurrences [<a href="#B14-minerals-12-01151" class="html-bibr">14</a>]. (<b>c</b>) Geological map of the Imini district showing the location of Far West, Tifersine and Plateaux deposits [<a href="#B12-minerals-12-01151" class="html-bibr">12</a>]. (<b>d</b>) Stratigraphic log of the western part of the district [<a href="#B13-minerals-12-01151" class="html-bibr">13</a>]. Cross-section is presented in [<a href="#B11-minerals-12-01151" class="html-bibr">11</a>].</p> Full article ">Figure 2
<p>Simplified and modified paragenetic sequence. The position of the Fe mineralization prior to the Mn oxide is illustrated. Adapted from [<a href="#B12-minerals-12-01151" class="html-bibr">12</a>].</p> Full article ">Figure 3
<p>Style of the Fe mineralization and schematic representations. (<b>A</b>) Botryoidal goethite filling fractures and forming thin veins at Tifersine site (sample 18TIF20). (<b>B</b>) Large botryoidal goethite filling cavities at the Plateaux site (sample 18PL07).</p> Full article ">Figure 4
<p>Pictures of botryoidal goethite samples. The distinction between goethite filling thin fractures (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>) and large goethite filling cavities (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>,<b>i</b>) is shown. The black frame indicates the area sampled for (U-Th)/He dating and isotopic analyses. Goethite (<b>h</b>,<b>i</b>) are exposition specimens for which no (U-Th)/He dating or isotopic analyses were carried out. Gtt = goethite; Hem = hematite; Cry = cryptomelane; Cal = calcite.</p> Full article ">Figure 5
<p>(<b>a</b>–<b>c</b>) SEM microphotographs of the most representative samples in back-scattered electron mode. (<b>d</b>) SEM microphotograph of botryoidal sample 18PL07. Secondary electron mode with the size of goethite crystallites (width exceeding 100 nm). Gtt = goethite; Hem = hematite; Co = coronadite group minerals; Cal = calcite.</p> Full article ">Figure 6
<p>Geochemical data of Far West, Tifersine and Plateaux samples. (<b>a</b>) Trace element patterns; (<b>b</b>) rare earth element patterns normalized to the continental crust; (<b>c</b>) As vs. Cu contents and (<b>d</b>) U vs. Cu contents. The fracture-filling goethite is reported using gray circle symbols, except for 18TIF-20 where yellow-gray color is used, and the cavity-filling goethite is reported with a red open circle symbol.</p> Full article ">Figure 7
<p>δD, δ<sup>18</sup>O and (U-Th)/He data of Imini goethite. (<b>a</b>) Evolution of the δD and δ<sup>18</sup>O values of the studied goethite. Continental goethite from [<a href="#B31-minerals-12-01151" class="html-bibr">31</a>] is reported for comparison as part of the supergene field. Temperature lines are calculated from [<a href="#B32-minerals-12-01151" class="html-bibr">32</a>]. The meteoric water line (MWL) of [<a href="#B33-minerals-12-01151" class="html-bibr">33</a>] is given for reference. Carbonate ranges of values of Cenomanian-Turonian dolostones are given by the gray shade [<a href="#B34-minerals-12-01151" class="html-bibr">34</a>]. (<b>b</b>,<b>c</b>) Imini goethite GHe age variation as a function of the effective uranium U content and the δD values, respectively. Cavity- and fracture-filling goethite (open red circle and orange circle, respectively) is reported. Sample 18TIF-20 fracture-filling goethite is distinguished from the other samples with a star filling the orange circle.</p> Full article ">Figure 8
<p>Cavity-filling botryoidal goethite samples (<b>a</b>) 18FAR02A, (<b>b</b>) 18TIF01 and (<b>c</b>) 18PL07 and evolution of Th and U contents and (U-Th)/He ages along transects of the samples. On the sample pictures, the letters A to F and the white rectangular zone refer to the sampling zone given in <a href="#app1-minerals-12-01151" class="html-app">Table S6</a>.</p> Full article ">Figure 9
<p>Imini cavity and fracture-filling goethite (U-Th)/He (this study) and Tasdremt coronadite group minerals <sup>40</sup>Ar/<sup>39</sup>Ar [<a href="#B14-minerals-12-01151" class="html-bibr">14</a>]: histogram of age distribution. The late Cretaceous and middle to early Cenozoic compressional phases [<a href="#B15-minerals-12-01151" class="html-bibr">15</a>,<a href="#B37-minerals-12-01151" class="html-bibr">37</a>] and temporal information of sedimentological deposits [<a href="#B16-minerals-12-01151" class="html-bibr">16</a>,<a href="#B23-minerals-12-01151" class="html-bibr">23</a>] are also reported.</p> Full article ">
11 pages, 4515 KiB  
Review
Phanerozoic Evolution of Continental Large Igneous Provinces: Implications for Galactic Seasonality
by Victor P. Nechaev, Frederick L. Sutherland and Eugenia V. Nechaeva
Minerals 2022, 12(9), 1150; https://doi.org/10.3390/min12091150 - 11 Sep 2022
Cited by 1 | Viewed by 1655
Abstract
This study reviews the available data on the Phanerozoic plume activity (Large Igneous Provinces (LIP’s) size and frequency) and geochemistry of their igneous rocks. A major goal of this review is to try to find the changes in intensity and geochemistry of mantle [...] Read more.
This study reviews the available data on the Phanerozoic plume activity (Large Igneous Provinces (LIP’s) size and frequency) and geochemistry of their igneous rocks. A major goal of this review is to try to find the changes in intensity and geochemistry of mantle plumes linked to the Earth’s evolution and galactic seasonality that was supposed in the authors’ previous publications. The data indicate that the Cambrian–Ordovician and Jurassic–Cretaceous galactic summers were associated with peaks of various igneous activities including both plume- and subduction/collision-related magmatism, while the Carboniferous–Permian and current galactic winters led to significant drops within the igneous activity. The materials subducted into the transitional and lower mantle, which highly influenced the plume magmas in the galactic-summer times, were less significant in the galactic spring and autumn seasons. The least subduction-influenced LIPs were probably the Tarim and Emeishan deep plume magmas that developed in the mid–late Permian, during the galactic late winter–early spring subseason. The Fe enrichment of clinopyroxenite, gabbro, and associated ores of these provinces might be caused by fluids ascending from the core–mantle boundary. However, the most significant core influence through plume-associated fluids on the surface of solid Earth is supposed to have occurred in the galactic summer times (Cambrian–Ordovician and Jurassic–Cretaceous), which is indicated by peak abundances of ironstone ores. Their contributions to the Cambrian–Ordovician and Jurassic–Cretaceous plume magmas were, however, obscured by more significant influences from subduction. Full article
(This article belongs to the Special Issue Geological Evolution of The Cretaceous and Associated Mineralization)
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Figure 1

Figure 1
<p>The proposed galactic seasons (after [<a href="#B2-minerals-12-01150" class="html-bibr">2</a>] in comparison with global changes in igneous and iron ore-forming activities (after [<a href="#B19-minerals-12-01150" class="html-bibr">19</a>,<a href="#B20-minerals-12-01150" class="html-bibr">20</a>,<a href="#B21-minerals-12-01150" class="html-bibr">21</a>]) with additions from [<a href="#B6-minerals-12-01150" class="html-bibr">6</a>,<a href="#B22-minerals-12-01150" class="html-bibr">22</a>]). (A)volume of volcanic rocks; (<b>B</b>) ophiolite frequency; (<b>C</b>) kimberlite frequency; (<b>D</b>) carbonatite deposits (<b>E</b>) Lip’s size (<b>F</b>) number of ooidal ironstone deposits. The LIPs names are shown only for the provinces for which geochemical data are used in this study.</p> Full article ">Figure 2
<p>TAS diagrams for distinguishing the selected LIPs between the Andersonian, Morganian and Super plumes according to the discrimination by Zang et al. [<a href="#B18-minerals-12-01150" class="html-bibr">18</a>]. Plots of the LIPs attributed to the galactic spring, summer, autumn, and winter times (see <a href="#minerals-12-01150-f001" class="html-fig">Figure 1</a>) are colored in green, red, yellow–orange, and blue, respectively. Data sources are cited in <a href="#sec2-minerals-12-01150" class="html-sec">Section 2</a>. (<b>A</b>) Kalkarindji; (<b>B</b>) Yakutian-Vilui and Kola-Dnieper; (<b>C</b>) Scagerrak and Tarim; (<b>D</b>) Emeishan and Siberian Trips; (<b>E</b>) Yellowstone and Afro-Arabian; (<b>F</b>) Geccan and North Atlantic; (<b>G</b>) Parana-Etendeka and High Arctic; (<b>H</b>) Karoo and Central Altantic.</p> Full article ">Figure 3
<p>Th/Nb vs. TiO<sub>2</sub>/Yb in mafic rocks (SiO<sub>2</sub> = 41–52 wt.%) from the selected LIPs on the LIP printing diagram with a subduction-modified lithospheric mantle (SZLM) array and a ‘plume’ array [<a href="#B16-minerals-12-01150" class="html-bibr">16</a>,<a href="#B17-minerals-12-01150" class="html-bibr">17</a>]. MORB, mid-oceanic ridge basalt; OIB, oceanic island basalt; OPB, oceanic plateau basalt. Data sources are cited in <a href="#sec2-minerals-12-01150" class="html-sec">Section 2</a>. (<b>A</b>) Kalkarindji; (<b>B</b>) Yakutian-Vilui and Kola-Dnieper; (<b>C</b>) Scagerrak and Tarim; (<b>D</b>) Emeishan and Siberian Trips; (<b>E</b>) Yellowstone and Afro-Arabian; (<b>F</b>) Geccan and North Atlantic; (<b>G</b>) Parana-Etendeka and High Arctic; (<b>H</b>) Karoo and Central Altantic.</p> Full article ">Figure 4
<p>The SiO<sub>2</sub>/FeOt ratio in magmatic rocks of the selected LIPs. FeOt is total iron as FeO. Compositions of ironstone deposits, the core, primitive mantle, and crust are shown after [<a href="#B22-minerals-12-01150" class="html-bibr">22</a>,<a href="#B24-minerals-12-01150" class="html-bibr">24</a>,<a href="#B25-minerals-12-01150" class="html-bibr">25</a>,<a href="#B26-minerals-12-01150" class="html-bibr">26</a>], respectively. Data sources are cited in <a href="#sec2-minerals-12-01150" class="html-sec">Section 2</a>. (<b>A</b>) Kalkarindji; (<b>B</b>) Yakutian-Vilui and Kola-Dnieper; (<b>C</b>) Scagerrak and Tarim; (<b>D</b>) Emeishan and Siberian Trips; (<b>E</b>) Yellowstone and Afro-Arabian; (<b>F</b>) Geccan and North Atlantic; (<b>G</b>) Parana-Etendeka and High Arctic; (<b>H</b>) Karoo and Central Altantic.</p> Full article ">
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