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18 pages, 5323 KiB  
Article
Silica Accumulation in Potato (Solanum tuberosum L.) Plants and Implications for Potato Yield Performance—Results from Field Experiments in Northeast Germany
by Daniel Puppe, Jacqueline Busse, Mathias Stein, Danuta Kaczorek, Christian Buhtz and Jörg Schaller
Biology 2024, 13(10), 828; https://doi.org/10.3390/biology13100828 - 16 Oct 2024
Viewed by 77
Abstract
The potato is the most important non-cereal food crop, and thus improving potato growth and yield is the focus of agricultural researchers and practitioners worldwide. Several studies reported beneficial effects of silicon (Si) fertilization on potato performance, although plant species from the family [...] Read more.
The potato is the most important non-cereal food crop, and thus improving potato growth and yield is the focus of agricultural researchers and practitioners worldwide. Several studies reported beneficial effects of silicon (Si) fertilization on potato performance, although plant species from the family Solanaceae are generally considered to be non-Si-accumulating. We used results from two field experiments in the temperate zone to gain insight into silica accumulation in potato plants, as well as corresponding long-term potato yield performance. We found relatively low Si contents in potato leaves and roots (up to 0.08% and 0.3% in the dry mass, respectively) and negligible Si contents in potato tuber skin and tuber flesh for plants grown in soils with different concentrations of plant-available Si (field experiment 1). Moreover, potato yield was not correlated to plant-available Si concentrations in soils in the long term (1965–2015, field experiment 2). Based on our results, we ascribe the beneficial effects of Si fertilization on potato growth and yield performance reported in previous studies mainly to antifungal/osmotic effects of foliar-applied Si fertilizers and to changes in physicochemical soil properties (e.g., enhanced phosphorus availability and water-holding capacity) caused by soil-applied Si fertilizers. Full article
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Figure 1

Figure 1
<p>Overview of the plots at the silica amendment experiment. While six plots serve as control (i.e., plot numbers 1.1–1.6, marked by black squares), six plots represent Si treatments with 0.5% (i.e., plot numbers 2.1–2.3, marked by light green squares) or 1.0% (i.e., plot numbers 3.1–3.3, marked by dark green squares) amorphous silica mass percentage.</p>
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<p>Overview of the plots at the LTFE (modified from Puppe et al. [<a href="#B21-biology-13-00828" class="html-bibr">21</a>]). The plots used in the study by Puppe et al. [<a href="#B21-biology-13-00828" class="html-bibr">21</a>] are highlighted in color (see legend). 1 = low fertilization rate (NPK 1, ~30 kg N ha<sup>−1</sup> y<sup>−1</sup>), 3 = medium (i.e., common) fertilization rate (NPK 3, ~98 kg N ha<sup>−1</sup> y<sup>−1</sup>), and 5 = high fertilization rate (NPK 5, ~166 kg N ha<sup>−1</sup> y<sup>−1</sup>). At plots with crop straw recycling (NPK + Straw), NPK fertilization has been supplemented by incorporation of 4.0 t (dry mass) straw ha<sup>−1</sup> every second year using chopped straw of the recently harvested cereal crop. At the control plots, neither NPK fertilization, nor crop straw recycling has been performed.</p>
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<p>Plant-available Si in soils of control and Si plots of the silica amendment experiment. Means are marked by “x” in the boxplots each. Different letters indicate statistically significant differences (Kruskal–Wallis ANOVA, <span class="html-italic">p</span> &lt; 0.05) between the plots.</p>
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<p>Relative Si abundance (SEM-EDX) in leaves, tubers (i.e., tuber skin and tuber flesh), and roots of potato plants taken at control and Si plots of the silica amendment experiment. Black and green bars represent means of normalized mass percent, error bars represent corresponding standard deviations. x = no data available.</p>
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<p>Elemental analyses (SEM-EDX) of leaf samples from potato plants taken at the first sampling date (30 June 2022) at control and Si plots of the silica amendment experiment. (<b>A</b>) Micrograph of the leaf top epidermis (control), (<b>B</b>) micrograph of the leaf undersurface epidermis (control), (<b>C</b>) corresponding exemplary EDX spectra derived from SEM-EDX measurements performed in a specific region of interest in (<b>B</b>) (green circle), (<b>D</b>) micrograph of a leafstalk cross-section (1.0% ASi), (<b>E</b>) corresponding exemplary EDX spectra derived from SEM-EDX measurements performed in a specific region of interest in (<b>D</b>) (green circle), (<b>F</b>) micrograph of a leafstalk cross-section (1.0% ASi), and (<b>G</b>) corresponding compositional map for Si in a specific region of interest in (<b>F</b>) (red rectangle).</p>
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<p>Potato yields for low (<b>A</b>), medium (i.e., common) (<b>B</b>), and high (<b>C</b>) fertilization plots (NPK 1, NPK 3, and NPK 5, respectively) at the long-term field experiment. Yields are stated for all years in which potatoes were grown during the ongoing long-term field experiment. Different letters indicate statistically significant differences (Kruskal–Wallis ANOVA, <span class="html-italic">p</span> &lt; 0.05) between control, NPK, and NPK + Straw plots in a specific year.</p>
Full article ">Figure 6 Cont.
<p>Potato yields for low (<b>A</b>), medium (i.e., common) (<b>B</b>), and high (<b>C</b>) fertilization plots (NPK 1, NPK 3, and NPK 5, respectively) at the long-term field experiment. Yields are stated for all years in which potatoes were grown during the ongoing long-term field experiment. Different letters indicate statistically significant differences (Kruskal–Wallis ANOVA, <span class="html-italic">p</span> &lt; 0.05) between control, NPK, and NPK + Straw plots in a specific year.</p>
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<p>Plant-available Si in soils of the different plots at the long-term field experiment for the years 1976, 1998, and 2018 (data taken from Puppe et al. [<a href="#B21-biology-13-00828" class="html-bibr">21</a>]). Different letters indicate statistically significant differences (Kruskal–Wallis ANOVA, <span class="html-italic">p</span> &lt; 0.05) between the three years for specific plots. If no statistical significances were found for a specific plot, no letters were stated.</p>
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<p>Monthly climate data (<span class="underline">temp</span>erature and <span class="underline">prec</span>ipitation) for the region, where our study sites are located. Climate data are stated for all years in which potatoes were grown during the ongoing long-term field experiment at ZALF. Temperatures ≥ 17 °C (diminishment of potato tuberization) in the potato growing season (April–September) in Brandenburg, Germany, are highlighted in yellow. Figure created using “ClimateCharts.net” [<a href="#B44-biology-13-00828" class="html-bibr">44</a>], modified.</p>
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24 pages, 11094 KiB  
Article
Synergistic Effects of Polypropylene Fibers and Silica Fume on Structural Lightweight Concrete: Analysis of Workability, Thermal Conductivity, and Strength Properties
by Zehra Funda Akbulut, Eva Kuzielová, Taher A. Tawfik, Piotr Smarzewski and Soner Guler
Materials 2024, 17(20), 5042; https://doi.org/10.3390/ma17205042 (registering DOI) - 15 Oct 2024
Viewed by 286
Abstract
Structural lightweight concrete (SLWC) is crucial for reducing building weight, reducing structural loads, and enhancing energy efficiency through lower thermal conductivity. This study explores the effects of incorporating silica fume (SF), micro-polypropylene (micro-PP), and macro-PP fibers on the workability, thermal properties, and strength [...] Read more.
Structural lightweight concrete (SLWC) is crucial for reducing building weight, reducing structural loads, and enhancing energy efficiency through lower thermal conductivity. This study explores the effects of incorporating silica fume (SF), micro-polypropylene (micro-PP), and macro-PP fibers on the workability, thermal properties, and strength of SLWC. SF was added to all mixtures, substituting 10% of the Portland cement (PC), except for the control mixture. Macro-PP fibers were introduced alone or in combination with micro-PP fibers at volumetric ratios of 0.3% and 0.6%. The study evaluated various parameters, including slump, Vebe time, density, water absorption (WA), ultrasonic pulse velocity (UPV), thermal conductivity coefficients (k), compressive strength (CS), and splitting tensile strength (STS) across six different SLWC formulations. The results indicate that while SF negatively impacted the workability of SLWC mortars, it improved CS and STS due to the formation of calcium silicate hydrate (C-S-H) gels from SF’s high pozzolanic activity. Additionally, using micro-PP fibers in combination with macro-PP fibers rather than solely macro-PP fibers enhanced the workability, CS, and STS of the SLWC samples. Although SF had a minor effect on reducing thermal conductivity, the use of macro-PP fibers alone was more effective for improving thermal properties by creating a more porous structure compared to the hybrid use of micro-PP fibers. Moreover, increasing the ratio of micro- and macro-PP fibers from 0.3% to 0.6% resulted in lower CS values but a significant increase in STS values. Full article
(This article belongs to the Special Issue Advanced Characterization of Fiber-Reinforced Composite Materials)
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Figure 1

Figure 1
<p>The images of the PA<sub>s</sub> ((<b>a</b>) 0–4 mm, (<b>b</b>) 4–8 mm, and (<b>c</b>) 8–16 mm), (<b>d</b>) SF, (<b>e</b>) 12 mm micro-PP, and (<b>f</b>) 40 mm macro-PP fibers.</p>
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<p>The SEM images of the pumice aggregate and silica fume (SF). (<b>a</b>) pumice aggregate (<b>b</b>) silica fume.</p>
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<p>A schematic overview of the experimental procedure.</p>
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<p>The slump values of fresh SLWC mixtures.</p>
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<p>The Vebe time–slump relationship of fresh SLWC mixtures.</p>
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<p>The de-molded density (DD) and oven-dry density (ODD) values of K0–K5 SLWC mixtures.</p>
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<p>The water absorption (WA) values of SLWC specimens.</p>
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<p>The ultrasonic pulse velocity (UPV) values of SLWC specimens.</p>
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<p>The thermal conductivity coefficient (k) values of SLWC specimens.</p>
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<p>The compressive strength (CS) values of SLWC specimens.</p>
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<p>The relationship between fiber volume ratio and compressive strength (CS) values of SLWC specimens.</p>
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<p>The splitting tensile strength (STS) values of SLWC specimens.</p>
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<p>The relationship between fiber volume ratio and splitting tensile strength (STS) values of SLWC specimens.</p>
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<p>The SEM images of K0, K1, and K5 SLWC specimens.</p>
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12 pages, 2999 KiB  
Article
Ordered Mesoporous Nitrogen Dope Carbon Synthesized from Aniline for Stabilization of Ruthenium Species in CO2 Hydrogenation to Formate
by Arsalan Haider, Ahmad Masudi, Sunghee Ahn, Kwangho Park, Kyung Rok Lee and Kwang-Deog Jung
Catalysts 2024, 14(10), 720; https://doi.org/10.3390/catal14100720 - 15 Oct 2024
Viewed by 337
Abstract
The hydrogenation of CO2 to produce formic acid has garnered increasing interest as a means to address climate change and promote the hydrogen economy. This research investigates the nanocasting technique for the synthesis of ordered mesoporous nitrogen-doped carbon (MNC-An). KIT-6 functioned as [...] Read more.
The hydrogenation of CO2 to produce formic acid has garnered increasing interest as a means to address climate change and promote the hydrogen economy. This research investigates the nanocasting technique for the synthesis of ordered mesoporous nitrogen-doped carbon (MNC-An). KIT-6 functioned as the silica template, while aniline served as the nitrogen–carbon precursor. The resultant MNC-An exhibits cubic Ia3D geometry, possesses significant mesoporosity, and has a high nitrogen content, which is essential for stabilizing ruthenium single atoms. The catalyst exhibited a specific activity of 252 mmolFAgcat−1 following a 2 h reaction at 120 °C. Moreover, the catalyst exhibited exceptional relative activity during five recycling experiments while preserving its catalytic efficacy. The atomically dispersed ruthenium and its Ru3+ oxidation state demonstrated perseverance both before and after the treatment. The results indicated that the synthesized catalyst possesses potential for the expedited commercialization of CO2 hydrogenation to produce formic acid. The elevated carbon yield, along with excellent thermal stability, renders it a viable substrate for attaching and stabilizing atomically dispersed ruthenium catalysts. Full article
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Graphical abstract

Graphical abstract
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<p>Schematic illustration for synthesis of MNC-An using nanocasting.</p>
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<p>HRTEM (<b>a</b>), SAXS pattern (<b>b</b>), N<sub>2</sub> adsorption–desorption isotherm (<b>c</b>) and GCMC pore size distribution (<b>d</b>) for MNC-An. Closed and open symbols in <a href="#catalysts-14-00720-f002" class="html-fig">Figure 2</a>c indicate the adsorption and desorption.</p>
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<p>XRD pattern (<b>a</b>), Raman analysis (<b>b</b>), XPS C1s (<b>c</b>) and N1s (<b>d</b>) deconvolution for MNC-An.</p>
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<p>Stability Test of Ru/MNC-An over five cycles (reaction conditions: 120 °C, 80 bar pressure; H<sub>2</sub>:CO<sub>2</sub> (1:1), 1MTEA, 2 h reaction).</p>
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<p>HRTEM and HAADF-STEM of fresh catalyst Ru/MNC-An (<b>a</b>,<b>c</b>), spent catalyst (<b>b</b>,<b>d</b>). Red and purple boxes indicate the area where HAADF-STEM images were acquired. XPS Ru(3P) of fresh (<b>e</b>) and spent (<b>f</b>) catalyst.</p>
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<p>Deconvoluted N1s spectra of fresh (<b>a</b>) and spent (<b>b</b>) catalysts.</p>
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<p>Deconvoluted N1s spectra of fresh and spent catalysts.</p>
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20 pages, 519 KiB  
Review
Silicon-, Silica-, and Silicate-Toothpastes for Remineralization and Repair of Teeth: A Scoping Review
by Fabio Correia Sampaio, Andressa Feitosa Bezerra de Oliveira, Nayanna Lana Soares Fernandes, Ana Carolina Cheron Gentile, Giovanna Bueno Marinho, Marcelo José Strazzeri Bönecker, Marco Aurelio Benini Paschoal, Paulo Henrique Perlatti D’Alpino and Fabiano Vieira Vilhena
Oral 2024, 4(4), 467-486; https://doi.org/10.3390/oral4040038 (registering DOI) - 15 Oct 2024
Viewed by 234
Abstract
Objective: The purpose of this scoping review was to identify gaps in the literature and summarize findings from studies examining the use of silicon-, silica-, and silicate-based toothpastes for the remineralization and repair of mineralized tooth tissues. Methods: A 10-year literature search [...] Read more.
Objective: The purpose of this scoping review was to identify gaps in the literature and summarize findings from studies examining the use of silicon-, silica-, and silicate-based toothpastes for the remineralization and repair of mineralized tooth tissues. Methods: A 10-year literature search was conducted using PubMed and Scopus, adhering to PRISMA 2020 guidelines. A total of 331 studies were initially identified, with 56 full-text review articles. After selecting the manuscripts, 27 studies were qualitatively analyzed by four reviewers, focusing on the results of both in vivo and in vitro methods. Results: The findings suggest that toothpastes containing silicon, silica, and silicate demonstrate promising results for remineralization and enamel repair, with evidence of mineral layer formation and/or deep enamel surface remineralization under various conditions. Additionally, the use of these toothpastes can lead to the obliteration of dentinal tubules within a few days. The results collectively support the efficacy of these toothpastes in enamel repair. Most of the clinical studies focused on dentine hypersensitivity, followed by white spot lesions. Conclusions: Silicon-, silica-, and silicate-based toothpastes (bioactive Si-toothpastes) can be considered effective based mostly on laboratory studies. There remains a need for more in vivo research studies on enamel and dentin mineral repair. Existing studies provide strong evidence that these technologies can reduce dentin hypersensitivity and promote enamel–dentin repair. Full article
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Figure 1
<p>PRISMA 2020 flow diagram. * Databases and registers only, no websites; ** No automation tools were used in the process.</p>
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16 pages, 5129 KiB  
Article
Enhanced Electrochemiluminescence of Luminol and-Dissolved Oxygen by Nanochannel-Confined Au Nanomaterials for Sensitive Immunoassay of Carcinoembryonic Antigen
by Weibin Li, Ruliang Yu and Fengna Xi
Molecules 2024, 29(20), 4880; https://doi.org/10.3390/molecules29204880 (registering DOI) - 15 Oct 2024
Viewed by 380
Abstract
Simple development of an electrochemiluminescence (ECL) immunosensor for convenient detection of tumor biomarker is of great significance for early cancer diagnosis, treatment evaluation, and improving patient survival rates and quality of life. In this work, an immunosensor is demonstrated based on an enhanced [...] Read more.
Simple development of an electrochemiluminescence (ECL) immunosensor for convenient detection of tumor biomarker is of great significance for early cancer diagnosis, treatment evaluation, and improving patient survival rates and quality of life. In this work, an immunosensor is demonstrated based on an enhanced ECL signal boosted by nanochannel-confined Au nanomaterial, which enables sensitive detection of the tumor biomarker—carcinoembryonic antigen (CEA). Vertically-ordered mesoporous silica film (VMSF) with a nanochannel array and amine groups was rapidly grown on a simple and low-cost indium tin oxide (ITO) electrode using the electrochemically assisted self-assembly (EASA) method. Au nanomaterials were confined in situ on the VMSF through electrodeposition, which catalyzed both the conversion of dissolved oxygen (O2) to reactive oxygen species (ROS) and the oxidation of a luminol emitter and improved the electrode active surface. The ECL signal was enhanced fivefold after Au nanomaterial deposition. The recognitive interface was fabricated by covalent immobilization of the CEA antibody on the outer surface of the VMSF, followed with the blocking of non-specific binding sites. In the presence of CEA, the formed immunocomplex reduced the diffusion of the luminol emitter, resulting in the reduction of the ECL signal. Based on this mechanism, the constructed immunosensor was able to provide sensitive detection of CEA ranging from 1 pg·mL−1 to 100 ng·mL−1 with a low limit of detection (LOD, 0.37 pg·mL−1, S/N = 3). The developed immunosensor exhibited high selectivity and good stability. ECL determination of CEA in fetal bovine serum was achieved. Full article
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Figure 1

Figure 1
<p>Schematic illustration for the fabrication of the ECL immunosensor for sensitive detection of CEA based on enhanced ECL by nanochannel-confined Au nanomaterials and an immunorecognition interface fabricated on the outer surface of NH<sub>2</sub>-VMSF.</p>
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<p>(<b>a</b>) TEM image of the top-view surface of NH<sub>2</sub>-VMSF. Inset is the corresponding TEM image at high magnification. The hexagon represents six adjacent nanochannels. (<b>b</b>) TEM image of the cross-section of NH<sub>2</sub>-VMSF. (<b>c</b>) SEM image of the cross-section of the NH<sub>2</sub>-VMSF/ITO electrode.</p>
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<p>CV curves obtained from different electrodes in 0.5 mM of (<b>a</b>) K<sub>3</sub>[Fe(CN)<sub>6</sub>] and (<b>b</b>) Ru(NH<sub>3</sub>)<sub>6</sub>Cl<sub>3</sub>. The scanning rate is 50 mV/s.</p>
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<p>(<b>a</b>) XPS survey spectra obtained from the NH<sub>2</sub>-VMSF/ITO and Au@NH<sub>2</sub>-VMSF/ITO electrodes. (<b>b</b>) High-resolution Au 4f spectra obtained from the Au@NH<sub>2</sub>-VMSF/ITO electrode. (<b>c</b>) CV curves obtained from the NH<sub>2</sub>-VMSF/ITO or Au@NH<sub>2</sub>-VMSF/ITO electrode in 0.5 M of H<sub>2</sub>SO<sub>4</sub>.</p>
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<p>(<b>a</b>) EIS plots obtained in KCl (0.1 M) containing Fe(CN)<sub>6</sub><sup>3</sup>/<sup>4−</sup> (2.5 mM). The frequency range for EIS measurements was from 0.1 Hz to 100 kHz, with a perturbation amplitude of 5 mV. The used CEA solution was 1 ng mL<sup>−1</sup> in PBS. (<b>b</b>) The ECL signal obtained from different electrodes in 100 μM of luminol. The bias of PMT was 700 V. The CV scan range was from −1.0 V to 0.8 V, with a scan rate of 100 mV/s.</p>
Full article ">Figure 6
<p>(<b>a</b>) CV curves obtained from different electrodes in the absence or presence of dissolved oxygen. (<b>b</b>) CV curves obtained from different electrodes in the absence or presence of luminol. CV curves obtained from the NH<sub>2</sub>-VMSF/ITO (<b>c</b>) and the Au@NH<sub>2</sub>-VMSF/ITO electrodes (<b>d</b>) in 0.1 M KHP (pH 4) containing 0.5 mM K<sub>3</sub>[Fe(CN)<sub>6</sub>]. The scan rate was 30, 50, 70, 100, 150, 200, and 300 mV/s, respectively. Insets are the linear relationships between the peak current and the square root of the scan rate obtained from (<b>c</b>) the NH<sub>2</sub>-VMSF/ITO or (<b>d</b>) the Au@NH<sub>2</sub>-VMSF/ITO electrode.</p>
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<p>(<b>a</b>) The ratio of the ECL signal obtained from the Au@NH<sub>2</sub>-VMSF/ITO electrode in the presence of different radical trapping agents. The concentration of 1,4-benzoquinone (BQ) and tert-butanol (TBA) was 100 μM and 100 μg/mL, respectively. (<b>b</b>) The ECL signal obtained from the Au@NH<sub>2</sub>-VMSF/ITO electrode in 0.01 M PBS (pH = 7.4) solution containing 100 μM of luminol, in which Au nanomaterials were deposited for 0 s, 1 s, 2 s, 5 s, or 10 s, respectively. The concentration of the HAuCl<sub>4</sub> solution was 1 mM. (<b>c</b>) The ECL signal obtained from an immunosensor fabricated using different times for Ab immobilization. (<b>d</b>) The ECL signal obtained using different times for CEA binding.</p>
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<p>(<b>a</b>) ECL signals from the fabricated immunosensor incubated with different concentrations of CEA. (<b>b</b>) Linear calibration curve of CEA detection. (<b>c</b>) The ratio of the ECL signal of the immunosensor before (I<sub>0</sub>) and after (I) incubation with the different substances. The concentration of Na<sup>+</sup> and Cl<sup>−</sup> is 10 μM; the concentration of Glu is 20 μM; the concentration of CA125 is 200 mU mL<sup>−1</sup>; the concentration of CRP and PCT is 200 ng mL<sup>–1</sup>; the fetal bovine serum was diluted 50 times using PBS (D-FBS); and the concentration of CEA is 10 ng mL<sup>–1</sup>. (<b>d</b>) Stability of the immunosensor within five days.</p>
Full article ">Figure 8 Cont.
<p>(<b>a</b>) ECL signals from the fabricated immunosensor incubated with different concentrations of CEA. (<b>b</b>) Linear calibration curve of CEA detection. (<b>c</b>) The ratio of the ECL signal of the immunosensor before (I<sub>0</sub>) and after (I) incubation with the different substances. The concentration of Na<sup>+</sup> and Cl<sup>−</sup> is 10 μM; the concentration of Glu is 20 μM; the concentration of CA125 is 200 mU mL<sup>−1</sup>; the concentration of CRP and PCT is 200 ng mL<sup>–1</sup>; the fetal bovine serum was diluted 50 times using PBS (D-FBS); and the concentration of CEA is 10 ng mL<sup>–1</sup>. (<b>d</b>) Stability of the immunosensor within five days.</p>
Full article ">
21 pages, 16172 KiB  
Article
Taurine Protects against Silica Nanoparticle-Induced Apoptosis and Inflammatory Response via Inhibition of Oxidative Stress in Porcine Ovarian Granulosa Cells
by Fenglei Chen, Jiarong Sun, Rongrong Ye, Tuba Latif Virk, Qi Liu, Yuguo Yuan and Xianyu Xu
Animals 2024, 14(20), 2959; https://doi.org/10.3390/ani14202959 - 14 Oct 2024
Viewed by 229
Abstract
Silica nanoparticles (SNPs) induce reproductive toxicity through ROS production, which significantly limits their application. The protective effects of taurine (Tau) against SNP-induced reproductive toxicity remain unexplored. So this study aims to investigate the impact of Tau on SNP-induced porcine ovarian granulosa cell toxicity. [...] Read more.
Silica nanoparticles (SNPs) induce reproductive toxicity through ROS production, which significantly limits their application. The protective effects of taurine (Tau) against SNP-induced reproductive toxicity remain unexplored. So this study aims to investigate the impact of Tau on SNP-induced porcine ovarian granulosa cell toxicity. In vitro, granulosa cells were exposed to SNPs combined with Tau. The localization of SNPs was determined by TEM. Cell viability was examined by CCK-8 assay. ROS levels were measured by CLSM and FCM. SOD and CAT levels were evaluated using ELISA and qPCR. Cell apoptosis was detected by FCM, and pro-inflammatory cytokine transcription levels were measured by qPCR. The results showed that SNPs significantly decreased cell viability, while increased cell apoptosis and ROS levels. Moreover, SOD and CAT were decreased, while IFN-α, IFN-β, IL-1β, and IL-6 were increased after SNP exposures. Tau significantly decreased intracellular ROS, while it increased SOD and CAT compared to SNPs alone. Additionally, Tau exhibited anti-inflammatory effects and inhibited cell apoptosis. On the whole, these findings suggest that Tau mitigates SNP-induced cytotoxicity by reducing oxidative stress, inflammatory response, and cell apoptosis. Tau may be an effective strategy to alleviate SNP-induced toxicity and holds promising application prospects in the animal husbandry and veterinary industry. Full article
(This article belongs to the Special Issue Developmental and Reproductive Toxicity of Nanoparticles in Animals)
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Figure 1
<p>Characteristics and cytotoxicity of SNPs: (<b>A</b>) Representative TEM image of SNPs. (<b>B</b>) Size distribution of SNPs. (<b>C</b>) CCK-8 assay. (<b>D</b>) LDH leakage assay. ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. Control.</p>
Full article ">Figure 2
<p>Cellular uptake and distribution of SNPs in porcine ovarian granulosa cells: (<b>A</b>) Representative TEM image in the control group. The cells were not exposed to SNPs. (<b>B</b>) Zoomed-in image of the white box in (<b>A</b>). (<b>C</b>) Zoomed-in image of the black box in (<b>B</b>). (<b>D</b>) Representative TEM image in the SNP-exposed group. The cells were exposed to 400 μg/mL SNPs for 48 h. (<b>E</b>) Zoomed-in image of the white box in (<b>D</b>). (<b>F</b>) Zoomed-in image of the black box in (<b>E</b>). Black arrows indicate vesicles in the cytoplasm and white arrows indicate SNPs. Scale bar, 5 μm (<b>A</b>,<b>D</b>), 2 μm (<b>B</b>,<b>E</b>), and 1 μm (<b>C</b>,<b>F</b>).</p>
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<p>SNP-induced oxidative stress in porcine ovarian granulosa cells. (<b>A</b>) Representative images of ROS staining by CLSM. Ovarian granulosa cells were exposed to control (<b>a</b>), 200 (<b>b</b>), 400 (<b>c</b>), and 800 (<b>d</b>) μg/mL SNPs for 48 h. Green indicates fluorescence of ROS and blue indicates the nucleus of ovarian granulosa cells. Scale bar, 30 μm. (<b>B</b>) Quantitative analysis of the intracellular ROS levels by FCM. (<b>C</b>) Corresponding analysis of fluorescence intensity in Figure (<b>B</b>). (<b>D</b>) Quantitative analysis of CAT mRNA levels by qPCR. (<b>E</b>) Quantitative analysis of SOD mRNA levels by qPCR. (<b>F</b>) Quantitative analysis of CAT enzyme activity by ELISA. (<b>G</b>) Quantitative analysis of SOD enzyme activity by ELISA. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control.</p>
Full article ">Figure 3 Cont.
<p>SNP-induced oxidative stress in porcine ovarian granulosa cells. (<b>A</b>) Representative images of ROS staining by CLSM. Ovarian granulosa cells were exposed to control (<b>a</b>), 200 (<b>b</b>), 400 (<b>c</b>), and 800 (<b>d</b>) μg/mL SNPs for 48 h. Green indicates fluorescence of ROS and blue indicates the nucleus of ovarian granulosa cells. Scale bar, 30 μm. (<b>B</b>) Quantitative analysis of the intracellular ROS levels by FCM. (<b>C</b>) Corresponding analysis of fluorescence intensity in Figure (<b>B</b>). (<b>D</b>) Quantitative analysis of CAT mRNA levels by qPCR. (<b>E</b>) Quantitative analysis of SOD mRNA levels by qPCR. (<b>F</b>) Quantitative analysis of CAT enzyme activity by ELISA. (<b>G</b>) Quantitative analysis of SOD enzyme activity by ELISA. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control.</p>
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<p>SNP-activated inflammatory response in porcine ovarian granulosa cells: (<b>A</b>–<b>D</b>) Quantitative analysis of the mRNA levels for IFN-α (<b>A</b>), IFN-β (<b>B</b>), IL-1β (<b>C</b>), and IL-6 (<b>D</b>) by qPCR. * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control.</p>
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<p>Cell apoptosis was activated in porcine ovarian granulosa cells after SNP exposures: (<b>A</b>) The apoptotic rate was determined by FCM. Q1-UL quadrant represents cell death caused by mechanical damage or necrotic cells, Q1-UR quadrant represents late apoptotic cells, Q1-LL quadrant represents the normal cells, and Q1-LR quadrant represents early apoptotic cells. (<b>B</b>) Quantification of the apoptotic rate. (<b>C</b>–<b>F</b>) Quantitative analysis of the mRNA levels for BCL-2 (<b>C</b>), BAX (<b>D</b>), Caspase-3 (<b>E</b>), and PARP (<b>F</b>) by qPCR. (<b>G</b>) Detection of BCL-2, BAX, cleaved Caspase-3, and cleaved PARP expressions by Western Blot. (<b>H</b>) Quantitative analysis of the band intensity for BCL-2, BAX, cleaved Caspase-3, and cleaved PARP. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control.</p>
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<p>Cell apoptosis was activated in porcine ovarian granulosa cells after SNP exposures: (<b>A</b>) The apoptotic rate was determined by FCM. Q1-UL quadrant represents cell death caused by mechanical damage or necrotic cells, Q1-UR quadrant represents late apoptotic cells, Q1-LL quadrant represents the normal cells, and Q1-LR quadrant represents early apoptotic cells. (<b>B</b>) Quantification of the apoptotic rate. (<b>C</b>–<b>F</b>) Quantitative analysis of the mRNA levels for BCL-2 (<b>C</b>), BAX (<b>D</b>), Caspase-3 (<b>E</b>), and PARP (<b>F</b>) by qPCR. (<b>G</b>) Detection of BCL-2, BAX, cleaved Caspase-3, and cleaved PARP expressions by Western Blot. (<b>H</b>) Quantitative analysis of the band intensity for BCL-2, BAX, cleaved Caspase-3, and cleaved PARP. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control.</p>
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<p>Tau inhibited SNP-induced oxidative stress in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>) Representative images of ROS staining by CLSM. Ovarian granulosa cells were exposed to control (<b>a</b>), 200 μg/mL SNP group (<b>b</b>), 400 μg/mL SNP (<b>c</b>), 800 μg/mL SNP (<b>d</b>), 10 mM Tau (<b>e</b>), 200 μg/mL SNP combined with 10 mM Tau (<b>f</b>), 400 μg/mL SNP combined with 10 mM Tau (<b>g</b>), and 800 μg/mL SNP combined with 10 mM Tau (<b>h</b>). Green indicates fluorescence of ROS and blue indicates the nucleus of ovarian granulosa cells. Scale bar, 30 μm. (<b>B</b>) Quantitative analysis of the intracellular ROS levels by FACS. (<b>C</b>) Corresponding analysis of the fluorescence intensity in Figure (<b>B</b>). (<b>D</b>) Quantitative analysis of CAT mRNA levels by qPCR. (<b>E</b>) Quantitative analysis of SOD mRNA levels by qPCR. (<b>F</b>) Quantitative analysis of CAT enzyme activity by ELISA. (<b>G</b>) Quantitative analysis of SOD enzyme activity by ELISA. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. SNP-exposed group.</p>
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<p>Tau inhibited SNP-induced oxidative stress in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>) Representative images of ROS staining by CLSM. Ovarian granulosa cells were exposed to control (<b>a</b>), 200 μg/mL SNP group (<b>b</b>), 400 μg/mL SNP (<b>c</b>), 800 μg/mL SNP (<b>d</b>), 10 mM Tau (<b>e</b>), 200 μg/mL SNP combined with 10 mM Tau (<b>f</b>), 400 μg/mL SNP combined with 10 mM Tau (<b>g</b>), and 800 μg/mL SNP combined with 10 mM Tau (<b>h</b>). Green indicates fluorescence of ROS and blue indicates the nucleus of ovarian granulosa cells. Scale bar, 30 μm. (<b>B</b>) Quantitative analysis of the intracellular ROS levels by FACS. (<b>C</b>) Corresponding analysis of the fluorescence intensity in Figure (<b>B</b>). (<b>D</b>) Quantitative analysis of CAT mRNA levels by qPCR. (<b>E</b>) Quantitative analysis of SOD mRNA levels by qPCR. (<b>F</b>) Quantitative analysis of CAT enzyme activity by ELISA. (<b>G</b>) Quantitative analysis of SOD enzyme activity by ELISA. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. SNP-exposed group.</p>
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<p>Tau inhibited SNP-activated inflammatory response in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>–<b>D</b>) Quantitative analysis of the mRNA levels for IFN-α (<b>A</b>), IFN-β (<b>B</b>), IL-1β (<b>C</b>), and IL-6 (<b>D</b>) by qPCR. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. SNP-exposed group.</p>
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<p>Tau inhibited SNP-activated inflammatory response in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>–<b>D</b>) Quantitative analysis of the mRNA levels for IFN-α (<b>A</b>), IFN-β (<b>B</b>), IL-1β (<b>C</b>), and IL-6 (<b>D</b>) by qPCR. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. SNP-exposed group.</p>
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<p>Tau inhibited SNP-induced cell apoptosis in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>) The apoptotic rate was determined by FCM. Q1-UL quadrant represents cell death caused by mechanical damage or necrotic cells, Q1-UR quadrant represents late apoptotic cells, Q1-LL quadrant represents the normal cells, and Q1-LR quadrant represents early apoptotic cells. (<b>B</b>) Quantification of the apoptotic rate. (<b>B</b>) Quantification of the apoptotic rate. (<b>C</b>–<b>F</b>) Quantitative analysis of the mRNA levels for BCL-2 (<b>C</b>), BAX (<b>D</b>), Caspase-3 (<b>E</b>), and PARP (F) by qPCR. (<b>G</b>) Detection of BCL-2, BAX, cleaved Caspase-3, and cleaved PARP expressions by Western Blot. (<b>H</b>) Quantitative analysis of the band intensity for BCL-2, BAX, cleaved Caspase-3, and cleaved PARP. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. SNP-exposed group.</p>
Full article ">Figure 8 Cont.
<p>Tau inhibited SNP-induced cell apoptosis in porcine ovarian granulosa cells. Ovarian granulosa cells were exposed to SNPs in the absence or presence of 10 mM Tau for 48 h: (<b>A</b>) The apoptotic rate was determined by FCM. Q1-UL quadrant represents cell death caused by mechanical damage or necrotic cells, Q1-UR quadrant represents late apoptotic cells, Q1-LL quadrant represents the normal cells, and Q1-LR quadrant represents early apoptotic cells. (<b>B</b>) Quantification of the apoptotic rate. (<b>B</b>) Quantification of the apoptotic rate. (<b>C</b>–<b>F</b>) Quantitative analysis of the mRNA levels for BCL-2 (<b>C</b>), BAX (<b>D</b>), Caspase-3 (<b>E</b>), and PARP (F) by qPCR. (<b>G</b>) Detection of BCL-2, BAX, cleaved Caspase-3, and cleaved PARP expressions by Western Blot. (<b>H</b>) Quantitative analysis of the band intensity for BCL-2, BAX, cleaved Caspase-3, and cleaved PARP. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 vs. Control. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. SNP-exposed group.</p>
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17 pages, 3011 KiB  
Article
New Eco-Cements Made with Marabou Weed Biomass Ash
by Moisés Frías, Ana María Moreno de los Reyes, Ernesto Villar-Cociña, Rosario García, Raquel Vigil de la Villa and Milica Vidak Vasić
Materials 2024, 17(20), 5012; https://doi.org/10.3390/ma17205012 - 14 Oct 2024
Viewed by 356
Abstract
Biomass ash is currently attracting the attention of science and industry as an inexhaustible eco-friendly alternative to pozzolans traditionally used in commercial cement manufacture (fly ash, silica fume, natural/calcined pozzolan). This paper explores a new line of research into Marabou weed ash (MA), [...] Read more.
Biomass ash is currently attracting the attention of science and industry as an inexhaustible eco-friendly alternative to pozzolans traditionally used in commercial cement manufacture (fly ash, silica fume, natural/calcined pozzolan). This paper explores a new line of research into Marabou weed ash (MA), an alternative to better-known conventional agro-industry waste materials (rice husk, bagasse cane, bamboo, forest waste, etc.) produced in Cuba from an invasive plant harvested as biomass for bioenergy production. The study entailed full characterization of MA using a variety of instrumental techniques, analysis of pozzolanic reactivity in the pozzolan/lime system, and, finally its influence on the physical and mechanical properties of binary pastes and mortars containing 10% and 20% MA replacement content. The results indicate that MA has a very low acid oxide content and a high loss on ignition (30%) and K2O content (6.9%), which produces medium–low pozzolanic activity. Despite an observed increase in the blended mortars’ total and capillary water absorption capacity and electrical resistivity and a loss in mechanical strength approximately equivalent to the replacement percentage, the 10% and 20% MA blended cements meet the regulatory chemical, physical, and mechanical requirements specified. Marabou weed ash is therefore a viable future supplementary cementitious material. Full article
(This article belongs to the Special Issue Advances in Rock and Mineral Materials)
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<p>The appearance of Marabou weed before and after thermal processing.</p>
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<p>Density distribution curves of the starting materials.</p>
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<p>Changes in the amount of fixed lime with reaction time.</p>
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<p>XRD diffractograms of the ash before and after 28 d. (C: calcite, Q: Quartz, K: Arkanite, and D: Dolomite).</p>
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<p>Ettringite and CSH gels (<b>left</b>) and detailed view of CSH gels (<b>right</b>).</p>
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<p>Langavant calorimetry: (<b>A</b>) heating curve and (<b>B</b>) hydration heat of the mortars.</p>
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<p>Total absorption curves in the mortars analyzed.</p>
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<p>Capillary water absorption in the mortars.</p>
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<p>Changes in electrical resistivity as a function of hydration time.</p>
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<p>Changes in compressive strength losses versus the OPC mortar.</p>
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<p>The relationship between compressive strength and resistivity.</p>
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<p>Pore distribution density curves at 90 d.</p>
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22 pages, 6806 KiB  
Review
A Bibliometric Analysis and Review on Applications of Industrial By-Products in Asphalt Mixtures for Sustainable Road Construction
by Adham Mohammed Alnadish, Madhusudhan Bangalore Ramu, Narimah Kasim, Aawag Mohsen Alawag and Abdullah O. Baarimah
Buildings 2024, 14(10), 3240; https://doi.org/10.3390/buildings14103240 - 12 Oct 2024
Viewed by 517
Abstract
The growing consumption of natural resources to meet the needs of road construction has become a significant challenge to environmental sustainability. Additionally, the increase in industrial by-products has raised global concerns due to their environmental impacts. The utilization of industrial by-products in asphalt [...] Read more.
The growing consumption of natural resources to meet the needs of road construction has become a significant challenge to environmental sustainability. Additionally, the increase in industrial by-products has raised global concerns due to their environmental impacts. The utilization of industrial by-products in asphalt mixtures offers an effective solution for promoting sustainable practices. The objective of this article is to conduct a bibliometric analysis and citation-based review to characterize and analyze the scientific literature on the use of steel slag aggregates, copper slag, phosphorus slag, bottom ash, fly ash, red mud, silica fume, and foundry sand in asphalt mixtures. Another aim is to identify research gaps and propose recommendations for future studies. The bibliometric analysis was conducted using VOSviewer software version 1.6.18, focusing on authors, co-authorship, bibliographic coupling, and countries. A total of 909 articles were selected for the bibliometric analysis. The findings indicate that more effort is needed to expand the application of industrial by-products in asphalt mixtures. Furthermore, these by-products should be utilized in different types of asphalt mixtures. The incorporation of industrial by-products into asphalt mixes also requires field validation and further laboratory investigations, particularly concerning aging and moisture resistance. In addition, the effects of chemical reactions involving industrial by-products on the long-term performance of asphalt layers should be evaluated. Finally, this article encourages engineers and researchers to intensify their efforts in utilizing industrial by-products for environmental sustainability. Full article
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<p>Approach for selecting the published articles for bibliometric analysis.</p>
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<p>Annual publications.</p>
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<p>Network visualization of steel slag aggregates.</p>
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<p>Network visualization of copper slag.</p>
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<p>Network visualization of phosphorus slag.</p>
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<p>Network visualization of bottom ash.</p>
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<p>Network visualization of fly ash.</p>
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<p>Network visualization of red mud.</p>
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<p>Network visualization of silica fume.</p>
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<p>Network visualization of foundry sand.</p>
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17 pages, 7186 KiB  
Article
Fumed-Si-Pr-Ald-Barb as a Fluorescent Chemosensor for the Hg2+ Detection and Cr2O72− Ions: A Combined Experimental and Computational Perspective
by Ghodsi Mohammadi Ziarani, Mahtab Rezakhani, Mehran Feizi-Dehnayebi and Stoyanka Nikolova
Molecules 2024, 29(20), 4825; https://doi.org/10.3390/molecules29204825 - 11 Oct 2024
Viewed by 363
Abstract
The surface of fumed silica nanoparticles was modified by pyridine carbaldehyde and barbituric acid to provide fumed-Si-Pr-Ald-Barb. The structure was identified and investigated through diverse techniques, such as FT-IR, EDX, Mapping, BET, XRD, SEM, and TGA. This nanocomposite was used to detect different [...] Read more.
The surface of fumed silica nanoparticles was modified by pyridine carbaldehyde and barbituric acid to provide fumed-Si-Pr-Ald-Barb. The structure was identified and investigated through diverse techniques, such as FT-IR, EDX, Mapping, BET, XRD, SEM, and TGA. This nanocomposite was used to detect different cations and anions in a mixture of H2O:EtOH. The results showed that fumed-Si-Pr-Ald-Barb can selectively detect Hg2+ and Cr2O72− ions. The detection limits were calculated at about 5.4 × 10−3 M for Hg2+ and 3.3 × 10−3 M for Cr2O72− ions. A computational method (DFT) was applied to determine the active sites on the Pr-Ald-Barb for electrophilic and nucleophilic attacks. The HOMO-LUMO molecular orbital was calculated by B3LYP/6-311G(d,p)/LANL2DZ theoretical methods. The energy gap for the Pr-Ald-Barb and Pr-Ald-Barb+ion complexes was predicted by the EHOMO and ELUMO values. The DFT calculation confirms the suggested experimental mechanism for interacting the Pr-Ald-Barb with ions. Full article
(This article belongs to the Special Issue Applications of Fluorescent Sensors in Food and Environment)
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Graphical abstract

Graphical abstract
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<p>(a) Fumed-Si-Pr-Ald; (b) Fumed-Si-Pr-Ald-Barb.</p>
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<p>Mapping of fumed-Si-Pr-Ald-Barb.</p>
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<p>N<sub>2</sub> adsorption-desorption for (a) Fumed-Si-Pr-Cl; (b) Fumed-Si-Pr-Ald; (c) Fumed-Si-Pr-Ald-Barb.</p>
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<p>SEM of fumed-Si-Pr-Ald-Barb.</p>
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<p>TGA analysis of (a) Fumed-Si-Pr-Cl; (b) Fumed-Si-Pr-Ald; (c) Fumed-Si-Pr-Ald-Barb.</p>
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<p>Fluorescence spectra of the aqueous suspended fumed-Si-Pr-Ald-Barb (2.5 mL, 0.02 g in 100 mL (H<sub>2</sub>O:EtOH/2:3)) by different cations (λₑ<sub>m</sub> = 300 nm, λₑ<sub>x</sub> = 375 nm).</p>
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<p>Fluorescence response of fumed-Si-Pr-Ald-Barb after adding different concentrations of Hg<sup>2+</sup> (10, 20, …, 300 µL) (λₑ<sub>m</sub> = 300 nm, λₑ<sub>x</sub> = 375 nm).</p>
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<p>Fluorescence spectra of the aqueous suspended fumed-Si-Pr-Ald-Barb (2.5 mL, 0.02 g in 100 mL (H<sub>2</sub>O:EtOH/2:3)) by different anions (λₑ<sub>m</sub> = 300 nm, λₑ<sub>x</sub> = 380 nm).</p>
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<p>Fluorescence response of fumed-Si-Pr-Ald-Barb after adding different concentrations of Cr₂O₇<sup>2−</sup> (10, 20, …, 300 µL) (λₑ<sub>m</sub> = 300 nm, λₑ<sub>x</sub> = 380 nm).</p>
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<p>The MEP surface of Pr-Ald-Barb generated from DFT calculation.</p>
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<p>The optimized geometries of (<b>a</b>) Pr-Ald-Barb; (<b>b</b>) Pr-Ald-Barb+Cr<sub>2</sub>O<sub>7</sub><sup>2−</sup>; (<b>c</b>,<b>d</b>) Pr-Ald-Barb+Hg<sup>2+</sup> under the DFT approach.</p>
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<p>The FMOs distribution of (<b>a</b>) Pr-Ald-Barb, (<b>b</b>) Pr-Ald-Barb+Cr<sub>2</sub>O<sub>7</sub><sup>2−</sup>, and (<b>c</b>) Pr-Ald-Barb+Hg<sup>2+</sup>.</p>
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<p>RDG surface of (<b>a</b>) Pr-Ald-Barb+Cr<sub>2</sub>O<sub>7</sub><sup>2−</sup> and (<b>b</b>) Pr-Ald-Barb+Hg<sup>2+</sup>.</p>
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<p>Synthesis of fumed-Si-Pr-Ald-Barb.</p>
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<p>The mechanism of fumed-Si-Pr-Ald-Barb.</p>
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21 pages, 5514 KiB  
Article
Long-Term Investigation of Nano-Silica Gel for Water Shut-Off in Fractured Reservoirs
by Ahmed Ali, Mustafa Al Ramadan and Murtada Saleh Aljawad
Gels 2024, 10(10), 651; https://doi.org/10.3390/gels10100651 - 11 Oct 2024
Viewed by 273
Abstract
Silicate gels have long been utilized as water shut-off agents in petroleum fields to address excessive water production. In recent years, nano-silica gel has emerged as a promising alternative to traditional silicate gels, offering potentially improved plugging performance. However, the long-term effectiveness of [...] Read more.
Silicate gels have long been utilized as water shut-off agents in petroleum fields to address excessive water production. In recent years, nano-silica gel has emerged as a promising alternative to traditional silicate gels, offering potentially improved plugging performance. However, the long-term effectiveness of these gels remains uncertain, posing challenges to sustained profitability. Therefore, a comprehensive study spanning 6 months was conducted on fractured and induced channel samples treated with nano-silica gel of 75/25 wt% (silica/activator) at 200 °F. A comparative analysis was performed with samples treated using polyacrylamide/polyethyleneimine PAM/PEI gel (9/1 wt%) to compare the performance of both systems. Throughout the aging period in formation water at 167 °F, endurance tests were conducted at regular intervals, complemented by computed tomography (CT) scans to monitor any potential degradation. The results revealed nano-silica gel’s superior long-term performance in plugging fractures and channels compared to PAM/PEI gel. Even after 6 months, the nano-silica gel maintained a remarkable 100% plugging efficiency at 1000 psi, with a maximum leak-off rate of 0.088 cc/min in the mid-fractured sample and 0.027 in the induced channel sample. In comparison, PAM/PEI gel exhibited a reduction in efficiency to 99.15% in the fractured sample (5.5 cc/min maximum leak-off rate) and 99.99% in the induced channel sample (0.036 cc/min maximum leak-off rate). These findings highlight the potential of nano-silica gel as a more durable water shut-off agent for managing water production in fractures and channels. Full article
(This article belongs to the Special Issue Gels for Oil and Gas Industry Applications (3rd Edition))
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<p>Fractured core sample images: (<b>a</b>) prepared core sample; (<b>b</b>) 3D CT scan image.</p>
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<p>Nano-silica gel treatment on the fractured sample.</p>
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<p>(<b>a</b>) CT scan of the fractured sample before nano-silica gel treatment; (<b>b</b>) CT scan of the fractured sample after nano-silica gel treatment; (<b>c</b>) color code scale.</p>
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<p>Nano-silica gel plugging performance over 6 months (fractured sample).</p>
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<p>PAM/PEI gel treatment in the fractured sample.</p>
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<p>(<b>a</b>) CT scan of the fractured sample before PAM/PEI gel treatment; (<b>b</b>) CT scan of the fractured sample after PAM/PEI gel treatment; (<b>c</b>) color code scale.</p>
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<p>PAM/PEI gel performance over 6 months (fractured sample).</p>
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<p>Performance comparison of nano-silica and PAM/PEI gels in the fractured sample.</p>
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<p>A 3D image of the induced channel sample of experiment 3.</p>
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<p>Nano-silica gel treatment on the induced channel sample.</p>
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<p>(<b>a</b>) CT scan of the induced channel before nano-silica gel treatment; (<b>b</b>) CT scan of the induced channel after nano-silica gel treatment; (<b>c</b>) color code scale.</p>
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<p>Nano-silica gel plugging efficiency over 6 months (induced channel sample).</p>
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<p>PAM/PEI gel treatment on the induced channel sample.</p>
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<p>(<b>a</b>) CT scan of the induced channel before PAM/PEI gel treatment; (<b>b</b>) CT scan of the induced channel after PAM/PEI gel treatment; (<b>c</b>) Color code scale.</p>
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<p>PAM/PEI gel performance over 6 months (induced channel sample).</p>
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<p>Comparison of plugging efficiency of nano-silica gel and PAM/PEI gel in the induced channel sample.</p>
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<p>Gel samples after curing: (<b>a</b>) nano-silica gel; (<b>b</b>) PAM/PEI gel.</p>
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<p>Stages of gel performance evaluation.</p>
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<p>Coreflooding equipment for gel treatment and endurance test.</p>
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41 pages, 6783 KiB  
Article
Stress-Responsive Gene Expression, Metabolic, Physiological, and Agronomic Responses by Consortium Nano-Silica with Trichoderma against Drought Stress in Bread Wheat
by Ghalia S. Aljeddani, Ragaa A. Hamouda, Amal M. Abdelsattar and Yasmin M. Heikal
Int. J. Mol. Sci. 2024, 25(20), 10954; https://doi.org/10.3390/ijms252010954 - 11 Oct 2024
Viewed by 497
Abstract
The exploitation of drought is a critical worldwide challenge that influences wheat growth and productivity. This study aimed to investigate a synergistic amendment strategy for drought using the single and combined application of plant growth-promoting microorganisms (PGPM) (Trichoderma harzianum) and biogenic [...] Read more.
The exploitation of drought is a critical worldwide challenge that influences wheat growth and productivity. This study aimed to investigate a synergistic amendment strategy for drought using the single and combined application of plant growth-promoting microorganisms (PGPM) (Trichoderma harzianum) and biogenic silica nanoparticles (SiO2NPs) from rice husk ash (RHA) on Saudi Arabia’s Spring wheat Summit cultivar (Triticum aestivum L.) for 102 DAS (days after sowing). The significant improvement was due to the application of 600 ppm SiO2NPs and T. harzianum + 600 ppm SiO2NPs, which enhanced the physiological properties of chlorophyll a, carotenoids, total pigments, osmolytes, and antioxidant contents of drought-stressed wheat plants as adaptive strategies. The results suggest that the expression of the studied genes (TaP5CS1, TaZFP34, TaWRKY1, TaMPK3, TaLEA, and the wheat housekeeping gene TaActin) in wheat remarkably enhanced wheat tolerance to drought stress. We discovered that the genes and metabolites involved significantly contributed to defense responses, making them potential targets for assessing drought tolerance levels. The drought tolerance indices of wheat were revealed by the mean productivity (MP), stress sensitivity index (SSI), yield stability index (YSI), and stress tolerance index (STI). We employed four databases, such as BAR, InterPro, phytozome, and the KEGG pathway, to predict and decipher the putative domains in prior gene sequencing. As a result, we discovered that these genes may be involved in a range of important biological functions in specific tissues at different developmental stages, including response to drought stress, proline accumulation, plant growth and development, and defense response. In conclusion, the sole and/or dual T. harzianum application to the wheat cultivar improved drought tolerance strength. These findings could be insightful data for wheat production in Saudi Arabia under various water regimes. Full article
(This article belongs to the Special Issue Advanced Plant Molecular Responses to Abiotic Stresses)
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<p>Stepwise of the green synthesis of silica nanoparticles (SiO<sub>2</sub> NPs) from rice husk ash.</p>
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<p>Optical and structural characterization of silica nanoparticles through: (<b>a</b>) ultra-violet (UV) spectroscopy; (<b>b</b>) zeta potential analysis; and (<b>c</b>) SEM-EDX analysis: scanning electron microscopy (SEM) and energy dispersive X-ray (EDX).</p>
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<p>XRD analysis of silica nanoparticles.</p>
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<p>Chemical characterization of silica nanoparticles through (<b>a</b>) Fourier transform infrared (FTIR) spectroscopy; (<b>b</b>) thermogravimetric analysis (TGA).</p>
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<p>Cell plot of 18 morphological and phenotypic traits of 65 DAS of <span class="html-italic">T. aestivum</span> under different water regimes (D0, control; 100% FC; D1, mild drought with 50% FC; D2, Severe drought with 30% FC). T0 (control: distilled water), T1 (<span class="html-italic">T. harzianum</span>), T2 (SiO<sub>2</sub>NPs (600 ppm(), and T3 (<span class="html-italic">T. harzianum</span> + SiO<sub>2</sub>NPs (600 ppm)). Abbreviations: PL (plant length; SHL (shoot length); RL (root length); SH/R (shoot/root length ratio); L. no (leaves number); LL (leaf length); LW (leaf width); LA (leaf area); LP (leaf perimeter); RW (root width); R. no (root number); FWSH (fresh weight of shoot); DWSH (dry weight of shoot); FWR (fresh weight of root); DWR (dry weight of root); WCSH (water content of shoot), and WCR (water content of root). The dark red color indicates the highest values, while the dark green color shows the lowest ones.</p>
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<p>Cell plot of 14 physiological and biochemical traits of 65 DAS of <span class="html-italic">T. aestivum</span> under different water regimes (D0, control; 100% FC; D1, mild drought with 50% FC; D2, severe drought with 30% FC). T0 (control: distilled water), T1 (<span class="html-italic">T. harzianum</span>), T2 (SiO<sub>2</sub>NPs (600 ppm)), and T3 (<span class="html-italic">T. harzianum</span> + SiO<sub>2</sub>NPs (600 ppm)). Abbreviations: EL (electrolyte leakage); Chl a (chlorophyll a); Chl b (chlorophyll b); Card (carotenoids); TP (total pigments); Carb (carbohydrates); ProT (protein); ProL (proline); TFC (total flavonoids content); TPC (total phenolic content); CAT (catalase); POD (peroxidase), and PPO (polyphenol oxidase). The dark red color indicates the highest values, while the dark blue color shows the lowest ones.</p>
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<p>Principal component analysis (PCA): (<b>a</b>) score plot; (<b>b</b>) biplot of all 32 combined vegetative traits (morphological, physiological and biochemical traits; (<b>c</b>) heatmap of partial correlation among the most significant morpho-physiological parameters at the heading stage of 65 DAS of <span class="html-italic">T. aestivum</span> under different water regimes. The dashed blue, green, and red circles represent the distribution of the treated plants under different water regimes. The dots were <span class="html-italic">T. aestivum</span> under different water regimes of FC, and the vectors (red arrows) were parameters. The green-to-red color gradient indicated positive correlation, while the green-to-violet color gradient indicated the negative correlation (see scale at the above right corner). Abbreviations are provided in previous figures.</p>
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<p>(<b>a</b>–<b>e</b>) Gene expression quantitative real-time PCR (qRT-PCR) of five drought-responsive genes at the heading stage of 65 DAS of <span class="html-italic">T. aestivum</span> under different water regimes. The genes are <span class="html-italic">TaP5CS1</span>, <span class="html-italic">TaZFP34</span>, <span class="html-italic">TaWRKY1</span>, <span class="html-italic">TaMPK3</span>, <span class="html-italic">TaLEA</span>, and the wheat house-keeping gene <span class="html-italic">TaActin</span>. ****, ***, **, * denote significant at <span class="html-italic">p</span> ≤ 0.0001, <span class="html-italic">p</span> ≤ 0.001, <span class="html-italic">p</span> ≤ 0.01, <span class="html-italic">p</span> ≤ 0.05, respectively, and ns donates non-significant difference.</p>
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<p>Agronomic attributes of 22 yield traits of 102 DAS of <span class="html-italic">T. aestivum</span> under different water regimes: (<b>a</b>) plot of partial contribution, (<b>b</b>) biplot, (<b>c</b>), and (<b>d</b>) T<sup>2</sup> contribution plots showing Hotelling’s T<sup>2</sup> values and the upper control limit (UCL) which represents in the red line while, the green line shows the median. Abbreviations: PL (plant length; SHL (shoot length); RL (root length); SH/R (shoot/root length ratio); L. no (leaf number); FLL (flag leaf length); FLW (leaf width); FLL/FLW (flag leaf length to weight ratio); FLA (leaf area); FLP (flag leaf perimeter); FLAn (flag leaf angle); RW (root width); R. no (root number); FWSH (fresh weight of shoot); DWSH (dry weight of shoot); FWR (fresh weight of root); DWR (dry weight of root); WCSH (water content of shoot) and WCR (water content of root); S. no (no. of spikelets/spike); FS (fertile spikelets) and SS (sterile spikelets).</p>
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<p>The kernel or grain parameters of 102 DAS of <span class="html-italic">T. aestivum</span> under different water regimes: (<b>a</b>) plot of loading coefficient and (<b>b</b>) partial contributions. Abbreviations: 20-GWt (20-grains weight); GW (grain width); GP (grain perimeter); GA (grain area); L (length of grain major axis); W (length of seed minor axis); AR (aspect ratio); Circ. (circulatory); Round (roundness) and Feret (Feret diameter).</p>
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<p>Drought tolerance traits of 102 DAS of <span class="html-italic">T. aestivum</span> under different water regimes: (<b>a</b>) scatter plot with heatmap and (<b>b</b>) partial contributions plot showing the intercorrelation between parameters. Abbreviations: mean productivity (MP); geometric productivity (GMP); tolerance index (TOL); stress susceptibility index (SSI); stress tolerance index (STI); harmonic mean of yield (HARM); yield stability index (YSI); relative drought index (RDI); drought resistance index (DRI); yield reduction ratio (YRR), and yield index (YI). The green color indicates positive correlation, purple color indicates the negative correlation, while the size of circles indicates the significance (see scale in the above–right corner).</p>
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<p>(<b>a</b>) The putative “wheat electronic fluorescent pictograph” tissue expression <span class="html-italic">of TaZFP34-TraesCS1D02G312200</span>, <span class="html-italic">TaWRKY1-TraesCS1B02G161400</span>, <span class="html-italic">TaMAPK3-TraesCS4A02G106400</span>, <span class="html-italic">TaLEA-TraesCS3A02G150800</span>, and <span class="html-italic">TaP5CS1-TraesCS3B02G395900</span> genes at different tissues and developmental stages; and (<b>b</b>) gene expression heatmap. The more intense the red color of the expression bar, the more gene expression detected according to [<a href="#B45-ijms-25-10954" class="html-bibr">45</a>,<a href="#B46-ijms-25-10954" class="html-bibr">46</a>].</p>
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<p>Experimental design and treatments of <span class="html-italic">T. aestivum</span> under different water regimes (D0, control; 100% FC; D1, mild drought with 50% FC; D2, Severe drought with 30% FC). T0 (control: distilled water), T1 (<span class="html-italic">T. harzianum</span>), T2 (SiO<sub>2</sub>NPs (600 ppm)), and T3 (<span class="html-italic">T. harzianum</span> + SiO<sub>2</sub>NPs (600 ppm)).</p>
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16 pages, 6290 KiB  
Article
Study of Styrene Butadiene Rubber Reinforced by Polybutadiene Liquid Rubber-Modified Silica
by Qing Liao, Xiao Tang, Jiao Tang, Jiaxiang Tang, Housheng Xia, Zhongyi Sheng, Jianping Zhou and Junfeng Niu
Polymers 2024, 16(20), 2866; https://doi.org/10.3390/polym16202866 - 10 Oct 2024
Viewed by 453
Abstract
The dispersion of silica in rubber systems and its interaction with rubber are two key factors in the preparation of rubber composites with excellent properties. In view of this, silica modified with terminal isocyanate-based polybutadiene liquid rubber (ITPB) is used to improve the [...] Read more.
The dispersion of silica in rubber systems and its interaction with rubber are two key factors in the preparation of rubber composites with excellent properties. In view of this, silica modified with terminal isocyanate-based polybutadiene liquid rubber (ITPB) is used to improve the dispersion effect of silica in rubber and enhance its interaction with the rubber matrix to improve the rubber’s performance. The impact of different modification conditions on the dispersion of silica and the properties of modified silica-filled rubber composites were studied by changing the amount of ITPB and the modification method of silica, including blending and chemical grafting. The experimental results show that ITPB is successfully grafted onto silica, and the use of modified silica improves the cross-linking density of rubber, promotes the rate of rubber vulcanization, and overcomes the shortcomings of the delayed vulcanization of silica itself. When the ratio of ITPB liquid rubber to silica equals 1:20, the comprehensive performance of rubber is the best, the ITPB-modified silica has a better dispersion effect in rubber, and the rolling resistance is slightly improved, with tensile strength reaching 12.6 MPa. The material demonstrates excellent overall performance and holds promise for applications in the rail, automotive, and electrical fields. Full article
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<p>FTIR spectra of unmodified and modified silica.</p>
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<p>Reaction mechanism of ITPB-modified silica.</p>
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<p>Thermogravimetric analysis (TGA) curve of ITPB-modified silica.</p>
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<p>Vulcanization characteristics of enhanced SBR composites.</p>
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<p>Thermogravimetric profiles of BR composites.</p>
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<p>The tensile stress–strain curve of the SBR composites.</p>
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<p>Schematic diagram of crosslinking reactions between chemically modified silica and rubber.</p>
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<p>(<b>a</b>) SEM image of P0-SBR rubber; (<b>b</b>) SEM image of P5-SBR rubber; (<b>c</b>) fracture surface of P0-SBR rubber; (<b>d</b>) fracture surface of P5-SBR rubber.</p>
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<p>Temperature curve of Tan δ for rubber.</p>
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20 pages, 1958 KiB  
Article
Assessing the Toxicity of Metal- and Carbon-Based Nanomaterials In Vitro: Impact on Respiratory, Intestinal, Skin, and Immune Cell Lines
by Juliana Carrillo-Romero, Gartze Mentxaka, Adrián García-Salvador, Alberto Katsumiti, Susana Carregal-Romero and Felipe Goñi-de-Cerio
Int. J. Mol. Sci. 2024, 25(20), 10910; https://doi.org/10.3390/ijms252010910 - 10 Oct 2024
Viewed by 467
Abstract
The field of nanotechnology has experienced exponential growth, with the unique properties of nanomaterials (NMs) being employed to enhance a wide range of products across diverse industrial sectors. This study examines the toxicity of metal- and carbon-based NMs, with a particular focus on [...] Read more.
The field of nanotechnology has experienced exponential growth, with the unique properties of nanomaterials (NMs) being employed to enhance a wide range of products across diverse industrial sectors. This study examines the toxicity of metal- and carbon-based NMs, with a particular focus on titanium dioxide (TiO2), zinc oxide (ZnO), silica (SiO2), cerium oxide (CeO2), silver (Ag), and multi-walled carbon nanotubes (MWCNTs). The potential health risks associated with increased human exposure to these NMs and their effect on the respiratory, gastrointestinal, dermal, and immune systems were evaluated using in vitro assays. Physicochemical characterisation of the NMs was carried out, and in vitro assays were performed to assess the cytotoxicity, genotoxicity, reactive oxygen species (ROS) production, apoptosis/necrosis, and inflammation in cell lines representative of the systems evaluated (3T3, Caco-2, HepG2, A549, and THP-1 cell lines). The results obtained show that 3T3 and A549 cells exhibit high cytotoxicity and ROS production after exposure to ZnO NMs. Caco-2 and HepG2 cell lines show cytotoxicity when exposed to ZnO and Ag NMs and oxidative stress induced by SiO2 and MWCNTs. THP-1 cell line shows increased cytotoxicity and a pro-inflammatory response upon exposure to SiO2. This study emphasises the importance of conducting comprehensive toxicological assessments of NMs given their physicochemical interactions with biological systems. Therefore, it is of key importance to develop robust and specific methodologies for the assessment of their potential health risks. Full article
(This article belongs to the Special Issue Toxicity of Nanoparticles)
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<p>TEM images of (<b>A</b>) NM 101, (<b>B</b>) NM 110, (<b>C</b>) NM 200, (<b>D</b>) NM 212, (<b>E</b>) NM 300 K, and (<b>F</b>) NM 400 at 0 h in milliQ water (stock) and 0 h and 24 h in DMEM, MEM, and RPMI.</p>
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<p>ROS production (%) of 3T3 (<b>A</b>), HepG2 (<b>B</b>), Caco-2 (<b>C</b>), and A549 (<b>D</b>) cell lines after exposure to all NMs (100 µg/mL and 50 µg/mL in NM 110 0.5 and NM 300 K 0.5) and to the negative (non-treated cells) and positive (H<sub>2</sub>O<sub>2</sub>) controls for 24 h. Results are expressed as means ± SD of six replicates per tested condition and three independent assays (<span class="html-italic">n</span> = 18). * Significantly different from negative control (C−) (<span class="html-italic">p</span> &lt; 0.05). ** (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Necrosis/apoptosis (%) of THP-1 cell line after exposure to all NMs (100 µg/mL and 50 µg/mL in NM 110 0.5 and NM 300 K 0.5) and to the negative (non-treated cells) and positive (Camptothecin and SDS for apoptosis and necrosis, respectively) controls for 24 h. Results are expressed as means ± SD of six replicates per tested condition and three independent assays (<span class="html-italic">n</span> = 18). * Significantly different from negative control (C−) (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) IL-1β, (<b>B</b>) TNF-α, (<b>C</b>) IL-8, and (<b>D</b>) IL-10 release in THP-1 cell line after exposure to all NMs (100 µg/mL and 50 µg/mL in NM 110 0.5 and NM 300 K 0.5) and to the negative (non-treated cells) and positive (LPS) controls for 24 h. Results are expressed as means ± SD of six replicates per tested condition and three independent assays (<span class="html-italic">n</span> = 18). * Significantly different from negative control (C−) (<span class="html-italic">p</span> &lt; 0.05).</p>
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19 pages, 3611 KiB  
Article
Effects of Silica Nanoparticles on the Piezoelectro-Elastic Response of PZT-7A–Polyimide Nanocomposites: Micromechanics Modeling Technique
by Usama Umer, Mustufa Haider Abidi, Syed Hammad Mian, Fahad Alasim and Mohammed K. Aboudaif
Polymers 2024, 16(20), 2860; https://doi.org/10.3390/polym16202860 - 10 Oct 2024
Viewed by 251
Abstract
By using piezoelectric materials, it is possible to convert clean and renewable energy sources into electrical energy. In this paper, the effect on the piezoelectro-elastic response of piezoelectric-fiber-reinforced nanocomposites by adding silica nanoparticles into the polyimide matrix is investigated by a micromechanical method. [...] Read more.
By using piezoelectric materials, it is possible to convert clean and renewable energy sources into electrical energy. In this paper, the effect on the piezoelectro-elastic response of piezoelectric-fiber-reinforced nanocomposites by adding silica nanoparticles into the polyimide matrix is investigated by a micromechanical method. First, the Ji and Mori–Tanaka models are used to calculate the properties of the nanoscale silica-filled polymer. The nanoparticle agglomeration and silica–polymer interphase are considered in the micromechanical modeling. Then, considering the filled polymer as the matrix and the piezoelectric fiber as the reinforcement, the Mori–Tanaka model is used to estimate the elastic and piezoelectric constants of the piezoelectric fibrous nanocomposites. It was found that adding silica nanoparticles into the polymer improves the elastic and piezoelectric properties of the piezoelectric fibrous nanocomposites. When the fiber volume fraction is 60%, the nanocomposite with the 3% silica-filled polyimide exhibits 39%, 31.8%, and 37% improvements in the transverse Young’s modulus ET, transverse shear modulus GTL, and piezoelectric coefficient e31 in comparison with the composite without nanoparticles. Furthermore, the piezoelectro-elastic properties such as ET, GTL, and e31 can be improved as the nanoparticle diameter decreases. However, the elastic and piezoelectric constants of the piezoelectric fibrous nanocomposites decrease once the nanoparticles are agglomerated in the polymer matrix. A thick interphase with a high stiffness enhances the nanocomposite’s piezoelectro-elastic performance. Also, the influence of volume fractions of the silica nanoparticles and piezoelectric fibers on the nanocomposite properties is studied. Full article
(This article belongs to the Special Issue Modeling of Polymer Composites and Nanocomposites)
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<p>Demonstration of the piezoelectric fibrous nanocomposite with a silica-nanoparticle-filled polymer matrix.</p>
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<p>Influence of nanoparticle volume fraction on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Influence of nanoparticle volume fraction on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Influence of interphase region on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Variation in (<b>a</b>) transverse Young’s modulus, (<b>b</b>) longitudinal shear modulus, (<b>c</b>) transverse shear modulus, and (<b>d</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub> of piezoelectric fibrous nanocomposite with interphase elastic modulus.</p>
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<p>Variation in (<b>a</b>) transverse Young’s modulus, (<b>b</b>) longitudinal shear modulus, (<b>c</b>) transverse shear modulus, and (<b>d</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub> of piezoelectric fibrous nanocomposite with interphase thickness.</p>
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<p>Influence of silica nanoparticle diameter on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Influence of silica nanoparticle dispersion quality on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Influence of silica nanoparticle dispersion quality on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing silica nanoparticles.</p>
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<p>Influence of nanoparticle types on the (<b>a</b>) longitudinal Young’s modulus, (<b>b</b>) transverse Young’s modulus, (<b>c</b>) longitudinal shear modulus, (<b>d</b>) transverse shear modulus, (<b>e</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub>, and (<b>f</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>33</sub> of the piezoelectric fibrous nanocomposite containing nanoparticles.</p>
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<p>Present predictions for Young’s modulus of silica-nanoparticle-filled PEEK nanocomposites compared to experimental data [<a href="#B45-polymers-16-02860" class="html-bibr">45</a>].</p>
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<p>Present predictions for Young’s modulus of silica-nanoparticle-filled nylon-6 nanocomposites compared to experimental data [<a href="#B46-polymers-16-02860" class="html-bibr">46</a>].</p>
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<p>Comparison between the results of the present model and results of [<a href="#B9-polymers-16-02860" class="html-bibr">9</a>] for (<b>a</b>) elastic constant <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>C</mi> </mrow> <mrow> <mn>33</mn> </mrow> </msub> </mrow> </semantics></math> and (<b>b</b>) piezoelectric coefficient <span class="html-italic">e</span><sub>31</sub> of PZT5-fiber-reinforced epoxy composites.</p>
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<p>Present predictions for Young’s modulus of silica-nanoparticle-filled P(MMA-co-MTC) nanocomposites compared to experimental data [<a href="#B50-polymers-16-02860" class="html-bibr">50</a>].</p>
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23 pages, 3251 KiB  
Article
Regeneration and Single Stage Batch Adsorber Design for Efficient Basic Blue-41 Dye Removal by Porous Clay Heterostructures Prepared from Al13 Montmorillonite and Pillared Derivatives
by Saheed A. Popoola, Hmoud Al Dmour, Rawan Al-Faze, Mohd Gulfam Alam, Souad Rakass, Hicham Oudghiri Hassani and Fethi Kooli
Materials 2024, 17(20), 4948; https://doi.org/10.3390/ma17204948 - 10 Oct 2024
Viewed by 550
Abstract
Porous clay heterostructures are a hybrid precursor between the pillaring process and organoclays. In this study, the organoclay was substituted by an aluminium intercalated species clay or pillared alumina clays. A porous clay heterostructure was successfully achieved from an aluminium intercalated species clay, [...] Read more.
Porous clay heterostructures are a hybrid precursor between the pillaring process and organoclays. In this study, the organoclay was substituted by an aluminium intercalated species clay or pillared alumina clays. A porous clay heterostructure was successfully achieved from an aluminium intercalated species clay, due to the easy exchange of the aluminium species by the cosurfactant and silica species. However, using alumina pillared clays, the porous clay heterostructures were not formed; the alumina species were strongly attached to clay sheets which made difficult their exchange with cosurfactant molecules. In this case, the silica species were polymerized and decorated the surface of the used materials as indicated by different characterization techniques. The specific surface area of the porous clay heterostructure material reached 880 m2/g, and total pore volume of 0.258 cc/g, while the decorated silica alumina pillared clays exhibited lower specific surface area values of 244–440 m2/g and total pore volume of 0.315 to 0.157 cc/g. The potential of the synthesized materials was evaluated as a basic blue-41 dye removal agent. Porous clay heterostructure material has a removal capacity of 279 mg/g; while the other materials exhibited lower removal capacities between 75 mg/g and 165 mg/g. The used regeneration method was related to the acidity of the studied materials. The acidity of the materials possessed an impact on the adopted regeneration procedure in this study, the removal efficiency was maintained at 80% of the original performance after three successive regeneration cycles for the porous clay heterostructure. The Langmuir isotherm characteristics were used to propose a single-stage batch design. Porous clay heterostructures with a higher removal capacity resulted in a decrease in the quantities needed to achieve the target removal percentage of the BB-41 dye from an aqueous solution. Full article
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<p>(<b>left</b>) PXRD patterns of raw clay, intercalated with the Al<sub>13</sub> species and calcined at different temperatures; (<b>right</b>) after reaction with C<sub>12</sub>amine and TEOS, then calcined at 550 °C.</p>
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<p>TEM micrographs of (<b>a</b>) raw Mt, (<b>b</b>) intercalated with the Al13 species (Al-IMt), (<b>c</b>) after calcination at 500 °C, (<b>d</b>) PAl-MtCH, and (<b>e</b>) PAl-Mt500CH.</p>
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<p>(<b>left</b>) <sup>29</sup>Si MAS NMR and (<b>right</b>) <sup>27</sup>Al MAS NMR of the different materials.</p>
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<p>TGA (black) and DTG (red) features of the different materials: (<b>a</b>) Mt, (<b>b</b>) Al-IMt, (<b>c</b>) PAl-IMtCH, (<b>d</b>) PAl-Mt(500), and (<b>e</b>) derived PAl-Mt(500)CH.</p>
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<p>N<sub>2</sub> adsorption-desorption isotherms of different materials: (<b>a</b>) Mt, (<b>b</b>) Al-IMt, (<b>c</b>) PAlMtCH, (<b>d</b>) Al-PMt(500), and (<b>e</b>) PMt(500)CH.</p>
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<p>Effect of on the removal properties of BB-41 dye, (<b>left</b>) PAl-IMtCH used mass and (<b>right</b>) initial BB-41 pH solution.</p>
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<p>Effect of the BB-41 initial concentration of the removal properties of the PAl-IMtCH (filled triangles) and PAl-PMt(500)CH (non-filled triangles).</p>
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<p>Variation of removal percentage (%) after different regeneration cycles.</p>
Full article ">Figure 9
<p>Required masses of PAl-IMtCH (<b>left</b>) and PAl-PMt(500)CH (<b>right</b>) to reduce different volumes (L) of BB-41 solutions (C<sub>i</sub> = 200 mg/L) to different removal percentages.</p>
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