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Search Results (7,421)

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9 pages, 3837 KiB  
Article
Using Principal Component Analysis for Temperature Readings from YF3:Pr3+ Luminescence
by Anđela Rajčić, Zoran Ristić, Jovana Periša, Bojana Milićević, Saad Aldawood, Abdullah N. Alodhayb, Željka Antić and Miroslav D. Dramićanin
Technologies 2024, 12(8), 131; https://doi.org/10.3390/technologies12080131 (registering DOI) - 12 Aug 2024
Abstract
The method of measuring temperature using luminescence by analyzing the emission spectra of Pr3+-doped YF3 using principal component analysis is presented. The Pr3+-doped YF3 is synthesized using a solid-state technique, and its single-phase orthorhombic crystal structure is [...] Read more.
The method of measuring temperature using luminescence by analyzing the emission spectra of Pr3+-doped YF3 using principal component analysis is presented. The Pr3+-doped YF3 is synthesized using a solid-state technique, and its single-phase orthorhombic crystal structure is confirmed using X-ray diffraction. The emission spectra measured within the 93–473 K temperature range displays characteristic Pr3+ f-f electronic transitions. The red emission from the 3P0,13H6,3F2 electronic transition mostly dominates the spectra. However, at low temperatures, the intensity of the green emissions from the 3P0,13H5, deep-red 3P0,13F4, and the deep-red emissions from the 3P0,13F4 transitions are considerably lower compared to the intensity of the red emissions. Temperature variations directly impact the photoluminescent spectra, causing a notable increase in the green and deep-red emissions from the 3P1 excited state. We utilized the entire spectrum as an input for principal component analysis, considering each temperature as an independent group of data. The first principal component explained 99.3% of the variance in emission spectra caused by temperature and we further used it as a reliable temperature indicator for luminescence thermometry. The approach has a maximum absolute sensitivity of around 0.012 K−1. The average accuracy and precision values are 0.7 K and 0.5 K, respectively. Full article
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Figure 1

Figure 1
<p>XRD pattern of Pr<sup>3+</sup>-doped YF<sub>3</sub> powder presented with ICDD Card No. 01-070-1935 shows a single-phase orthorhombic crystal structure.</p>
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<p>Scanning electron microscopy images of Pr<sup>3+</sup>-doped YF<sub>3</sub> sample under (<b>a</b>) 2000<math display="inline"><semantics> <mrow> <mo>×</mo> </mrow> </semantics></math>; and (<b>b</b>) 30,000<math display="inline"><semantics> <mrow> <mo>×</mo> </mrow> </semantics></math> magnification; (<b>c</b>) particle size distribution.</p>
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<p>Pr<sup>3+</sup>-doped YF<sub>3</sub> (<b>a</b>) excitation spectrum (λ<sub>em</sub> = 605 nm) and (<b>b</b>) temperature-dependent photoluminescent emission spectra (λ<sub>exc</sub> = 450 nm) recorded in the 500–750 nm spectral and 200–473 K temperature range.</p>
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<p>(<b>a</b>) The cumulative explained variance plot, (<b>b</b>) typical photoluminescent emission spectrum of Pr<sup>3+</sup>−doped YF<sub>3</sub> sample (top graph), and corresponding values for <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mn>1</mn> </mrow> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">o</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">f</mi> <mi mathvariant="normal">f</mi> </mrow> </msubsup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mn>2</mn> </mrow> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">o</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">f</mi> <mi mathvariant="normal">f</mi> </mrow> </msubsup> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="normal">P</mi> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mn>3</mn> </mrow> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">o</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">f</mi> <mi mathvariant="normal">f</mi> </mrow> </msubsup> </mrow> </semantics></math> with their significance (lower plots). The highest influence weight of ~ 99.3% is <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> <mi>C</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>, while the next parametric component, <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>P</mi> <mi>C</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>, has ~0.7% influence. The third principal component has an almost negligible influence.</p>
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<p>(<b>a</b>) Temperature dependence of PC<sub>1</sub> with temperature (diamonds) and polynomial fit (red line); (<b>b</b>,<b>c</b>) calculated absolute and relative sensitivities as a function of temperature, respectively; (<b>d</b>) the experimentally determined values of accuracy (ΔT, circles) and precision (δT, diamonds) of the PCA luminescence thermometry method. The maximal absolute sensitivity of the method is ~0.012K<sup>−1</sup> while the relative sensitivity value decreases with temperature, from 0.84%K<sup>−1</sup> at 200 K to 0.25%K<sup>−1</sup> at 473 K. The average values for accuracy and precision are 0.7 K and 0.5 K, respectively.</p>
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26 pages, 9279 KiB  
Article
Fracture Evolution during CO2 Fracturing in Unconventional Formations: A Simulation Study Using the Phase Field Method
by Bing Yang, Qianqian Ren, Hai Huang, Haizhu Wang, Yong Zheng, Liangbin Dou, Yanlong He, Wentong Zhang, Haoyu Chen and Ruihong Qiao
Processes 2024, 12(8), 1682; https://doi.org/10.3390/pr12081682 - 12 Aug 2024
Abstract
With the introduction of China’s “dual carbon” goals, CO2 is increasingly valued as a resource and is being utilized in unconventional oil and gas development. Its application in fracturing operations shows promising prospects, enabling efficient extraction of oil and gas while facilitating [...] Read more.
With the introduction of China’s “dual carbon” goals, CO2 is increasingly valued as a resource and is being utilized in unconventional oil and gas development. Its application in fracturing operations shows promising prospects, enabling efficient extraction of oil and gas while facilitating carbon sequestration. The process of reservoir stimulation using CO2 fracturing is complex, involving coupled phenomena such as temperature variations, fluid behavior, and rock mechanics. Currently, numerous scholars have conducted fracturing experiments to explore the mechanisms of supercritical CO2 (SC-CO2)-induced fractures in relatively deep formations. However, there is relatively limited numerical simulation research on the coupling processes involved in CO2 fracturing. Some simulation studies have simplified reservoir and operational parameters, indicating a need for further exploration into the multi-field coupling mechanisms of CO2 fracturing. In this study, a coupled thermo-hydro-mechanical fracturing model considering the CO2 properties and heat transfer characteristics was developed using the phase field method. The multi-field coupling characteristics of hydraulic fracturing with water and SC-CO2 are compared, and the effects of different geological parameters (such as in situ stress) and engineering parameters (such as the injection rate) on fracturing performance in tight reservoirs were investigated. The simulation results validate the conclusion that CO2, especially in its supercritical state, effectively reduces reservoir breakdown pressures and induces relatively complex fractures compared with water fracturing. During CO2 injection, heat transfer between the fluid and rock creates a thermal transition zone near the wellbore, beyond which the reservoir temperature remains relatively unchanged. Larger temperature differentials between the injected CO2 fluid and the formation result in more complicated fracture patterns due to thermal stress effects. With a CO2 injection, the displacement field of the formation deviated asymmetrically and changed abruptly when the fracture formed. As the in situ stress difference increased, the morphology of the SC-CO2-induced fractures tended to become simpler, and conversely, the fracture presented a complicated distribution. Furthermore, with an increasing injection rate of CO2, the fractures exhibited a greater width and extended over longer distances, which are more conducive to reservoir volumetric enhancement. The findings of this study validate the authenticity of previous experimental results, and it analyzed fracture evolution through the multi-field coupling process of CO2 fracturing, thereby enhancing theoretical understanding and laying a foundational basis for the application of this technology. Full article
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Figure 1
<p>COMSOL implementation of phase field modeling for fracturing problems.</p>
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<p>Schematic of a cracked square plate under a single-edge notched tension test, where <span class="html-italic">L</span> = 1 mm.</p>
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<p>Validation of 2D single-edge notched square subjected to tension. (<b>a</b>) When <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>7.5</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>, the crack extended in a pattern under displacements of <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.6</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.9</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>. (<b>b</b>) When <math display="inline"><semantics> <mrow> <msub> <mi>l</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>1.5</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>, the crack extended in a pattern under displacements of <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.0</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.2</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>=</mo> <mn>5.4</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mi>mm</mi> </mrow> </semantics></math>.</p>
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<p>Load–displacement curves of the 2D single-edge notched tension test.</p>
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<p>Geometric model of CO<sub>2</sub> fracturing.</p>
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<p>The main properties of CO<sub>2</sub>: (<b>a</b>) density, (<b>b</b>) viscosity, (<b>c</b>) heat conductivity, and (<b>d</b>) specific heat capacity changing with temperature and pressure. (<b>a</b>) The density varied with the temperature and pressure. (<b>b</b>) The viscosity distribution of CO<sub>2</sub>. (<b>c</b>) The thermal conductivity distribution of CO<sub>2</sub>. (<b>d</b>) The specific heat capacity of CO<sub>2</sub>.</p>
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<p>Main process of water fracturing on tight reservoir.</p>
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<p>Main process of CO<sub>2</sub> fracturing on tight reservoir.</p>
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<p>The pressure at the top of the wellbore during water and SC-CO<sub>2</sub> fracturing.</p>
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<p>Temperature distribution of formation at different times. (<b>a</b>) Formation temperature distribution during water fracturing. (<b>b</b>) Formation temperature distribution during SC-CO<sub>2</sub> fracturing.</p>
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<p>Contour of displacement in SC-CO<sub>2</sub> fracturing process.</p>
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<p>Contour of displacement in SC-CO<sub>2</sub> fracturing process.</p>
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<p>Displacement changes with time at top of wellbore.</p>
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<p>Variation characteristics of formation porosity during water and SC-CO<sub>2</sub> fracturing.</p>
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<p>Permeability changes with time at top of wellbore.</p>
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<p>Fracture mode induced by SC-CO<sub>2</sub> under different stress conditions ((<b>a</b>) 12/8 MPa; (<b>b</b>) 12/10 MPa; (<b>c</b>) 12/11 MPa; and (<b>d</b>) 12/12 MPa).</p>
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<p>Porosity of formation fractured by SC-CO<sub>2</sub> under different in situ stress values.</p>
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<p>Permeability of formation fractured by SC-CO<sub>2</sub> under different in situ stress values.</p>
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<p>Fracture mode induced by SC-CO<sub>2</sub> under different temperature conditions.</p>
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<p>Porosity of formation fractured by SC-CO<sub>2</sub> under different temperatures.</p>
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<p>Permeability of formation fractured by SC-CO<sub>2</sub> under different temperatures.</p>
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<p>Fracture mode induced by SC-CO<sub>2</sub> under different injection rates.</p>
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<p>Porosity of formation fractured by SC-CO<sub>2</sub> under different injection rates.</p>
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<p>Permeability of formation fractured by SC-CO<sub>2</sub> under different injection rates.</p>
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14 pages, 2693 KiB  
Article
Thermally Active Medium-Density Fiberboard (MDF) with the Addition of Phase Change Materials for Furniture and Interior Design
by Julia Dasiewicz, Anita Wronka, Aleksandra Jeżo and Grzegorz Kowaluk
Materials 2024, 17(16), 4001; https://doi.org/10.3390/ma17164001 (registering DOI) - 12 Aug 2024
Viewed by 72
Abstract
No matter where we reside, the issue of greenhouse gas emissions impacts us all. Their influence has a disastrous effect on the earth’s climate, producing global warming and many other irreversible environmental impacts, even though it is occasionally invisible to the independent eye. [...] Read more.
No matter where we reside, the issue of greenhouse gas emissions impacts us all. Their influence has a disastrous effect on the earth’s climate, producing global warming and many other irreversible environmental impacts, even though it is occasionally invisible to the independent eye. Phase change materials (PCMs) can store and release heat when it is abundant during the day (e.g., from solar radiation), for use at night, or on chilly days when buildings need to be heated. As a consequence, buildings use less energy to heat and cool, which lowers greenhouse gas emissions. Consequently, research on thermally active medium-density fiberboard (MDF) with PCMs is presented in this work. MDF is useful for interior design and furniture manufacturing. The boards were created using pine (Pinus sylvestris L.) and spruce (Picea abies L.) fibers, urea–formaldehyde resin, and PCM powder, with a phase transition temperature of 22 °C, a density of 785 kg m−3, a latent heat capacity of 160 kJ kg−1, a volumetric heat capacity of 126 MJ m−3, a specific heat capacity of 2.2 kJ kgK−1, a thermal conductivity of 0.18 W mK−1, and a maximum operating temperature of 200 °C. Before resination, the wood fibers were divided into two outer layers (16%) and an interior layer (68% by weight). Throughout the resination process, the PCM particles were solely integrated into the inner layer fibers. The mats were created by hand. A hydraulic press (AKE, Mariannelund, Sweden) was used to press the boards, and its operating parameters were 180 °C, 20 s/mm of nominal thickness, and 2.5 MPa for the maximum unit pressing pressure. Five variants of MDF with a PCM additive were developed: 0%, 5%, 10%, 30%, and 50%. According to the study, scores at the MOR, MOE, IB, and screw withdrawal resistance (SWR) tests decreased when PCM content was added, for example, MOE from 3176 to 1057 N mm−2, MOR from 41.2 to 11.5 N mm−2, and IB from 0.78 to 0.27 N mm−2. However, the results of the thickness swelling and water absorption tests indicate that the PCM particles do not exhibit a substantial capacity to absorb water, retaining the dimensional stability of the MDF boards. The thickness swelling positively decreased with the PCM content increase from 15.1 to 7.38% after 24 h of soaking. The panel’s thermal characteristics improved with the increasing PCM concentration, according to the data. The density profiles of all the variations under consideration had a somewhat U-shaped appearance; however, the version with a 50% PCM content had a flatter form and no obvious layer compaction on the panel surface. Therefore, certain mechanical and physical characteristics of the manufactured panels can be enhanced by a well-chosen PCM addition. Full article
(This article belongs to the Special Issue Thermal Stability and Fire Performance of Polymeric Materials)
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Figure 1
<p>Influence of various contents of PCM on the MOR of produced MDF.</p>
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<p>Influence of various contents of PCM on the MOE of produced MDF.</p>
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<p>Water absorption of the MDF produced with the use of various contents of PCM.</p>
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<p>Thickness swelling of the MDF produced with the use of various contents of PCM.</p>
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<p>Thermal properties of MDF produced with different contents of PCM.</p>
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<p>Screw withdrawal resistance of the MDF produced with the use of various contents of PCM.</p>
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<p>Internal bond of the MDF produced with the use of various contents of PCM.</p>
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<p>Density profiles of tested samples.</p>
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25 pages, 859 KiB  
Article
Entanglement and Generalized Berry Geometrical Phases in Quantum Gravity
by Diego J. Cirilo-Lombardo and Norma G. Sanchez
Symmetry 2024, 16(8), 1026; https://doi.org/10.3390/sym16081026 - 12 Aug 2024
Viewed by 143
Abstract
A new formalism is introduced that makes it possible to elucidate the physical and geometric content of quantum space–time. It is based on the Minimum Group Representation Principle (MGRP). Within this framework, new results for entanglement and geometrical/topological phases are found and implemented [...] Read more.
A new formalism is introduced that makes it possible to elucidate the physical and geometric content of quantum space–time. It is based on the Minimum Group Representation Principle (MGRP). Within this framework, new results for entanglement and geometrical/topological phases are found and implemented in cosmological and black hole space–times. Our main results here are as follows: (i) We find the Berry phases for inflation and for the cosmological perturbations and express them in terms of the observables, such as the spectral scalar and tensor indices, nS and nT, and the tensor-to-scalar ratio r. The Berry phase for de Sitter inflation is imaginary with the sign describing the exponential acceleration. (ii) The pure entangled states in the minimum group (metaplectic) Mp(n) representation for quantum de Sitter space–time and black holes are found. (iii) For entanglement, the relation between the Schmidt type representation and the physical states of the Mp(n) group is found: This is a new non-diagonal coherent state representation complementary to the known Sudarshan diagonal one. (iv) Mean value generators of Mp(2) are related to the adiabatic invariant and topological charge of the space–time, (matrix element of the transition <t<). (v) The basic even and odd n-sectors of the Hilbert space are intrinsic to the quantum space–time and its discrete levels (in particular, continuum for n), they do not require any extrinsic generation process such as the standard Schrodinger cat states, and are entangled. (vi) The gravity or cosmological on one side and another of the Planck scale are entangled. Examples: The quantum primordial trans-Planckian de Sitter vacuum and the classical late de Sitter vacuum today; the central quantum gravity region and the external classical gravity region of black holes. The classical and quantum dual gravity regions of the space–time are entangled. (vii) The general classical-quantum gravity duality is associated with the Metaplectic Mp(n) group symmetry which provides the complete full covering of the phase space and of the quantum space–time mapped from it. Full article
(This article belongs to the Section Physics)
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Figure 1

Figure 1
<p>Chiral-antichiral oscillation (zitterbebegung) giving the pattern of cat states from first principles. The asymmetry in the pattern can be seen, marking a preferential temporal evolution.</p>
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<p>3D picture of the chiral-antichiral oscillation (cat states pattern).</p>
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<p>The three images show from top to down the entangled coherent state where the degree of entaglement varies as a function of time from the highest to the lowest degree controlled by the overlap <math display="inline"><semantics> <mfenced separators="" open="&#x2329;" close="&#x232A;"> <mi>α</mi> <mspace width="0.166667em"/> <mo>|</mo> <mspace width="0.166667em"/> <mi>β</mi> </mfenced> </semantics></math>. Here <math display="inline"><semantics> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </semantics></math> correspond to <math display="inline"><semantics> <mrow> <mo form="prefix">Re</mo> <mspace width="0.166667em"/> <mover accent="true"> <mi>α</mi> <mo>˜</mo> </mover> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mo form="prefix">Im</mo> <mspace width="0.166667em"/> <mover accent="true"> <mi>α</mi> <mo>˜</mo> </mover> </mrow> </semantics></math>.</p>
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21 pages, 3727 KiB  
Article
Al-Si Order and Chemical Composition Model across Scapolite Solid Solutions with Evidence from Rietveld Structure Refinements
by Sytle M. Antao
Minerals 2024, 14(8), 812; https://doi.org/10.3390/min14080812 (registering DOI) - 11 Aug 2024
Viewed by 227
Abstract
Scapolite forms solid solutions between the end members marialite, Na4[Al3Si9O24]Cl = Me0, and meionite, Ca4[Al6Si6O24]CO3 = Me100. Al-Si order and chemical composition [...] Read more.
Scapolite forms solid solutions between the end members marialite, Na4[Al3Si9O24]Cl = Me0, and meionite, Ca4[Al6Si6O24]CO3 = Me100. Al-Si order and chemical composition models are proposed for the scapolite solid solutions. These models predict the chemical composition, Al-Si order, and average <T–O> distances between Me0–Me100. These models are based on the observed order of clusters and on two solid solutions that meet at Me75 coupled with predicted chemical compositions and <T–O> distances. The [Na4·Cl]3+ and [NaCa3·CO3]5+ clusters are ordered between Me0–Me75, whereas the clusters [NaCa3·CO3]5+ and [Ca4·CO3]6+ are disordered from Me75–Me100. To confirm the structural model, the crystal structure of 27 scapolite samples between Me6–Me93 has been obtained using synchrotron high-resolution powder X-ray diffraction (HRPXRD) data and Rietveld structure refinements. The structure was refined in space group P42/n for all the samples. The <T–O> distances indicate that the T1 (=Si), T2 (=Al), and T3 (=Si) sites are completely ordered at Me37.5, where the 1:1 ratio of [Na4·Cl]3+:[NaCa3·CO3]5+ clusters are ordered and gives rise to antiphase domain boundaries (APBs) based on Cl-CO3 order instead of Al-Si order. The presence of APBs based on Cl-CO3 order and cluster order indicate that neither space group P42/n nor I4/m are correct for the structure of scapolite, but the lower symmetry space group P42/n is a good approximation for modeling the average structure of scapolite. The complete Al-Si order at Me37.5 changes in a regular and predictable manner toward the end members: Me0, Me75, and Me100. The observed unit cell and several structural parameters show a discontinuity at Me75, where the series is divided into two. There is no structural evidence to support any phase transition in the scapolite series. The T1 site contains only Si from Me0–Me37.5; from Me37.5–Me100, Al atoms enter the T1 site and the <T1–O> distance increases linearly to Me100. Full article
(This article belongs to the Special Issue Crystal Structure, Mineralogy, and Geochemistry of Scapolite)
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Figure 1

Figure 1
<p>(<b>a</b>) Scapolite structure projected down the <b><span class="html-italic">c</span></b> axis showing the framework T and interstitial M and A sites, as well as the four-membered rings and oval-shaped channels for space group <span class="html-italic">P</span>4<sub>2</sub>/<span class="html-italic">n</span>. The scapolite structure in the higher symmetry space group <span class="html-italic">I</span>4/<span class="html-italic">m</span> has the same topology with T2′ = T2 + T3. (<b>b</b>) Part of the structure of scapolite in space group <span class="html-italic">P</span>4<sub>2</sub>/<span class="html-italic">n</span> showing a central cage containing A and M sites; the A anion is coordinated by four M cations in a square-planar configuration. Uncommon five-membered rings are shown.</p>
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<p>A model for Al-Si order across scapolite solid solutions based on average tetrahedral distances: T1 = &lt;T1–O&gt;, T2 = &lt;T2–O&gt;, T3 = &lt;T3–O&gt;, &lt;T2,3–O&gt; = (&lt;T2–O&gt; + &lt;T3–O&gt;)/2, and mean &lt;T–O&gt; = (&lt;T1–O&gt; + &lt;T2–O&gt; + &lt;T3–O&gt;)/3. The &lt;T–O&gt; distances with Me%, Si <span class="html-italic">apfu</span>, and T site occupancies [=Al/(Al + Si)]] are given (<a href="#minerals-14-00812-t001" class="html-table">Table 1</a>). The thick black line is based on data points at Me<sub>37.5</sub> and Me<sub>56.25</sub> (open circles). The experimental mean &lt;T–O&gt; distances (solid squares from this study) are fitted by the thin black straight line (R<sup>2</sup> = 0.9124). At Me<sub>37.5</sub>, a maximum occurs for Al-Si order, cluster order, and intensity of type-b reflections.</p>
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<p>HRPXRD trace for a typical scapolite sample-14 from Fishtail Lake, Ontario (Me<sub>40.1</sub>) at room <span class="html-italic">T</span>, together with the calculated (continuous line) and observed (crosses) profiles. The difference curve (<span class="html-italic">I<sub>obs</sub></span>–<span class="html-italic">I<sub>calc</sub></span>) is shown at the bottom. The short vertical lines indicate allowed reflection positions. The (021) reflection is indicated and shown in the insert. All the data beyond 10 and 20° are multiplied by 5 and 30, respectively.</p>
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<p>Variation of normalized unit-cell parameters (<span class="html-italic">V</span>/<span class="html-italic">V</span><sub>0</sub>, solid squares; <span class="html-italic">a</span>/<span class="html-italic">a</span><sub>0</sub>, solid triangles; <span class="html-italic">c</span>/<span class="html-italic">c</span><sub>0</sub>, solid circles) with (<b>a</b>) volume, <span class="html-italic">V</span>; (<b>b</b>) Me<span class="html-italic">%</span>; (<b>c</b>) Al <span class="html-italic">apfu</span>; and (<b>d</b>) mean &lt;T–O&gt; distance. Lines shown are least-squares fits to the data from this study (solid symbols). Dashed vertical lines are drawn where a discontinuity occurs for the <span class="html-italic">c</span>/<span class="html-italic">c</span><sub>0</sub> ratio, but the <span class="html-italic">a</span>/<span class="html-italic">a</span><sub>0</sub> and <span class="html-italic">V</span>/<span class="html-italic">V</span><sub>0</sub> ratios increase linearly. The Al-Si atoms are partially responsible for the increase in <span class="html-italic">a</span>/<span class="html-italic">a</span><sub>0</sub> and <span class="html-italic">V</span>/<span class="html-italic">V</span><sub>0</sub> as Al replaces Si atoms in going from Me<sub>0</sub> to Me<sub>100</sub>. Al-Si order is responsible for the variation in the <span class="html-italic">c</span>/<span class="html-italic">c</span><sub>0</sub> ratio that has a maximum value at Me<sub>37.5</sub> and a minimum value at Me<sub>75</sub> in (<b>b</b>). The change in <span class="html-italic">c</span> parameter is small compared to that for <span class="html-italic">a</span> and <span class="html-italic">V</span>. Discontinuities occur at 5 Al <span class="html-italic">apfu</span> in (<b>c</b>) and mean &lt;T–O&gt; distance in (<b>d</b>). Data from reference [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are displayed.</p>
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<p>Variation in unit-cell parameters with mean &lt;T–O&gt; distances across the scapolite series: (<b>a</b>) <span class="html-italic">a</span> parameter; (<b>b</b>) <span class="html-italic">c</span> parameter; (<b>c</b>) volume, <span class="html-italic">V</span>. Lines shown are fitted to the data from this study (solid symbols). A dashed line is drawn where a discontinuity occurs for the <span class="html-italic">c</span> parameter in (<b>b</b>), but <span class="html-italic">a</span> and <span class="html-italic">V</span> increase non-linearly (R<sup>2</sup> = 0.9224 in (<b>a</b>) and R<sup>2</sup> = 0.9301 in (<b>c</b>)). Al-Si order is responsible for the variation in <span class="html-italic">c</span> parameter that has a maximum value at Me<sub>37.5</sub> in (<b>b</b>) where complete Al-Si order occurs in the scapolite series. Data from reference [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are displayed.</p>
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<p>Average &lt;M–O&gt;[7] and M–A distances as a function of V (<b>a</b>,<b>d</b>); Me% (<b>b</b>,<b>e</b>); and Al <span class="html-italic">apfu</span> (<b>c</b>,<b>f</b>). Solid lines are least-squares fits to the data from this study. A dashed line is drawn at V = 1120 Å<sup>3</sup> (<b>a</b>,<b>d</b>), Me<sub>75</sub> (<b>b</b>,<b>e</b>), and 5 Al <span class="html-italic">apfu</span> (<b>c</b>,<b>f</b>) where discontinuities are observed. The &lt;M–O&gt;[7] distances decrease from Me<sub>0</sub> to Me<sub>100</sub> because of the replacement of Na by Ca atoms, whereas the M–A distances increase because of the replacement of Cl by CO<sub>3</sub> groups. Data from reference [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are displayed.</p>
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<p>Average of six tetrahedral bridging angles, &lt;T–O–T&gt;, as a function of (<b>a</b>) <span class="html-italic">V</span>; (<b>b</b>) Me%; and (<b>c</b>) Al <span class="html-italic">apfu</span>. Solid lines are least-squares fits to the data from this study. Average &lt;T–O–T&gt; angle decreases from Me<sub>0</sub> to Me<sub>100</sub> because of the replacement of Na by Ca atoms, which causes the TO<sub>4</sub> tetrahedra to rotate. Data from reference [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are displayed.</p>
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<p>Average tetrahedral distances, &lt;T–O&gt;, as a function of (<b>a</b>) <span class="html-italic">V</span>; (<b>b</b>) Me%; and (<b>c</b>) Al <span class="html-italic">apfu</span>. Solid lines are least-squares fits to the data from this study (solid symbols). The mean &lt;T–O&gt; distance [mean T = (&lt;T1–O&gt; + &lt;T2–O&gt; + &lt;T3–O&gt;)/3] increases linearly from Me<sub>0</sub> to Me<sub>100</sub> in (<b>b</b>). The average &lt;T1–O&gt; distance increases slightly from Me<sub>0</sub> to Me<sub>37.5</sub> in (<b>b</b>), or 3 to 4 Al <span class="html-italic">apfu</span> in (<b>c</b>) even though the T1 site contains only Si atoms in this range. From Me<sub>37.5</sub> to Me<sub>100</sub> in (<b>b</b>), or 4 to 6 Al <span class="html-italic">apfu</span> in (<b>c</b>), the average &lt;T1–O&gt; distance increases linearly as Al atoms begin to enter the T1 site. The average &lt;T2,3–O&gt; distance also increases slightly from Me<sub>0</sub> to Me<sub>37.5</sub>, or 3 to 4 Al <span class="html-italic">apfu</span>, and thereafter it levels off [&lt;T2,3–O&gt; = (&lt;T2–O&gt; + &lt;T3–O&gt;)/2]. Predicted mean &lt;T–O&gt; distances are shown as dashed lines in (<b>b</b>,<b>c</b>). Data from reference [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are displayed.</p>
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<p>Average tetrahedral distances for the T sites with Me%, Si <span class="html-italic">apfu</span>, and Al/(Al + Si). The data from this study are shown in magenta (T1 = &lt;T1–O&gt;), red (T2 = &lt;T2–O&gt;), blue (T3 = &lt;T3–O&gt;), and green (&lt;T2,3–O&gt; = (&lt;T2–O&gt; + &lt;T3–O&gt;)/2) symbols. Data from Sokolova and Hawthorne [<a href="#B27-minerals-14-00812" class="html-bibr">27</a>] are shown in black symbols. All data are placed on the graph and are not fitted. The average &lt;T–O&gt; distances from this study match the model quite well. Samples near Me<sub>37.5</sub> have complete Al-Si order. At Me<sub>0</sub>, &lt;T1–O&gt; = 1.6100 and &lt;T2,3–O&gt; = 1.6601 Å. At Me<sub>100</sub>, &lt;T1–O&gt; = 1.6667 and &lt;T2,3–O&gt; = 1.6834 Å.</p>
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<p>Expansion of the scapolite structure with Me% and temperature (<span class="html-italic">T</span>). Double-headed black arrow indicates opening of the oval-shaped channels that arise from rotation of the TO<sub>4</sub> tetrahedra “out” as indicated by the black arrow heads in the four-membered rings because of thermal expansion. The red arrows correspond to closing of the channels with increasing Me% by rotation of the TO<sub>4</sub> tetrahedra “in” as indicated by the red arrow heads in the four-membered rings. These openings/closings are caused by expansion or contraction of the &lt;M–O&gt; and M–A distances and give rise to a more open/closed framework structure with <span class="html-italic">T</span> or Me%.</p>
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<p>Linear variation of channel width/length ratio (short axis Oc–Od/long axis Oa–Ob in <a href="#minerals-14-00812-f010" class="html-fig">Figure 10</a>) with Me%. The solid line is a least-squares fit to the data from this study (R<sup>2</sup> = 0.8161).</p>
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15 pages, 2988 KiB  
Article
The Effect of Component Defects on the Performance of Perovskite Devices and the Low-Cost Preparation of High-Purity PbI2
by Boyu Dong, Yuhan Xie and Yongbing Lou
Molecules 2024, 29(16), 3810; https://doi.org/10.3390/molecules29163810 (registering DOI) - 11 Aug 2024
Viewed by 213
Abstract
The efficiency and reproducibility of perovskite solar cells (PSCs) are significantly influenced by the purity of lead iodide (PbI2) in the raw materials used. Pb(OH)I has been identified as the primary impurity generated from PbI2 in water-based synthesis. Consequently, a [...] Read more.
The efficiency and reproducibility of perovskite solar cells (PSCs) are significantly influenced by the purity of lead iodide (PbI2) in the raw materials used. Pb(OH)I has been identified as the primary impurity generated from PbI2 in water-based synthesis. Consequently, a comprehensive investigation into the impact of Pb(OH)I impurities on film and device performance is essential. In this study, PbI2, with varying stoichiometries, was synthesized to examine the effects of different Pb(OH)I levels on perovskite device performance. The characterization results revealed that even trace amounts of Pb(OH)I impede the formation of precursor prenucleation clusters. These impurities also increase the energy barrier of the α-phase and facilitate the transition of the intermediate phase to the δ-phase. These effects result in poor perovskite film morphology and sub-optimal photovoltaic device performance. To address these issues, a cost-effective method for preparing high-stoichiometry PbI2 was developed. The formation of Pb(OH)I was effectively inhibited through several strategies: adjusting solution pH and temperature, modifying material addition order, simplifying the precipitation–recrystallization process, and introducing H3PO2 as an additive. These modifications enabled the one-step synthesis of high-purity PbI2. PSCs prepared using this newly synthesized high-stoichiometry PbI2 demonstrated photovoltaic performance comparable to those fabricated with commercial PbI2 (purity ≥ 99.999%). Our novel method offers a cost-effective alternative for synthesizing high-stoichiometry PbI2, thereby providing a viable option for the production of high-performance PSCs. Full article
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<p>(<b>a</b>) The stoichiometry of different PbI<sub>2</sub> samples; (<b>b</b>) XRD patterns of commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; SEM images (<b>c</b>–<b>f</b>) of commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; (<b>c</b>) commercial PbI<sub>2</sub>; (<b>d</b>) PbI<sub>1.956</sub>; (<b>e</b>) PbI<sub>1.932</sub>; (<b>f</b>) PbI<sub>1.880</sub>. The red circle indicates the needle-shaped crystal structure Pb(OH)I.</p>
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<p>(<b>a</b>) XRD patterns of perovskite thin films prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; (<b>b</b>) ultraviolet absorption spectra of perovskite thin films prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; SEM images (<b>c</b>–<b>f</b>) of perovskite thin films prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; (<b>c</b>) commercial PbI<sub>2</sub>; (<b>d</b>) PbI<sub>1.956</sub>; (<b>e</b>) PbI<sub>1.932</sub>; (<b>f</b>) PbI<sub>1.880</sub>. Unreacted PbI<sub>2</sub> marked in red circle.</p>
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<p>(<b>a</b>) DLS spectra of commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub> in DMF solution; (<b>b</b>) DLS spectra of perovskite precursor solution prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>.</p>
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<p>(<b>a</b>) PL spectra of perovskite thin films prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>; (<b>b</b>) TRPL spectra of perovskite thin films prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>.</p>
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<p>Box plots of perovskite devices: (<b>a</b>) PCE; (<b>b</b>) <span class="html-italic">Jsc</span>; (<b>c</b>) FF; (<b>d</b>) <span class="html-italic">Voc</span> prepared from commercial PbI<sub>2</sub> and different stoichiometric PbI<sub>2</sub>. The structure was FTO/C−TiO<sub>2</sub>−SnO<sub>2</sub>/FA<sub>0.95</sub>Cs<sub>0.05</sub>PbI<sub>3</sub>/Spiro−MeOTAD/Ag.</p>
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<p>SEM images (<b>a</b>,<b>b</b>) of PbI<sub>2</sub>: (<b>a</b>) commercial PbI<sub>2</sub>; (<b>b</b>) PbI<sub>1.995</sub>. (<b>c</b>) XRD patterns of commercial PbI<sub>2</sub> and PbI<sub>1.995</sub>.</p>
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<p>SEM images of perovskite films prepared from (<b>a</b>) commercial PbI<sub>2</sub> and (<b>b</b>) PbI<sub>1.995</sub>; (<b>c</b>) ultraviolet absorption spectra of perovskite thin films; (<b>d</b>) XRD patterns of perovskite thin films; (<b>e</b>) PL spectra of perovskite thin films; (<b>f</b>) TRPL spectra of perovskite thin films. Unreacted PbI<sub>2</sub> is marked in red circles and the peak indicated by the asterisk is the characteristic peak of PbI<sub>2</sub> impurity.</p>
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<p>Box plots of perovskite devices: (<b>a</b>) PCE; (<b>b</b>) <span class="html-italic">Jsc</span>; (<b>c</b>) FF; (<b>d</b>) <span class="html-italic">Voc</span> prepared from commercial PbI<sub>2</sub> and PbI<sub>1.995</sub>. The structure was FTO/C−TiO<sub>2</sub>−SnO<sub>2</sub>/FA<sub>0.95</sub>Cs<sub>0.05</sub>PbI<sub>3</sub>/Spiro−MeOTAD/Ag.</p>
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19 pages, 9078 KiB  
Article
Influence of Gamma-Phase Aluminum Oxide Nanopowder and Polyester–Glass Recyclate Filler on the Destruction Process of Composite Materials Reinforced by Glass Fiber
by Katarzyna Panasiuk, Krzysztof Dudzik, Grzegorz Hajdukiewicz and Norbert Abramczyk
Polymers 2024, 16(16), 2276; https://doi.org/10.3390/polym16162276 (registering DOI) - 10 Aug 2024
Viewed by 408
Abstract
Recycling of composite materials is an important global issue due to the wide use of these materials in many industries. Waste management options are being explored. Mechanical recycling is one of the methods that allows obtaining polyester–glass recyclate in powder form as a [...] Read more.
Recycling of composite materials is an important global issue due to the wide use of these materials in many industries. Waste management options are being explored. Mechanical recycling is one of the methods that allows obtaining polyester–glass recyclate in powder form as a result of appropriate crushing and grinding of waste. Due to the fact that the properties of composites can be easily modified by adding various types of fillers and nanofillers, this is one of the ways to improve the properties of such complex composite materials. This article presents the strength parameters of composites with the addition of fillers in the form of polyester–glass recyclate and a nanofiller in the form of gamma-phase aluminum nanopowder. To analyze the obtained results, Kolmogorov-Sinai (K-S) metric entropy was used to determine the transition from the elastic to the viscoelastic state in materials without and with the addition of nanoaluminum, during a static tensile test. The tests included samples with the addition of fillers and nanofillers, as well as a base sample without any additives. The article presents the strength parameters obtained from a testing machine during a static tensile test. Additionally, the acoustic emission method was used during the research. Thanks to which, graphs of the effective value of the electrical signal (RMS) were prepared as a function of time, the parameters were previously identified as extremely useful for analyzing the destruction process of composite materials. The values obtained from the K-S metric entropy method and the acoustic emission method were plotted on sample stretching graphs. The influence of the nanofiller and filler on these parameters was also analyzed. The presented results showed that the aluminum nanoadditive did not increase the strength parameters of the composite with recyclate as a result of the addition of aluminum nanofiller; however, its addition influenced the operational parameters, which is reflected in a 5% increase in the UTS value (from 55% to 60%). Full article
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<p>Samples prepared for static tensile test: (<b>a</b>) geometric parameters, (<b>b</b>) ready for static tensile test.</p>
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<p>Example sample screenshot from the AE data software.</p>
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<p>Measuring station: 1—computer with test expert II software Version 3.3, 2—computer with AE Win for USB software Version E5.30, 3—Zwick Roell testing machine.</p>
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<p>Diagram of measuring station [<a href="#B11-polymers-16-02276" class="html-bibr">11</a>,<a href="#B44-polymers-16-02276" class="html-bibr">44</a>].</p>
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<p>Sample undergoing testing: 1—extensometer, 2—AE sensor.</p>
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<p>Graph of deformation depending on measurement points.</p>
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<p>A fragment of the sample tensile curve containing one 60—digit interval of successively recorded elongation values ε and 6 marked sub-intervals of this interval.</p>
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<p>Observation of the surface using SEM for the sample: (<b>a</b>) A0R0, (<b>b</b>) A0R10.</p>
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<p>Examples of stress–strain curves for three tested materials.</p>
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<p>(<b>a</b>) K-S metric entropy as a function of time plotted on the stress–strain curves, (<b>b</b>) effective value of the electrical signal (RMS) as a function of time plotted on the stress–strain curve for an exemplary sample without the addition of recyclate (A0R0), (<b>c</b>) magnification of the first decrease in the entropy value, (<b>d</b>) magnification of the first increase in RMS [V].</p>
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<p>Change in the amplitude and frequency of the acoustic emission signal as a function of time for an exemplary sample made of a composite without additives (A0R0).</p>
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<p>Change in acoustic emission signal power as a function of frequency for an exemplary sample made of a composite without additives (A0R0): (<b>a</b>) total spectrum, (<b>b</b>) enlargement of the selected area.</p>
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<p>(<b>a</b>) K-S metric entropy as a function of time plotted on the stress–strain curve, (<b>b</b>) effective value of the electrical signal (RMS) as a function of time plotted on the stress–strain curve for an exemplary sample with 10% recyclate content (A0R10), (<b>c</b>) magnification of the first decrease in the entropy value, (<b>d</b>) magnification of the first increase of RMS [V].</p>
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<p>Change in the amplitude and frequency of the acoustic emission signal as a function of time for an exemplary sample made of a composite with 10% of recyclate (A0R10).</p>
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<p>Change in acoustic emission signal power as a function of frequency for an exemplary sample made of a composite with 10% of recyclate (A0R10): (<b>a</b>) total spectrum, (<b>b</b>) enlargement of the marked area.</p>
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<p>(<b>a</b>) K-S metric entropy as a function of time plotted on the stress–strain curve, (<b>b</b>) effective value of the electrical signal (RMS) as a function of time plotted on the stress–strain curve for an exemplary sample with 10% recyclate and 2% recyclate-nanopowder (A2R10), (<b>c</b>) magnification of the first decrease in the entropy value, (<b>d</b>) magnification of the first increase in RMS [V].</p>
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<p>Change in the amplitude and frequency of the acoustic emission signal as a function of time for an exemplary sample made of a composite with 10% recyclate and 2% nanopowder (A2R10).</p>
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<p>Change in acoustic emission signal power as a function of frequency for an exemplary composite sample with 10% recyclate and 2% nano-powder (A2R10): (<b>a</b>) total spectrum, (<b>b</b>) enlargement of the marked area.</p>
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<p>Plot of deformation as a function of time ε (t), with plotted values obtained by applying K-S metric entropy and acoustic emission (RMS).</p>
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<p>Stress versus strain σ (ε) with plotted values obtained by applying K-S metric entropy and acoustic emission (RMS).</p>
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17 pages, 13049 KiB  
Article
Effect of Trace Elements on the Thermal Stability and Electrical Conductivity of Pure Copper
by Haitao Liu, Jincan Dong, Shijun Liang, Weiqiang Li and Yong Liu
Coatings 2024, 14(8), 1017; https://doi.org/10.3390/coatings14081017 - 10 Aug 2024
Viewed by 246
Abstract
Abstract: The impact of introducing trace transition elements on the thermal stability and conductivity of pure copper was examined through metallographic microscopy (OM), transmission electron microscopy (TEM), and electrical conductivity measurements; the interaction between trace transition element and trace impurity element S in [...] Read more.
Abstract: The impact of introducing trace transition elements on the thermal stability and conductivity of pure copper was examined through metallographic microscopy (OM), transmission electron microscopy (TEM), and electrical conductivity measurements; the interaction between trace transition element and trace impurity element S in the matrix was analyzed. The results show that the addition of trace Ti and trace Cr, Ni, and Ag elements significantly enhances the thermal stability of the pure copper grain size. After high-temperature treatment at 900 °C/30 min, the grain sizes of Cu, Cu-Ti-S, and Cu-Cr-Ni-Ag-S were measured and found to be 200.24 μm, 83.83 μm, and 31.08 μm, respectively, thus establishing a thermal stability ranking of Cu-Cr-Ni-Ag-S > Cu-Ti-S > Cu. Furthermore, the conductivities of pure copper remain high even after the addition of trace transition elements, with recorded values for Cu, Cu-Ti-S, and Cu-Cr-Ni-Ag-S of 100.7% IACS, 100.2% IACS, and 98.5% IACS, respectively. The enhancement of thermal stability is primarily attributed to the pinning effect of the TiS and CrS phases, as well as the solid solution dragging of Ni and Ag elements. Trace Ti and Cr elements can react with S impurities to form a hexagonal-structure TiS phase and monoclinic-structure CrS phase, which are non-coherent with the matrix. Notably, the CrS phase is smaller than the TiS phase. In addition, the precipitation of these compounds also reduces the scattering of free electrons by solute atoms, thereby minimizing their impact on the alloy’s conductivity. Full article
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<p>Experimental process.</p>
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<p>Effect of trace elements on the cold-rolled conductivity of 4N pure copper.</p>
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<p>Effect of trace transition group elements on the conductivity of pure copper at different temperatures.</p>
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<p>Optical micrographs of pure copper with trace element 4N added in a cold-rolled state: (<b>a</b>) optical micrograph of 4Ncu; (<b>b</b>) 4N Cu-Ti-S optical micrograph; and (<b>c</b>) 4N Cu-Cr-Ni-Ag-S optical micrograph.</p>
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<p>Optical micrograph and average grain size of 4N pure copper with different trace elements added after high-temperature treatment in a cold-rolled state: (<b>a</b>) 4Ncu optical micrograph; (<b>b</b>) 4N Cu-Ti-S optical micrographs; (<b>c</b>) 4N Cu-Cr-Ni-Ag-S optical micrograph; and (<b>d</b>) average grain size.</p>
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<p>Recrystallization temperature curves of 4N pure copper with different trace elements added.</p>
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<p>Optical micrographs of 4N Cu pure copper at different annealing temperatures: (<b>a</b>) optical micrograph at 30 °C/1 h; (<b>b</b>) optical micrograph at 160 °C/1 h; (<b>c</b>) optical micrograph at 190 °C/1 h; and (<b>d</b>) optical micrograph at 280 °C/1 h.</p>
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<p>Optical micrographs of 4Ncu-Ti-S at different annealing temperatures: (<b>a</b>) optical micrograph at 30 °C/1 h; (<b>b</b>) optical micrograph at 160 °C/1 h; (<b>c</b>) optical micrograph at 190 °C/1 h; and (<b>d</b>) optical micrograph at 280 °C/1 h.</p>
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<p>Optical micrographs of 4Ncu-Cr-Ni-Ag-S at different annealing temperatures: (<b>a</b>) optical micrograph at 30 °C/1 h; (<b>b</b>) optical micrograph at 160 °C/1 h; (<b>c</b>) optical micrograph at 190 °C/1 h; and (<b>d</b>) optical micrograph at 280 °C/1 h.</p>
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<p>Dislocation and precipitated phase analysis of cold-rolled-state 4N Cu-Ti-S: (<b>a</b>) dislocation wall; (<b>b</b>) dislocation cells; (<b>c</b>) HAADF-STEM images at the grain boundary; and (<b>d</b>) HAADF-STEM images within the grains.</p>
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<p>Precipitated phase analysis of cold-rolled 4N Cu-Ti-S at the grain boundary: (<b>a</b>) BF-TEM image; (<b>b</b>) EDS surface scan of titanium; (<b>c</b>) EDS surface scan of sulfur elements; (<b>d</b>) EDS spot scanning of precipitated phase; (<b>e</b>) SAD image of precipitated phase; and (<b>f</b>) TEM high-resolution morphology of the interface between the TiS phase and Cu matrix.</p>
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<p>Precipitated phase analysis of cold-rolled 4N Cu-Ti-S within the grain boundary: (<b>a</b>) BF-TEM image; (<b>b</b>) EDS surface scan of titanium; (<b>c</b>) EDS surface scan of sulfur elements; (<b>d</b>) EDS spot scanning of precipitated phase; (<b>e</b>) SAD image of precipitated phase; and (<b>f</b>) TEM high-resolution morphology of the interface between the TiS phase and Cu matrix.</p>
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<p>Dislocation and precipitated phase analysis of cold-rolled-state 4N Cu-Cr-Ni-Ag-S: (<b>a</b>) dislocation wall; (<b>b</b>) dislocation cells; (<b>c</b>) HAADF-STEM images at the grain boundary; and (<b>d</b>) HAADF-STEM images within the grain boundary.</p>
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<p>Precipitated phase analysis of cold-rolled 4N Cu-Cr-Ni-Ag-S at the grain boundary: (<b>a</b>) BF-TEM image; (<b>b</b>) EDS surface scan of copper elements; (<b>c</b>) EDS surface scan of chromium elements; (<b>d</b>) EDS surface scan of nickel elements; (<b>e</b>) EDS surface scan of silver elements; (<b>f</b>) EDS surface scan of sulfur elements; (<b>g</b>) EDS spot scanning of precipitated phase; (<b>h</b>) SAD image of precipitated phase; and (<b>i</b>) TEM high-resolution morphology of the interface between the CrS phase and Cu matrix.</p>
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<p>Precipitated phase analysis of cold-rolled 4N Cu-Cr-Ni-Ag-S within the grain boundary: (<b>a</b>) BF-TEM image; (<b>b</b>) EDS surface scan of copper elements; (<b>c</b>) EDS surface scan of chromium elements; (<b>d</b>) EDS surface scan of nickel elements; (<b>e</b>) EDS surface scan of silver elements; (<b>f</b>) EDS surface scan of sulfur elements; (<b>g</b>) EDS spot scanning of precipitated phase; (<b>h</b>) SAD image of precipitated phase; and (<b>i</b>) TEM high-resolution morphology of the interface between the CrS phase and Cu matrix.</p>
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<p>Schematic diagram of the mechanism of action of trace alloying elements on the thermal stability of pure copper.</p>
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22 pages, 21234 KiB  
Article
Real-Time Milling Chatter Detection and Control with Axis Encoder Feedback and Spindle Speed Manipulation
by Hakan Çalışkan
J. Manuf. Mater. Process. 2024, 8(4), 173; https://doi.org/10.3390/jmmp8040173 - 10 Aug 2024
Viewed by 236
Abstract
This paper introduces a complete real-time algorithm, where the chatter is detected and eliminated by spindle speed manipulation via the chatter energy feedback calculated from the axis encoder measurement. The proposed method does not require profound knowledge of the machining dynamics; instead, the [...] Read more.
This paper introduces a complete real-time algorithm, where the chatter is detected and eliminated by spindle speed manipulation via the chatter energy feedback calculated from the axis encoder measurement. The proposed method does not require profound knowledge of the machining dynamics; instead, the entire algorithm exploits the fact that milling vibrations consist of forced vibrations at spindle speed harmonics and chatter vibrations that are close to one of the natural modes, with sidebands which are spread at the multiples of spindle speed frequency above and below the chatter frequency. The developed algorithm is able to identify the amplitude, phase and frequency of all the harmonics constituting the periodic forced and chatter vibrations. The key challenge is to select dominant chatter frequencies for the calculation of a robust and accurate chatter energy ratio feedback; this is achieved by utilizing the frequency estimation variance of EKF as a novel chatter indicator. Based on the chatter energy ratio feedback, the controller overrides the spindle speed in order to suppress the chatter energy below a particular threshold value. The varying spindle speed challenge is handled by updating the state transition matrices of the Kalman filters and real-time calculation of the band-pass filter coefficients, based on the derived discrete time transfer functions. The developed algorithm is tested on a Deckel FP5cc CNC which is in-house retrofitted and has a PC-based controller for the real-time application of the proposed algorithm. It is shown that the real-time chatter frequency and amplitude estimates are compatible with off-line FFT analysis, and chatter can be successfully eliminated by energy feedback. Full article
(This article belongs to the Special Issue Dynamics and Machining Stability for Flexible Systems)
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<p>The schematic of the proposed algorithm.</p>
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<p>Block diagram representation of the real–time implementation of a single BPF.</p>
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<p>The finite state machine for the application of automatic chatter control algorithm.</p>
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<p>The in-house retrofitted Deckel FP5cc/T CNC; a PC-based controller with TwinCAT software allows the implementation of ACC algorithm together with the CNC-related motion control tasks.</p>
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<p>The chatter frequency analysis by offline FFT analysis. (<b>a</b>) FFT of 6.3 to 6.4 s; (<b>b</b>) FFT of 6.4 to 6.5 s.</p>
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<p>The frequency and amplitude estimation performance of EKF. (<b>a</b>) Chatter frequency estimate; (<b>b</b>) detailed view; (<b>c</b>) amplitude estimates; (<b>d</b>) detailed view.</p>
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<p>Chatter energy calculation with different methods. (<b>a</b>) Chatter energy; (<b>b</b>) the frequency estimation variance of EKF.</p>
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<p>Full slot tests; first the ACC is off, then ACC is on, 3500 rpm, 1000 mm/min, AL7075 workpiece, <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math>20 mm 3 insert toll, 0.3 mm depth of cut. (<b>a</b>) Tool–workpiece; (<b>b</b>) Y–axis positions; (<b>c</b>) chatter energy: ACC enabled vs. disabled; (<b>d</b>) the spindle speed manipulation and ER response.</p>
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<p>Performance of ACC with varying depth of cut. (<b>a</b>) Tool path of varying radial depth of cut; (<b>b</b>) tool–workpiece; (<b>c</b>) Y–axis position; (<b>d</b>) ACC off chatter energy ratio; (<b>e</b>) ACC on chatter energy ratio; (<b>f</b>) EKF chatter frequency estimate; (<b>g</b>) EKF chatter frequency estimate.</p>
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17 pages, 1811 KiB  
Article
Thermodynamic Exercises for the Kinetically Controlled Hydrogenation of Carvone
by Artemiy A. Samarov, Sergey V. Vostrikov, Aleksandr P. Glotov and Sergey P. Verevkin
Chemistry 2024, 6(4), 706-722; https://doi.org/10.3390/chemistry6040042 (registering DOI) - 10 Aug 2024
Viewed by 131
Abstract
Carvone belongs to the chemical family of terpenoids and is the main component of various plant oils. Carvone and its hydrogenated products are used in the flavouring and food industries. A quantitative thermodynamic analysis of the general network of carvone hydrogenation reactions was [...] Read more.
Carvone belongs to the chemical family of terpenoids and is the main component of various plant oils. Carvone and its hydrogenated products are used in the flavouring and food industries. A quantitative thermodynamic analysis of the general network of carvone hydrogenation reactions was performed based on the thermochemical properties of the starting carvone and all possible intermediates and end products. The enthalpies of vaporisation, enthalpies of formation, entropies and heat capacities of the reactants were determined by complementary measurements and a combination of empirical, theoretical and quantum chemical methods. The energetics and entropy change in the hydrogenation and isomerisation reactions that take place during the conversion of carvone were derived, and the Gibbs energies of the reactions were estimated. It was shown that negative Gibbs energies are recorded for all reactions that may occur during the hydrogenation of carvone, although these differ significantly in magnitude. This means that all these reactions are thermodynamically feasible in a wide range from ambient temperature to elevated temperatures. Therefore, all these reactions definitely take place under kinetic and not thermodynamic control. Nevertheless, the numerical Gibbs energy values can help to establish the chemoselectivity of catalysts used to convert carvone to either carvacarol or to dihydro- and terahydrocarvone, either in carvotanacetone or carveol. Full article
(This article belongs to the Section Theoretical and Computational Chemistry)
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Graphical abstract

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<p>General network of carvone hydrogenation reactions.</p>
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<p>Cis-trans isomerisation of the carvone derivatives as a concomitant of carvone hydrogenation reactions.</p>
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<p>Structures of the most stable conformers of carvone (CAS 99-49-0) as calculated using the G4 method.</p>
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<p>Calculating of <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mo>∆</mo> </mrow> <mrow> <mi mathvariant="normal">l</mi> </mrow> <mrow> <mi mathvariant="normal">g</mi> </mrow> </msubsup> <msubsup> <mrow> <mi>H</mi> </mrow> <mrow> <mi mathvariant="normal">m</mi> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msubsup> </mrow> </semantics></math>(298 K). Development of the contribution H→iPr(en) for the exchange of the H-atom in the cyclohexane ring for the iso-propenyl substituent (<b>left</b>). Development of the contribution H→iPr for the exchange of the H-atom in the cyclohexane ring for the iso-propyl substituent (<b>right</b>). All values in kJ·mol<sup>−1</sup>.</p>
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<p>Calculation of the enthalpy of vaporisation, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mo>∆</mo> </mrow> <mrow> <mi mathvariant="normal">l</mi> </mrow> <mrow> <mi mathvariant="normal">g</mi> </mrow> </msubsup> <msubsup> <mrow> <mi>H</mi> </mrow> <mrow> <mi mathvariant="normal">m</mi> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msubsup> </mrow> </semantics></math>(298 K), of carvone using the 2-methyl-2-cyclohexen-1-one as the “centrepiece” (<b>left</b>). Calculation the enthalpy of vaporisation, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mo>∆</mo> </mrow> <mrow> <mi mathvariant="normal">l</mi> </mrow> <mrow> <mi mathvariant="normal">g</mi> </mrow> </msubsup> <msubsup> <mrow> <mi>H</mi> </mrow> <mrow> <mi mathvariant="normal">m</mi> </mrow> <mrow> <mi mathvariant="normal">o</mi> </mrow> </msubsup> </mrow> </semantics></math>(298 K), of tetrahydrocarvone using the 2-methyl-cyclohexanone as the “centrepiece” (<b>right</b>). All values in kJ·mol<sup>−1</sup>. The experimental values of vaporisation enthalpies of the “centrepieces” are given in <a href="#app1-chemistry-06-00042" class="html-app">Tables S2 and S5</a>.</p>
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<p>Reactions of the partial and complete hydrogenation of double bonds in carvone and carvacrol (reactions 16–18 in <a href="#chemistry-06-00042-t005" class="html-table">Table 5</a>).</p>
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23 pages, 47311 KiB  
Article
Petrogenesis and Tectonic Evolution of I- and A-Type Granites of Mount Abu Kibash and Tulayah, Egypt: Evidence for Transition from Subduction to Post-Collision Magmatism
by Amr El-Awady, Mabrouk Sami, Rainer Abart, Douaa Fathy, Esam S. Farahat, Mohamed S. Ahmed, Hassan Osman and Azza Ragab
Minerals 2024, 14(8), 806; https://doi.org/10.3390/min14080806 (registering DOI) - 9 Aug 2024
Viewed by 189
Abstract
The Neoproterozoic granitic rocks of Mount Abu Kibash and Tulayah in the central Eastern Desert of Egypt are of geodynamic interest and provide us with important information about the evolution and growth of the northern part of the Arabian–Nubian Shield (ANS) continental crust. [...] Read more.
The Neoproterozoic granitic rocks of Mount Abu Kibash and Tulayah in the central Eastern Desert of Egypt are of geodynamic interest and provide us with important information about the evolution and growth of the northern part of the Arabian–Nubian Shield (ANS) continental crust. They are primarily composed of granodiorites and syenogranites based on new field, mineralogical, and geochemical analyses. The granodiorites are marked by an enrichment of LILEs such as Sr, K, Rb, Ba compared to HFSEs like Nb, Ta, Ti and show a higher concentration of LREEs relative to HREEs. This composition suggests a subduction-related setting and aligns with the characteristics of subducted I-type granites in the ANS. Chemistry of the analyzed primary amphiboles in the investigated granodiorites support a calc-alkaline nature, mixed source and subduction-related setting. The granodiorites represent an early magmatic phase in this setting, likely formed from a mix of mantle-derived mafic magmas and lower crust material, with subsequent fractional crystallization. On the other hand, syenogranites exhibit high SiO2 (72.02–74.02 wt%), total alkali (7.82–8.01 wt%), and Al2O3 (13.79–14.25 wt%) levels, suggesting their derivation from peraluminous (A/CNK > 1) parental magmas. Their REE-normalized patterns are flat with a pronounced negative Eu anomaly, typical of post-collisional A2-type granites worldwide. These rocks originated from the partial melting of a juvenile lower crustal source (tonalite) in a post-collisional setting, driven by lithospheric delamination that facilitated mantle upwelling and underplating to the lower crust. Interaction between the upwelled mantle and lower crust led to fertilization (enrichment with HFSE and alkalis) of the lithosphere before partial melting. Fractional crystallization coupled with less considerable crustal assimilation are the main magmatic processes during the evolution of these rocks. The transition from subduction to post-collisional setting was accompanied by crustal uplifting, thickening and extensional collapse of ANS continental crust that caused emplacement of large masses of A-type granites in the northern ANS. Full article
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Figure 1
<p>(<b>a</b>) Geological map of the central Eastern Desert of Egypt exhibiting the distribution of granitoids and other rock units of the basement rocks adjacent to the studied area (modified after [<a href="#B10-minerals-14-00806" class="html-bibr">10</a>]). (<b>b</b>) Geological map of Mount Abu Kibash and Tulayah in the central Eastern Desert of Egypt.</p>
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<p>Field photographs of Mount Abu Kibash and Tulayah granitic rocks in the central Eastern Desert of Egypt. (<b>a</b>) Rounded mafic xenolith hosted in granodiorite. (<b>b</b>) High relief syenogranite at Mount Abu Kibash.</p>
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<p>Photomicrographs and back-scattered electron (BSE) images showing the main petrographic features of Mount Abu Kibash and Tulayah granites: (<b>a</b>) aggregations of biotite (Bt), amphibole (Amph), plagioclase (Plg), K-feldspar (Kfs), and quartz (Qtz) reflecting a typical hypidiomorphic texture of the studied granodiorite; (<b>b</b>) a close up BSE image within granodiorite showing the main mineral phases with the occurrence of ilmenite (Ilm) as an inclusion in amphiboles, (<b>c</b>) the occurrence of coarse- to medium- grained Bt, Plg, Kfs, and Qz minerals with hyidiomorphic texture in syenogranites; (<b>d</b>) BSE image showing the occurrence of magmatic biotite and the mutual relation between the mineral phases in syenogranites, (<b>e</b>) the occurrence of muscovite (Mus) in some syenogranite samples and forming with other minerals a hypidiomorphic texture (<b>f</b>) BSE image of a large ilmenite crystal sharing boundaries with muscovite and quartz in syenogranites.</p>
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<p>Mineral chemistry of silicate minerals in the studied granites. (<b>a</b>) Ab-An-Or ternary classification diagram indicating feldspar composition. (<b>b</b>) Classification diagram of biotite [<a href="#B13-minerals-14-00806" class="html-bibr">13</a>]. (<b>c</b>) (FeOt + MnO) − 10 * TiO<sub>2</sub> − MgO ternary diagram discriminating between primary, re-equilibrated, and secondary biotite [<a href="#B14-minerals-14-00806" class="html-bibr">14</a>]. (<b>d</b>) Mg–Ti–Na ternary diagrams discriminating between primary and secondary muscovite [<a href="#B15-minerals-14-00806" class="html-bibr">15</a>]. (<b>e</b>) Si vs. Mg/Mg + Fe + 2 binary diagram for amphiboles nomenclature [<a href="#B16-minerals-14-00806" class="html-bibr">16</a>]. (<b>f</b>) Ti vs. (Na + K) discrimination diagram of the studied amphiboles [<a href="#B17-minerals-14-00806" class="html-bibr">17</a>].</p>
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<p>Whole-rock chemistry of Mount Abu Kibash and Tulayah granites. (<b>a</b>) TAS classification diagram [<a href="#B19-minerals-14-00806" class="html-bibr">19</a>]. (<b>b</b>) Na<sub>2</sub>O–K<sub>2</sub>O–CaO ternary diagram of Egyptian granitic rocks [<a href="#B18-minerals-14-00806" class="html-bibr">18</a>]. Trondhjemites and calc-alkaline fields are after Barker and Arth [<a href="#B20-minerals-14-00806" class="html-bibr">20</a>].</p>
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<p>Harker variation diagrams of selected major oxides (TiO<sub>2</sub>, (<b>a</b>); Al<sub>2</sub>O<sub>3</sub>, (<b>b</b>); MgO, (<b>c</b>); K<sub>2</sub>O, (<b>d</b>); P<sub>2</sub>O<sub>5</sub>, (<b>e</b>); Fe<sub>2</sub>O<sub>3</sub><sup>t</sup>, (<b>f</b>) and trace elements (Rb, (<b>g</b>); Ba, (<b>h</b>); Sr, (<b>i</b>); Zr, (<b>j</b>); Y, (<b>k</b>); Sc, (<b>l</b>); V, (<b>m</b>); Cr, (<b>n</b>); Ni, (<b>o</b>) vs. SiO<sub>2</sub>. Fields in K<sub>2</sub>O vs. SiO<sub>2</sub> (<b>d</b>) after Rickwood [<a href="#B21-minerals-14-00806" class="html-bibr">21</a>]. Upper crust values are after Rudnick and Gao [<a href="#B22-minerals-14-00806" class="html-bibr">22</a>].</p>
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<p>Bulk-rock chemistry of Mount Abu Kibash and Tulayah granites. (<b>a</b>,<b>c</b>) Chondrite-normalized REE patterns of the investigated granodiorites and syenogranites. (<b>b</b>,<b>d</b>) Multi-element-normalized diagram of the studied granodiorites and syenogranites. Chondrite and primitive mantle normalization values and chondrite values are from Sun and McDonough [<a href="#B23-minerals-14-00806" class="html-bibr">23</a>]. Fields of Homrit Waggat A- and I-type granites [<a href="#B24-minerals-14-00806" class="html-bibr">24</a>], Gabal El-Ineigi A-type granites [<a href="#B26-minerals-14-00806" class="html-bibr">26</a>], and Qianlishan A2-type granites [<a href="#B25-minerals-14-00806" class="html-bibr">25</a>] are used for comparison.</p>
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<p>Crystallization conditions (P–T–<span class="html-italic">fO</span><sub>2</sub>) of the studied granites. (<b>a</b>) Ab–An–Or thermometry diagram [<a href="#B28-minerals-14-00806" class="html-bibr">28</a>]. (<b>b</b>) Ti vs. Mg/(Mg + Fe) for the analyzed biotite showing temperature isotherms [<a href="#B30-minerals-14-00806" class="html-bibr">30</a>]. (<b>c</b>) Ab–Qz–Or ternary diagram for the studied granitic rocks [<a href="#B31-minerals-14-00806" class="html-bibr">31</a>]. (<b>d</b>) Fe/(Fe + Mg) vs. AlIV + AlVI for the analyzed biotite. Ilmenite and magnetite series after Anderson et al. [<a href="#B32-minerals-14-00806" class="html-bibr">32</a>].</p>
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<p>Bulk-rock chemistry of the studied granites showing the role of contamination and fractional crystallization in their evolution. (<b>a</b>) Rb vs. K/Rb diagram [<a href="#B37-minerals-14-00806" class="html-bibr">37</a>]. (<b>b</b>) Zr vs. Th/Nb variation diagrams showing fractional crystallization (FC), assimilation fractional crystallization (AFC), and bulk assimilation (BA) trends [<a href="#B39-minerals-14-00806" class="html-bibr">39</a>]. (<b>c</b>) SiO<sub>2</sub> vs. CaO/Na<sub>2</sub>O diagram with AFC trend. (<b>d</b>) Zr vs. TiO<sub>2</sub> diagram for the studied granites.</p>
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<p>Bulk-rock chemistry showing different types and sources of the studied granites. (<b>a</b>,<b>b</b>) 10<sup>4</sup> × Ga/Al against Nb and K<sub>2</sub>O/MgO for distinguishing between I, S, M and A-type granites [<a href="#B40-minerals-14-00806" class="html-bibr">40</a>]. (<b>c</b>) Al<sub>2</sub>O<sub>3</sub>/(FeO<sup>t</sup> + MgO) − 3*CaO − 5*(K<sub>2</sub>O/Na<sub>2</sub>O) ternary diagram [<a href="#B41-minerals-14-00806" class="html-bibr">41</a>]. (<b>d</b>) Rb vs. K<sub>2</sub>O diagram [<a href="#B44-minerals-14-00806" class="html-bibr">44</a>].</p>
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<p>Bulk-rock chemistry of the studied granites. (<b>a</b>) SiO<sub>2</sub> vs. (Na<sub>2</sub>O + K<sub>2</sub>O) − CaO discrimination diagram [<a href="#B62-minerals-14-00806" class="html-bibr">62</a>]. (<b>b</b>) 100*(MgO + FeO<sup>t</sup> + TiO<sub>2</sub>)/SiO<sub>2</sub> vs. molar (Al<sub>2</sub>O<sub>3</sub> + CaO)/(FeO + Na<sub>2</sub>O + K<sub>2</sub>O) discrimination diagram for distinguishing between different types of granitic magma [<a href="#B61-minerals-14-00806" class="html-bibr">61</a>]. (<b>c</b>) FeO<sup>t</sup>/(FeO<sup>t</sup> + MgO) vs. SiO<sub>2</sub> [<a href="#B62-minerals-14-00806" class="html-bibr">62</a>]. (<b>d</b>) Molar Al<sub>2</sub>O<sub>3</sub>/(Na<sub>2</sub>O + K<sub>2</sub>O) vs. Al<sub>2</sub>O<sub>3</sub>/(CaO + Na<sub>2</sub>O+ K<sub>2</sub>O) for the studied granites [<a href="#B68-minerals-14-00806" class="html-bibr">68</a>]. (<b>e</b>) Y + Nb vs. Rb tectonic discrimination diagram of Pearce et al. [<a href="#B66-minerals-14-00806" class="html-bibr">66</a>]; the post-collisional granite field is from Pearce [<a href="#B65-minerals-14-00806" class="html-bibr">65</a>]. The A-type granite field in previous diagrams is after Whalen et al. [<a href="#B40-minerals-14-00806" class="html-bibr">40</a>]; Eastern Desert (ED) A2-type and I-type granites are after Azer et al. [<a href="#B24-minerals-14-00806" class="html-bibr">24</a>] and Farahat et al. [<a href="#B9-minerals-14-00806" class="html-bibr">9</a>]; Qianlishan A2-type granite field is after Chen et al. [<a href="#B25-minerals-14-00806" class="html-bibr">25</a>]. (<b>f</b>) Hf-Rb/30−3*Ta tectonic discrimination diagram after Harris et al. [<a href="#B67-minerals-14-00806" class="html-bibr">67</a>]. (<b>g</b>) SiO<sub>2</sub> vs. FeO<sup>t</sup>/(FeO<sup>t</sup> + MgO) discrimination diagram [<a href="#B68-minerals-14-00806" class="html-bibr">68</a>]. (<b>h</b>) Y-Nb−3Ga ternary plot [<a href="#B69-minerals-14-00806" class="html-bibr">69</a>]; A1 = A-type granitoids with an ocean island basalt-type source; A2 = A-type granitoids with crust-derived magma. (<b>i</b>) Na<sub>2</sub>O-K<sub>2</sub>O-CaO ternary discrimination diagram showing different types of Egyptian granitoids [<a href="#B26-minerals-14-00806" class="html-bibr">26</a>], where I = old calc-alkaline phase, II = early subphase of young calc-alkaline phase, and III = late subphase of young calc-alkaline phase.</p>
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<p>Mineral chemistry of amphiboles and biotite from the studied granites. (<b>a</b>) TiO<sub>2</sub> vs Al<sub>2</sub>O<sub>3</sub> for the studied primary amphiboles [<a href="#B72-minerals-14-00806" class="html-bibr">72</a>]. (<b>b</b>) Cations of Al<sup>iv</sup> vs. K binary diagram discriminating between alkaline and calc-alkaline magma [<a href="#B71-minerals-14-00806" class="html-bibr">71</a>]. (<b>c</b>) SiO<sub>2</sub> vs. Na<sub>2</sub>O binary diagram of amphiboles [<a href="#B73-minerals-14-00806" class="html-bibr">73</a>] (I-Amph = within-plate amphiboles; S-Amph = Supra-subduction amphiboles). (<b>d</b>) FeO-MgO-Al<sub>2</sub>O<sub>3</sub> ternary discrimination diagram of biotite [<a href="#B70-minerals-14-00806" class="html-bibr">70</a>].</p>
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<p>Sketch showing emplacement of Mount Abu Kibash and Tulayah granitic intrusions within the central Eastern Desert of Egypt in different tectonic stages during the evolution of the ANS. (<b>a</b>) Generation of granodiorites (I-type granite) during the collisional stage in a subduction-related setting (active continental margin) and (<b>b</b>) emplacement of syenogranites (A-type granites) during the post-collisional stage.</p>
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18 pages, 835 KiB  
Review
Management of Heparin-Induced Thrombocytopenia: A Contemporary Review
by Jun Yen Ng, Melanie D’Souza, Felanita Hutani and Philip Choi
J. Clin. Med. 2024, 13(16), 4686; https://doi.org/10.3390/jcm13164686 (registering DOI) - 9 Aug 2024
Viewed by 315
Abstract
Heparin-induced thrombocytopenia (HIT) is a life- and limb-threatening immune-mediated emergency classically associated with heparin therapy. This review focuses on type II HIT, characterized by the development of antibodies against platelet-factor 4 (PF4) bound to heparin after exposure, causing life-threatening thrombocytopenia, arterial thrombosis, and/or [...] Read more.
Heparin-induced thrombocytopenia (HIT) is a life- and limb-threatening immune-mediated emergency classically associated with heparin therapy. This review focuses on type II HIT, characterized by the development of antibodies against platelet-factor 4 (PF4) bound to heparin after exposure, causing life-threatening thrombocytopenia, arterial thrombosis, and/or venous thrombosis. The high morbidity and mortality rates emphasize the need for early recognition and urgent intervention with discontinuation of heparin and initiation of non-heparin anticoagulation. We discuss the management of HIT with an emphasis on recent developments: (i) incorporating the phases of HIT (i.e., suspected, acute, subacute A and B, and remote) into its management, categorized according to platelet count, immunoassay, and functional assay results and (ii) direct-acting oral anticoagulants (DOACs), which are increasingly used in appropriate cases of acute HIT (off-label). In comparison to parenteral options (e.g., bivalirudin and danaparoid), they are easier to administer, are more cost-effective, and obviate the need for transition to an oral anticoagulant after platelet recovery. We also identify the knowledge gaps and suggest areas for future research. Full article
(This article belongs to the Special Issue Antibody-Mediated Thrombotic Diseases)
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<p>Pathogenesis of heparin-induced thrombocytopenia. Heparin exposure leads to the production of immunoglobulin G (IgG) antibodies against PF4 bound to heparin. These antibodies bind to and activate platelets causing thrombosis and thrombocytopenia. They also bind to endothelium, monocytes, and neutrophils leading to thrombin generation, which promotes thrombosis and further activation of platelets. Created with BioRender.com. PF4: platelet factor 4, IgG: immunoglobulin G.</p>
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<p>Key management steps in each phase of heparin-induced thrombocytopenia. HIT: heparin-induced thrombocytopenia, ICU: intensive care unit, VTE: venous thromboembolism.</p>
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24 pages, 637 KiB  
Article
Testing Stimulus Equivalence in Transformer-Based Agents
by Alexis Carrillo and Moisés Betancort
Future Internet 2024, 16(8), 289; https://doi.org/10.3390/fi16080289 - 9 Aug 2024
Viewed by 199
Abstract
This study investigates the ability of transformer-based models (TBMs) to form stimulus equivalence (SE) classes. We employ BERT and GPT as TBM agents in SE tasks, evaluating their performance across training structures (linear series, one-to-many and many-to-one) and relation types (select–reject, select-only). Our [...] Read more.
This study investigates the ability of transformer-based models (TBMs) to form stimulus equivalence (SE) classes. We employ BERT and GPT as TBM agents in SE tasks, evaluating their performance across training structures (linear series, one-to-many and many-to-one) and relation types (select–reject, select-only). Our findings demonstrate that both models performed above mastery criterion in the baseline phase across all simulations (n = 12). However, they exhibit limited success in reflexivity, transitivity, and symmetry tests. Notably, both models achieved success only in the linear series structure with select–reject relations, failing in one-to-many and many-to-one structures, and all select-only conditions. These results suggest that TBM may be forming decision rules based on learned discriminations and reject relations, rather than responding according to equivalence class formation. The absence of reject relations appears to influence their responses and the occurrence of hallucinations. This research highlights the potential of SE simulations for: (a) comparative analysis of learning mechanisms, (b) explainability techniques for TBM decision-making, and (c) TBM bench-marking independent of pre-training or fine-tuning. Future investigations can explore upscaling simulations and utilize SE tasks within a reinforcement learning framework. Full article
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<p>Training structures for members A, B, C, and D of an equivalence class. Baseline relations are shown in black solid arrows. Emergent relations for testing are reflexivity in dashed grey arrows; symmetry in black dashed arrows; and transitivity in black dotted arrows.</p>
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<p>NanoGPT transformer architecture, as described by Karpathy.</p>
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<p>Experimental pairs according to train structures condition. Baseline relations are shown in black solid arrows. Emergent relations for testing are reflexivity in dashed grey arrows; symmetry in black dashed arrows; and transitivity in black dotted arrows.</p>
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<p>Linear series train structure pairs by subset. Top left panel shows Baseline relations in black solid arrows. Symmetry in black dashed arrows on top right panel. Bottom left shows transitivity pairs in black dotted arrows. Bottom right shows reflexivity in dashed grey arrows.</p>
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<p>One-to-many. Top left panel shows Baseline relations in black solid arrows. Symmetry in black dashed arrows on top right panel. Bottom left panel shows transitivity pairs in black dotted arrows. Bottom right panel shows reflexivity in dashed grey arrows.</p>
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<p>Many-to-one. Top left panel shows Baseline relations in black solid arrows. Symmetry in black dashed arrows on top right panel. Bottom left panel shows transitivity pairs in black dotted arrows. Bottom right panel shows reflexivity in dashed grey arrows.</p>
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<p>Simulation 1 performance metrics.</p>
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<p>Simulation 2 performance metrics.</p>
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<p>Simulation 3 performance metrics.</p>
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<p>Simulation 4 performance metrics.</p>
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<p>Simulation 5 performance metrics.</p>
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<p>Simulation 6 performance metrics.</p>
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<p>Simulation 7 performance metrics.</p>
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<p>Simulation 8 performance metrics.</p>
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<p>Simulation 9 performance metrics.</p>
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<p>Simulation 10 performance metrics.</p>
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<p>Simulation 11 performance metrics.</p>
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<p>Simulation 12 performance metrics.</p>
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12 pages, 1407 KiB  
Article
Searching for Extra Higgs Boson Effects in General Two-Higgs Doublet Model (2HDM)
by George Wei-Shu Hou
Symmetry 2024, 16(8), 1013; https://doi.org/10.3390/sym16081013 - 8 Aug 2024
Viewed by 269
Abstract
Starting from our current impasse at the LHC, of observing an SM-like Higgs boson but nothing beyond, we focus on the General 2HDM (G2HDM), which possesses extra sets of Yukawa couplings as a likely Next New Physics. After expounding its merits, we [...] Read more.
Starting from our current impasse at the LHC, of observing an SM-like Higgs boson but nothing beyond, we focus on the General 2HDM (G2HDM), which possesses extra sets of Yukawa couplings as a likely Next New Physics. After expounding its merits, we explore our “Decadal Mission of the New Higgs/Flavor era”, reporting on an Academic Summit Project (ASP) in Taiwan that conducts a four-pronged pursuit of G2HDM: CMS and Belle II searches, a lattice study of first-order electroweak phase transition, and phenomenology. The ASP Midterm report is based on ATLAS and CMS searches for cgtH/tAttc¯, where H and A are exotic neutral scalar bosons, and now progressing onto a post-Midterm cgbH+btb¯ search, where H+ is the exotic charged Higgs boson, plus a few other searches at the LHC, all with discovery potential. We then discuss a plethora of flavor observables that can be explored by CMS and Belle II, as well as other dedicated experiments. Finally, we elucidate why G2HDM, providing myriad new dynamics, can remain well hidden so far. This brief report summarizes the progress of the ASP of the NSTC of Taiwan. Full article
(This article belongs to the Special Issue Feature Papers in 'Physics' Section 2024)
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<p>Two-loop Barr–Zee diagrams for eEDM, where the top loop and the <span class="html-italic">W</span> loop naturally tend to cancel, effectively a <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math>-<math display="inline"><semantics> <mi>γ</mi> </semantics></math>-<math display="inline"><semantics> <msup> <mi>γ</mi> <mo>*</mo> </msup> </semantics></math> insertion, where <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> runs over <span class="html-italic">h</span>, <span class="html-italic">H</span>, <span class="html-italic">A</span>, and even <math display="inline"><semantics> <msup> <mi>H</mi> <mo>+</mo> </msup> </semantics></math>.</p>
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<p>Figure 10 as taken from ATLAS paper [<a href="#B38-symmetry-16-01013" class="html-bibr">38</a>].</p>
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<p>Figure 1 as taken from CMS paper [<a href="#B39-symmetry-16-01013" class="html-bibr">39</a>]. Note that <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>A</mi> <mo>→</mo> <mi>t</mi> <mover accent="true"> <mi>t</mi> <mo stretchy="false">¯</mo> </mover> </mrow> </semantics></math> is also possible.</p>
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<p>Table 3 as taken from CMS paper [<a href="#B39-symmetry-16-01013" class="html-bibr">39</a>].</p>
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<p>Observed 95% CL upper limit on signal strength vs <math display="inline"><semantics> <msub> <mi>m</mi> <mi>A</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>ρ</mi> <mrow> <mi>t</mi> <mi>u</mi> </mrow> </msub> </semantics></math> (<b>left</b>) and <math display="inline"><semantics> <msub> <mi>ρ</mi> <mrow> <mi>t</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (<b>right</b>) for G2HDM without <span class="html-italic">A</span>–<span class="html-italic">H</span> interference, for the combination of <math display="inline"><semantics> <mrow> <msup> <mi>e</mi> <mo>±</mo> </msup> <msup> <mi>e</mi> <mo>±</mo> </msup> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msup> <mi>μ</mi> <mo>±</mo> </msup> <msup> <mi>μ</mi> <mo>±</mo> </msup> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msup> <mi>e</mi> <mo>±</mo> </msup> <msup> <mi>μ</mi> <mo>±</mo> </msup> </mrow> </semantics></math> categories. The color axis represents the observed upper limit on the signal strength. Expected (dashed) and observed (solid) exclusion contours are also shown (taken from Figure 6 of Ref. [<a href="#B39-symmetry-16-01013" class="html-bibr">39</a>]).</p>
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<p>Same as <a href="#symmetry-16-01013-f005" class="html-fig">Figure 5</a>, but with <span class="html-italic">A</span>–<span class="html-italic">H</span> interference (taken from Figure 7 of Ref. [<a href="#B39-symmetry-16-01013" class="html-bibr">39</a>]).</p>
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<p>The <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msub> <mi>V</mi> <mrow> <mi>t</mi> <mi>b</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>V</mi> <mrow> <mi>c</mi> <mi>b</mi> </mrow> </msub> <mrow> <mo stretchy="false">|</mo> </mrow> </mrow> </semantics></math> enhancement of <math display="inline"><semantics> <mrow> <mi>c</mi> <mi>g</mi> <mo>→</mo> <mi>b</mi> <msup> <mi>H</mi> <mo>+</mo> </msup> </mrow> </semantics></math> process w.r.t. 2HDM-II. <math display="inline"><semantics> <mrow> <msup> <mi>H</mi> <mo>+</mo> </msup> <mo>→</mo> <mi>t</mi> <mover accent="true"> <mi>b</mi> <mo stretchy="false">¯</mo> </mover> </mrow> </semantics></math> decay receives the same CKM factor <math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>t</mi> <mi>b</mi> </mrow> </msub> </semantics></math> multiplying <math display="inline"><semantics> <msub> <mi>ρ</mi> <mrow> <mi>t</mi> <mi>t</mi> </mrow> </msub> </semantics></math> [<a href="#B37-symmetry-16-01013" class="html-bibr">37</a>].</p>
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<p><math display="inline"><semantics> <mrow> <msup> <mi>B</mi> <mo>+</mo> </msup> <mo>→</mo> <msup> <mi>μ</mi> <mo>+</mo> </msup> <mi>ν</mi> </mrow> </semantics></math> decay, where the extra Yukawa coupling <math display="inline"><semantics> <msub> <mi>ρ</mi> <mrow> <mi>τ</mi> <mi>μ</mi> </mrow> </msub> </semantics></math> enters the process.</p>
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<p>A picture table of the <span class="html-italic">new flavor era</span> of G2HDM in the coming decades [<a href="#B48-symmetry-16-01013" class="html-bibr">48</a>]. The five gray boxes are remnants of <span class="html-italic">B</span>-<span class="html-italic">anomalies</span>, which evaporated with disappearance of <math display="inline"><semantics> <msub> <mi>R</mi> <mi>K</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>R</mi> <msup> <mi>K</mi> <mo>*</mo> </msup> </msub> </semantics></math> “<span class="html-italic">anomalies</span>” [<a href="#B47-symmetry-16-01013" class="html-bibr">47</a>]. Blue circles are the experimental limits as of 8/2020, while orange circles are projected limits. The downward red arrow depicts the G2HDM expectation according to the “Rule of Thumb” of Equation (<a href="#FD8-symmetry-16-01013" class="html-disp-formula">8</a>) below, which explains why G2HDM effects are well-hidden when lighter generations are involved. The red stars reflect SM expectations, and the green boxes are SM-G2HDM interference ranges.</p>
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<p>Illustration of the “Road Not Taken”: sub-TeV <span class="html-italic">H</span>, <span class="html-italic">A</span>, and <math display="inline"><semantics> <msup> <mi>H</mi> <mo>±</mo> </msup> </semantics></math> exotic Higgs bosons.</p>
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14 pages, 4035 KiB  
Article
Transcriptomic Analysis of Alfalfa Flowering and the Dual Roles of MsAP1 in Floral Organ Identity and Flowering Time
by Xu Jiang, Huiting Cui, Zhen Wang, Ruicai Long, Qingchuan Yang and Junmei Kang
Agronomy 2024, 14(8), 1741; https://doi.org/10.3390/agronomy14081741 - 8 Aug 2024
Viewed by 313
Abstract
Flowering, the transition from the vegetative to the reproductive stage, is vital for reproductive success, affecting forage quality, the yield of aboveground biomass, and seed production in alfalfa. To explore the transcriptomic profile of alfalfa flowering transition, we compared gene expression between shoot [...] Read more.
Flowering, the transition from the vegetative to the reproductive stage, is vital for reproductive success, affecting forage quality, the yield of aboveground biomass, and seed production in alfalfa. To explore the transcriptomic profile of alfalfa flowering transition, we compared gene expression between shoot apices (SAs) at the vegetative stage and flower buds (FBs) at the reproductive stage by mRNA sequencing. A total of 3,409 DEGs were identified, and based on gene ontology (GO), 42.53% of the most enriched 15 processes were associated with plant reproduction, including growth phase transition and floral organ development. For the former category, 79.1% of DEGs showed higher expression levels in SA than FB, suggesting they were sequentially turned on and off at the two test stages. For the DEGs encoding the components of circadian rhythm, sugar metabolism, phytohormone signaling, and floral organ identity genes, 60.71% showed higher abundance in FB than SA. Among them, MsAP1, an APETALA1 (AP1) homolog of Arabidopsis thaliana, showed high expression in flower buds and co-expressed with genes related to flower organ development. Moreover, ectopic expression of MsAP1 in Arabidopsis resulted in dwarfism and early flowering under long-day conditions. The MsAP1-overexpression plant displayed morphological abnormalities including fused whorls, enlarged pistils, determinate inflorescence, and small pods. In addition, MsAP1 is localized in the nucleus and exhibits significant transcriptional activity. These findings revealed a transcriptional regulation network of alfalfa transition from juvenile phase to flowering and provided genetic evidence of the dual role of MsAP1 in flowering and floral organ development. Full article
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<p>Transcriptome analysis of alfalfa shoot apical tissues on day 25 and the floral buds on day 35. (<b>a</b>) The kinetic growth analysis of alfalfa in terms of plant height under the normal conditions. (<b>b</b>,<b>c</b>) Image of alfalfa shoot apex (SA) and floral bud (FB) on day 25 and day 35, respectively. The tissues were used for mRNA sequencing. (<b>d</b>) Heatmap of differential gene expression profiles of SA (day 25) and FB (day 35). The heatmap was constructed using FPKM values and normalized to a range of zero to one. Red represents high FPKM values, and blue for low values. (<b>e</b>) DEGs identified in this study with cut off |log2Foldchange| &gt; 1. Red stands for the upregulated genes in FB relative to SA, and blue for the downregulated genes. (<b>f</b>) Linear regression analysis between mRNA sequencing data and the expression level test by RT-qPCR of the 15 randomly selected DEGs.</p>
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<p>Classification of the DEGs enriched in terms of biological process and pathway. (<b>a</b>) Analysis of biological processes of the DEGs. GO terms for growth stage transition are marked with dots, while GO terms for flower organ development are indicated with asterisks. (<b>b</b>) Top 15 enriched pathways via Mapman. (<b>c</b>) The most enriched GO function of the putative transcription factors. (<b>d</b>) Transcript profile of the DEGs involved in phytohormone IAA, GA, and CTK signaling. The scale represents normalized FPKM for the annotated genes via sequence homology. The gradient colors from red to blue denote high and low expression, respectively.</p>
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<p>Analysis of floral formation-related TFs. (<b>a</b>) Gene expression profiles of DEGs related to the timing of meristematic phase transition. The color scale indicates normalized FPKM changes in gene expression levels in alfalfa shoot apical and flower bud tissue. The gradient colors from red to blue indicate the abundance of gene expression from high to low. The arrow symbol represents the activation relationship. LFY, LEAFY; FUL, FRUITFULL; WUS, WUSCHEL; SOC1, SUPPRESSOR OF CONSTANS OVEREXPRESSION 1; SPL, squamosa promoter-binding-like protein. (<b>b</b>) Network analysis of <span class="html-italic">AP1</span> and <span class="html-italic">AP2</span> and their network genes. Pale purple lines indicate co-expression network and pale red lines indicate physical interaction in Arabidopsis. The red arrow symbol represents upregulated expression of genes in flower buds, while the blue symbol represents downregulated expression. (<b>c</b>) Analysis of <span class="html-italic">MsAP1</span> expression pattern in different organs in vegetative and reproductive growth phase. Tissue sampling during the vegetative growth stage was performed on the 25th day after harvesting, floral meristem tissues were collected on the 30th day, and stems, leaves, flower buds, and flowers during the flowering stage were collected on day 40. Data represent mean values (with error bars indicating standard deviations from 3 biological replicates), and different letters denote significance levels &lt; 0.01, determined by statistical analysis using one-way ANOVA.</p>
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<p>Transcriptional activity assay and subcellular localization investigation of MsAP1. (<b>a</b>) The subcellular localization of the MsAP1-GFP fusion protein transiently expressed in tobacco leaves. Images were captured using a confocal microscope. Label the two constructs (control upper and recombinant vector lower panel, respectively); scale bars: 100 µm. Green represents GFP fluorescence signal, and blue dots represent cell nuclei labeled with DAPI (4’,6-diamidino-2-phenylindole). (<b>b</b>) Schematic diagram of His reporter gene expression activated by MsAP1 in a yeast cell. GAL4-BD represents the binding domain of GAL4. (<b>c</b>) Assay of the transcriptional activation of MsAP1 in yeast (Y2H) cells. Yeast were transfected with pGBKT7-MsAP1 (BD-MsAP1), pGBKT7-GAL4AD (positive control), and pGBKT7 (BD, negative control), respectively. The transformed cells were streaked on SC/-T and selective medium (SC/-T-H + 15 mM 3-AT) to assess growth. SC/-T: synthetic dropout (SC) yeast growth medium lacking tryptophan, SC/-L-H: SC medium lacking tryptophan and histidine, and supply with 15 mM 3-AT.</p>
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<p>Overexpression of <span class="html-italic">MsAP1</span> promoted flowering and altered floral organ morphology in Arabidopsis. (<b>a</b>) The relative transcription level of <span class="html-italic">MsAP1</span>. (<b>b</b>) Image of the homozygous T2 seedlings on day 20 after germination (DAG) under the long-day conditions. WT: Col-0, OE1, and OE3 represented the two independent transgenic Arabidopsis lines (<span class="html-italic">35S::MsAP1-GFP</span>). Bar = 2 cm. (<b>c</b>) Flowering time analysis in terms of days to bolting under the long-day conditions. (<b>d</b>) Analysis of rosette leaf number at the emergence of the first flower under the long-day conditions. (<b>e</b>) Phenotypes of the <span class="html-italic">MsAP1</span> overexpressing Arabidopsis terminal flowers, bar = 3 mm. (<b>f</b>) Phenotype of the fruit of Arabidopsis <span class="html-italic">thaliana</span>. Bar = 5 mm. (<b>g</b>) Relative transcription levels of the key genes related to Arabidopsis floral transition. Asterisks indicate significant difference at <span class="html-italic">p</span> &lt; 0.01 compared with wild type by Student’s <span class="html-italic">t</span>-test.</p>
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