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29 pages, 1560 KiB  
Review
Unraveling the Biological Properties of Whey Peptides and Their Role as Emerging Therapeutics in Immune Tolerance
by Laura Quintieri, Anna Luparelli, Leonardo Caputo, William Schirinzi, Federica De Bellis, Leonardo Smiriglia and Linda Monaci
Nutrients 2025, 17(6), 938; https://doi.org/10.3390/nu17060938 - 7 Mar 2025
Abstract
Whey is a natural by-product of the cheese-making process and represents a valuable source of nutrients, including vitamins, all essential amino acids and proteins with high quality and digestibility characteristics. Thanks to its different techno-functional characteristics, such as solubility, emulsification, gelling and foaming, [...] Read more.
Whey is a natural by-product of the cheese-making process and represents a valuable source of nutrients, including vitamins, all essential amino acids and proteins with high quality and digestibility characteristics. Thanks to its different techno-functional characteristics, such as solubility, emulsification, gelling and foaming, it has been widely exploited in food manufacturing. Also, advances in processing technologies have enabled the industrial production of a variety of whey-based products exerting biological activities. The beneficial properties of whey proteins (WPs) include their documented effects on cardiovascular, digestive, endocrine, immune and nervous systems, and their putative role in the prevention and treatment of non-communicable diseases (NCDs). In this regard, research on their application for health enhancement, based on the optimization of product formulation and the development of pharmaceuticals, is highly relevant. Beyond the health and nutritionally relevant effects as in in vivo animal studies, the allergenicity of WPs and WP hydrolysates is also herein tackled and discussed, as well as their potential role as therapeutics for immune tolerance and so-called tolerogenic effects. Grounded on the WPs’ health-promoting functions, this paper presents the latest research showing the potential of whey-derived peptides as an alternative strategy in NCD treatment. This work also reports a careful analysis of their current use, also revealing which obstacles limit their full exploitation, thus highlighting the future challenges in the field. Concluding, safety considerations, encompassing WP allergenicity, are also discussed, providing some insights on the role of WPs and peptides in milk allergen immunotolerance. Full article
(This article belongs to the Topic Novel Therapeutic Nutrient Molecules, 2nd Volume)
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<p>Whey proteins and main biological and technological properties.</p>
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<p>Comparative representation of the tolerogenic <span class="html-italic">versus</span> allergic response to food antigens.</p>
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10 pages, 2996 KiB  
Article
Simulation of Shock-to-Detonation Transition by OpenFOAM
by Thien Xuan Dinh, Masatake Yoshida and Shuichi Ishikura
Aerospace 2025, 12(3), 214; https://doi.org/10.3390/aerospace12030214 - 7 Mar 2025
Viewed by 47
Abstract
Shock-to-detonation transition (SDT) is the detonation of explosive charge triggered by the shock pressure from a nearby detonated explosive or an impact at high speed. A good prediction of SDT is a key in the design of explosives’ use, storage, and transportation. Typically, [...] Read more.
Shock-to-detonation transition (SDT) is the detonation of explosive charge triggered by the shock pressure from a nearby detonated explosive or an impact at high speed. A good prediction of SDT is a key in the design of explosives’ use, storage, and transportation. Typically, SDT simulation must use designated commercial software; therefore, a high license cost is necessary. This paper presents a simulation of SDT by a cost-effective hydrodynamic code developed on an open-source code framework, OpenFOAM. The code adopted the multi-material Eulerian method, Ignition and Growth reaction rate model, and Riemann solver to solve the shock-induced detonation phenomenon. The code was verified by a Pop plot calculation and a sympathetic detonation simulation. In the Pop plot calculation, the distance-of-run to the detonation of Composition B depending on the initial shock pressure was simulated. The reactant and product phases of Composition B were modeled by the Jone–Wilkins–Lee (JWL) equation of state (EOS). The aluminum plate used to create the initial shock pressure was modeled by shock Mie–Gruneisen (MG) EOS. The predicted distance-of-run against the initial shock pressure was in good agreement with an empirical correlation and experimental data. In the sympathetic detonation simulation, the charge explosive and nearby explosive were Composition B and were modeled by JWL EOS as in the Pop plot calculation and the plexiglass gap was modeled by MG EOS. The simulated critical gap for the sympathetic detonation was well predicted as in the other published data. This implies that the code is valid for SDT simulation. In addition, it is a cost-effective simulation, since the code was developed on open-source code, so massive computation can then be run without license costs. Full article
(This article belongs to the Section Astronautics & Space Science)
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<p>The pressure history for the initial shock pressure of 4.35 GPa.</p>
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<p>The run to detonation with impact pressure.</p>
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<p>The gap test simulation configuration.</p>
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<p>The distribution of the density (<b>a</b>) and the product mass fraction (<b>b</b>). The shock moves from left to right. The line is the initial position of the gap.</p>
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<p>The shock propagation in a gap of 15 mm with a charge diameter of 32 mm.</p>
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<p>The shock propagation in a gap of 30 mm and with a charge diameter of 32 mm.</p>
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<p>The critical gap for sympathetic detonation, Kubota et al. [<a href="#B17-aerospace-12-00214" class="html-bibr">17</a>].</p>
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12 pages, 15543 KiB  
Article
Enhancing the Fatigue Properties of Rigid Polyurethane Foam by Dissipating the Mechanical Energy of Rubber Powder
by Jinlong Ju, Nana Yang, Yifei Zhang, Lei Yu, Guolu Ma and Wenhua Wu
Polymers 2025, 17(5), 705; https://doi.org/10.3390/polym17050705 - 6 Mar 2025
Viewed by 100
Abstract
Rigid polyurethane-based foam is an ideal choice for sandwich-panel-filling materials due to its high strength, low thermal conductivity, high adhesion, and high chemical resistivity. Since sandwich panel materials often face cyclic mechanical loads during their service, it is significant to study the design [...] Read more.
Rigid polyurethane-based foam is an ideal choice for sandwich-panel-filling materials due to its high strength, low thermal conductivity, high adhesion, and high chemical resistivity. Since sandwich panel materials often face cyclic mechanical loads during their service, it is significant to study the design methods of fatigue-resistant rigid polyurethane foam and its fatigue failure mechanism to improve the performance of sandwich-panel-filling materials. In this study, a fatigue-resistant rubber powder/polyurethane composite material was prepared by introducing rubber powder, and its fatigue failure mechanism was systematically studied. The static mechanical test results indicate that with the introduction of 20% rubber powder, the compressive strength (at 85% strain) increased to 588 kPa. Additionally, thanks to the excellent energy absorption and dissipation properties of rubber powder, it can effectively dissipate mechanical energy during cyclic loading. The fatigue test results show that after the introduction of rubber powder, the fatigue life of the polyurethane foam material increases from 10,258 cycles (for PU, stress ratio 0.6) to 45,987 cycles (for 20R-PU, stress ratio 0.6). This study not only proves the fact that rubber powder can improve the fatigue performance of foam materials but also provides a potential option for the design of high-performance filling materials. Full article
(This article belongs to the Section Polymer Physics and Theory)
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<p>The design of the rubber/PU composite.</p>
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<p>Specimens for (<b>a</b>) tensile test and (<b>b</b>) compression test.</p>
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<p>The microstructure of the (<b>a</b>) PU; (<b>b</b>) 10R-PU; (<b>c</b>) 20R-PU; (<b>d</b>) 30R-PU; and (<b>e</b>) 40R-PU rubber/PU composite. (<b>f</b>) The typical structure of rubber in 40R-PU foam; (<b>g</b>,<b>h</b>) the electron energy scattering spectrum and elemental mapping of 40R-PU.</p>
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<p>(<b>a</b>) The microstructure and (<b>b</b>) element distribution information of the rubber/PU interface, the red marked part is rubber particles.</p>
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<p>Compressive curve for PU and rubber/PU composite foams.</p>
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<p>(<b>a</b>) Compressive strength and (<b>b</b>) collapse strain/strength for PU and rubber/PU composite foams.</p>
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<p>Tensile curve for PU and rubber/PU composite foams.</p>
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<p>(<b>a</b>) Fracture strength, and (<b>b</b>) fracture strain for PU and rubber/PU composite foams during tensile test.</p>
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<p>Curves depicting the ratio between relative stress and cycles to failure for the composite foams.</p>
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<p>Fatigue fracture interface of the rubber/PU composite (Relative stress 0.6). The microstructure of PU with various load cycles: (<b>a</b>) ×100, (<b>b</b>) ×1000, and (<b>c</b>) ×10,000 (the crack area is between the red lines). The microstructure of 20R-PU with various load cycles: (<b>d</b>) ×100, (<b>e</b>) ×1000, and (<b>f</b>) ×10,000.</p>
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<p>Mechanism of toughening polyurethane foam with rubber powder, the arrows point to the energy dissipation process of the composite foam material.</p>
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17 pages, 3264 KiB  
Article
Differential Enzymatic Hydrolysis: A Study on Its Impact on Soy Protein Structure, Function, and Soy Milk Powder Properties
by Qian Li, Baoyue Chang, Guo Huang, Di Wang, Yue Gao, Zhijun Fan, Hongbo Sun and Xiaonan Sui
Foods 2025, 14(5), 906; https://doi.org/10.3390/foods14050906 - 6 Mar 2025
Viewed by 140
Abstract
Protein constitutes the primary nutrient in soy, and its modifications are intricately linked to the properties of the soy milk powder. This study employed six main commercial enzymes (bromelain, neutrase, papain, trypsin, flavourzyme, and alcalase) to investigate the impact of enzymatic hydrolysis on [...] Read more.
Protein constitutes the primary nutrient in soy, and its modifications are intricately linked to the properties of the soy milk powder. This study employed six main commercial enzymes (bromelain, neutrase, papain, trypsin, flavourzyme, and alcalase) to investigate the impact of enzymatic hydrolysis on the structural and functional properties of soy protein isolate (SPI), as well as its influence on the physicochemical properties of soy milk powder. The findings indicated that each of enzymes exhibits distinct specificity, with the degree of hydrolysis following the order: alcalase > flavourzyme > papain > bromelain > neutrase > trypsin. Enzymatic hydrolysis facilitates the unfolding of SPI, leading to the exposure of chromogenic fluorophores and hydrophobic amino acid residues, which in turn promotes an increase in free sulfhydryl content. Concurrently, this process induces the transformation of α-helix and β-sheet into β-turn and random coil. The enzyme modification enhances the solubility, emulsification, and foaming activities of SPI and significantly augment its antioxidant properties (p < 0.05). However, this enzymatic treatment adversely affects the stability of its emulsification and foaming properties. Subsequent to enzymatic hydrolysis, soy milk powder demonstrated a reduction in particle size and an improvement in solubility, which significantly enhanced its flavor profile. In summary, alcalase offers substantial advantages in augmenting the functional properties of SPI and increasing the solubility of soy milk powder. However, this process adversely affects the flavor profile of soy milk powder, a consequence attributed to the broad hydrolysis specificity of alcalase. Full article
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<p>Study flow diagrams for the study topics (<b>A</b>), and flowchart for preparation in the study of soy protein hydrolysate and enzymatic hydrolysis of soy milk powder (<b>B</b>).</p>
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<p>The degree of hydrolysis (<b>A</b>), SDS-PAGE analysis (<b>B</b>) including: Lane M: low protein molecular weight marker; Lane A: SPI; Lane B: N-SPIH; Lane C: A-SPIH; Lane D: B-SPIH; Lane E: F-SPIH; Lane F: P-SPIH; Lane G: T-SPIH, UV absorbance spectra (<b>C</b>), and fluorescence spectra of several protein hydrolysates (<b>D</b>). Where, different superscript letters indicate significant differences (same as below).</p>
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<p>FT-IR spectra of different samples.</p>
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<p>Solubility of hydrolysis of soy milk powder by different enzymes. Where, different superscript letters indicate significant differences (same as below).</p>
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<p>The SEM of hydrolysis of soy milk powder by different enzymes, including: SP (<b>A</b>), A-SPH (<b>B</b>), F-SPH (<b>C</b>), P-SPH (<b>D</b>), B-SPH (<b>E</b>), N-SPH (<b>F</b>), and T-SPH (<b>G</b>).</p>
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<p>Score chart of flavor principal components (<b>A</b>) and radar map (<b>B</b>) of soy milk powder.</p>
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18 pages, 7858 KiB  
Article
Transcriptome Analysis of Onobrychis viciifolia During Seed Germination Reveals GA3-Inducible Genes Associated with Phenylpropanoid and Hormone Pathways
by Yanyan Luo, Kun Wang, Jiao Cheng and Lili Nan
Int. J. Mol. Sci. 2025, 26(5), 2335; https://doi.org/10.3390/ijms26052335 - 6 Mar 2025
Viewed by 72
Abstract
Sainfoin (Onobrychis viciifolia) is a type of leguminous plant with high feeding value. It contains a high concentration of tannins at all growth stages, which can precipitate soluble proteins and form a large number of persistent foams in the rumen, so [...] Read more.
Sainfoin (Onobrychis viciifolia) is a type of leguminous plant with high feeding value. It contains a high concentration of tannins at all growth stages, which can precipitate soluble proteins and form a large number of persistent foams in the rumen, so that ruminant livestock will not develop dilatation disease during green feeding and grazing. The germination rate of O. viciifolia seeds is very low under natural conditions. The preliminary experiment showed that 600 mg/L GA3 treatment significantly improved the germination rate and seed vitality of sainfoin seeds. In comparison to CK, GA3 significantly decreased the relative content of endogenous inhibitors, with the most notable reduction observed in 4-nitroso-N-phenyl-benzenamine. Therefore, we selected the dry seed stage (GZ), imbibition stage (XZ), split stage (LK), and radicle emergence stage (MF) of four different germination stages treated with GA3 for transcriptome analysis. RNA-seq identified 1392, 2534 and 4284 differentially expressed genes (DEGs) in GZ vs. XZ, XZ vs. LK, and LK vs. MF, respectively. During seed germination, DEGs are mainly enriched in hormone signaling and phenylalanine biosynthesis pathways, and up-down-regulation of these DEGs may alter hormone and secondary metabolite levels to promote germination. The results of weighted gene co-expression network construction (WGCNA) also indicate that plant hormone signal transduction and phenylpropanoid biosynthesis play a dominant role in GA3-induced seed germination. In conclusion, the combined analysis of transcriptomic and physiological indicators provided new insights into seed germination and a theoretical basis for further study of candidate genes. Full article
(This article belongs to the Special Issue Advance in Plant Abiotic Stress: 2nd Edition)
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<p>Effects of GA<sub>3</sub> on the germination rate and seed vigor of sainfoin seeds. (<b>A</b>) Effect of GA<sub>3</sub> treatment on the seed germination phenotype of sainfoin; (<b>B</b>) Effect of GA<sub>3</sub> treatment on seed germination rate; (<b>C</b>,<b>E</b>) Effect of GA<sub>3</sub> treatment on plumule and radicle lengths; (<b>D</b>,<b>F</b>) Effect of GA<sub>3</sub> treatment on seed viability. Error bars represent the standard deviation (SD) of six replicates. Bars with different lowercase letters were significantly different according to Duncan’s multiple range test (<span class="html-italic">p</span> &lt; 0.05). “*” represents a highly significant difference according to the <span class="html-italic">t</span>-test.</p>
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<p>Effects of GA<sub>3</sub> on endogenous inhibitors in sainfoin seeds.</p>
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<p>Statistical analysis of differentially expressed genes during germination of sainfoin seeds under GA<sub>3</sub> treatment. (<b>A</b>) Number of total genes, up- and down-regulated DEGs in different comparison groups; (<b>B</b>) Venn diagram showing co-expressed genes of the three comparison groups; (<b>C</b>) Venn diagram of up-regulated genes; (<b>D</b>) Venn diagram of down-regulated genes. DEGs, differentially expressed genes; up, up-regulated DEGs; down, down-regulated DEGs.</p>
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<p>GO and KEGG enrichment analysis of DEGs during germination. (<b>A</b>) GO analysis of DEGs in GA<sub>3</sub>-treated sainfoin seeds during the germination process; (<b>B</b>) KEGG analysis of DEGs in GA<sub>3</sub>-treated sainfoin seeds during germination process.</p>
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<p>Analysis of hormone signal transduction pathways and endogenous hormone concentrations involved in the germination of sainfoin seeds. (<b>A</b>) Expression profile of DEGs associated with the ZA pathway; (<b>B</b>) Expression profile of DEGs associated with GA pathway; (<b>C</b>) Expression profile of DEGs associated with ABA pathway; (<b>D</b>) Expression profile of DEGs associated with IAA pathway; (<b>E</b>) Comparison of ZT, IAA, GA<sub>3</sub>, and ABA concentrations in sainfoin seeds under GA<sub>3</sub> treatment. Sample names are shown at the bottom of the figure. Expression levels, ranging from blue to red, indicate high to low expression of genes. Different lowercase letters indicate significant differences between GA<sub>3</sub>-treated seeds at different germination stages according to Duncan’s multiple range test (<span class="html-italic">p</span> &lt; 0.05). The error bar represents three repeated standard deviations (SD).</p>
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<p>Analysis of phenylalanine biosynthesis pathways involved in the germination of sainfoin seeds. Sample names are shown at the bottom of the figure. Expression levels, ranging from blue to red, indicate high to low expression of genes. All data shown indicate the average mean of three biological replicates (<span class="html-italic">n</span> = 3).</p>
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<p>WGCNA of genes during GA<sub>3</sub>-treated sainfoin seed germination. (<b>A</b>) Cluster dendrograms showing the co-expression modules identified by WGCNA. Each leaf in the tree represents a gene. Branches correspond to highly interconnected gene modules. The color rows below the dendrograms represent the division of modules based on clustering results and the 14 merged modules based on hierarchical clustering; (<b>B</b>) Module-sample relationship based on the Pearson correlation coefficient. Each row corresponds to a module and is represented by a different color. Each column corresponds to samples from different stages of seed germination.</p>
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<p>qRT-PCR validation of nine candidate DEGs. The error bar represents three repeated standard deviations (SD).</p>
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<p>Regulation model of exogenous GA<sub>3</sub> treatment promoting sainfoin seed germination.</p>
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16 pages, 7861 KiB  
Article
Preparation and Performance Evaluation of Environmentally Friendly Foam Hydrogel Based on Polyvinyl Alcohol/Organic Titanium Crosslinking Agent
by Ru Ma, Gaoshen Su, Ya Nie, Huan Yang and Xiaorong Yu
Gels 2025, 11(3), 181; https://doi.org/10.3390/gels11030181 - 6 Mar 2025
Viewed by 107
Abstract
Foam and hydrogel profile control are commonly utilized water-blocking and profile modification techniques in oil fields. This study integrates a foam system with a gel system, employing an organic titanium crosslinking agent to crosslink polyvinyl alcohol, thereby forming a gel system. Concurrently, a [...] Read more.
Foam and hydrogel profile control are commonly utilized water-blocking and profile modification techniques in oil fields. This study integrates a foam system with a gel system, employing an organic titanium crosslinking agent to crosslink polyvinyl alcohol, thereby forming a gel system. Concurrently, a gas-evolving agent is incorporated into the system to induce in situ foaming, thereby creating an environmentally benign foam gel system. The fundamental constituents of this system comprise 2 wt% to 5 wt% polyvinyl alcohol, 2 wt% to 4 wt% crosslinker, and 0.3 wt% to 0.9 wt% gas-generating agent. By varying the amounts of each component, the strength grade, gelation time, and foaming volume of the foam gel can be effectively adjusted. The results of the temperature resistance performance evaluation indicate that within the temperature range of 80 °C to 130 °C, the gelation performance of the foam gel is stable and good. At 90 °C, the foam gel can remain stable for 340 days with minimal strength variation. The plugging experiments indicate that the formulated foam gel system exhibits superior injectability and can effectively seal the sand-filled tube model, achieving a blocking efficiency of up to 96.36%. Full article
(This article belongs to the Special Issue Gels in the Oil Field)
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<p>Effect of the synergistic effect of polyvinyl alcohol and crosslinker concentration on the gelatinization grade of foam gel.</p>
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<p>Effect of the synergistic effect of polyvinyl alcohol and crosslinker concentration on the gelatinization volume of foam gel.</p>
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<p>Effect of the synergistic effect of polyvinyl alcohol and crosslinker concentration on the gelatinization time of foam gel.</p>
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<p>Experimental phenomena of gelatinization of 5 wt% polyvinyl alcohol concentration under different crosslinker concentrations.</p>
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<p>The effect of gas-generating agent concentration on the gel strength, gelation time, and gel volume of foam gels.</p>
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<p>Experimental phenomena of foam gel formation under different gas-generating agent concentrations.</p>
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<p>FTIR analysis of PVA foam gel.</p>
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<p>SEM: foam gel microstructure. (<b>a</b>) Internal structure of the gel; (<b>b</b>) Gel surface structure.</p>
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<p>Morphological characteristics of foam gels at 4× magnification. (<b>a</b>) Initial state of polyvinyl alcohol foam gel; (<b>b</b>) State of polyvinyl alcohol foam gel after 100 days at 90 °C; (<b>c</b>) State of polyvinyl alcohol foam gel after 200 days at 90 °C; (<b>d</b>) State of polyvinyl alcohol foam gel after 362 days at 90 °C.</p>
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<p>Weight loss rate–temperature variation of polyvinyl alcohol gel/foam gel.</p>
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<p>Effect of salt concentration on the properties of foam gels.</p>
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<p>Effect of temperature on the properties of foam gels.</p>
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<p>Viscoelastic analysis of gels.</p>
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<p>Relationship between volume retention rate and defoaming rate with time.</p>
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<p>Schematic diagram of the displacement experimental setup.</p>
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28 pages, 4600 KiB  
Article
Utilization of Coniferous and Deciduous Tree and Paper Ashes as Fillers of Rigid Polyurethane/Polyisocyanurate (PU/PIR) Foams
by Joanna Liszkowska, Magdalena Stepczyńska, Andrzej Trafarski, Justyna Miłek and Tomasz Karasiewicz
Materials 2025, 18(5), 1165; https://doi.org/10.3390/ma18051165 - 5 Mar 2025
Viewed by 271
Abstract
Five series of rigid polyurethane–polyisocyanurate (RPU/PIR) foams were obtained. They were modified by ashes from burning paper (P) and wood: conifers (pine—S, spruce—S’) and deciduous trees (oak—D, birch—B). The ash was added to rigid polyurethane–polyisocyanurate foams (PU/PIR). In this way, five series of [...] Read more.
Five series of rigid polyurethane–polyisocyanurate (RPU/PIR) foams were obtained. They were modified by ashes from burning paper (P) and wood: conifers (pine—S, spruce—S’) and deciduous trees (oak—D, birch—B). The ash was added to rigid polyurethane–polyisocyanurate foams (PU/PIR). In this way, five series of foams with different ash contents (from 1 to 9% wt.) were obtained: PP, PS, PD, PS’, PB. The model foam (reference—W) was obtained without filler. The basic properties, physico-mechanical, and thermal properties of the ashes and obtained foams were examined. It was specified, among other things, the cellular structure by scanning electron microscopy (SEM), and changes in chemical structure by Fourier-transform infrared spectroscopy (FTIR) were compared. The obtained foams were also subjected to thermostating in a circulating air dryer in increased temperature (120 °C) for 48 h. Ash tests showed that their skeletal density is about 2.9 g/cm3, and the pH of their solutions ranges from 9 to 13. The varied color of the ashes affected the color of the foams. SEM-EDS tests showed the presence of magnesium, calcium, silicon, potassium, aluminum, phosphorus, sodium, and sulfur in the ashes. Foam tests showed that pine ash is the most beneficial for foams, because it increases their compressive strength three times compared to W foam and improves their thermal stability. All ashes cause the residue after combustion of the foams (retention) to increase and the range of combustion of the samples to decrease. Full article
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<p>Ashes used for foams: (<b>a</b>) pine, (<b>b</b>) spruce, (<b>c</b>) birch, (<b>d</b>) paper, (<b>e</b>) oak.</p>
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<p>Ashes in resin for SEM-EDS.</p>
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<p>SEM images of ashes.</p>
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<p>DSC–EDS of ashes: (<b>a</b>) paper—P; (<b>b</b>) pine—S; (<b>c</b>) spruce—S’; (<b>d</b>) birch—B; (<b>e</b>) oak—D.</p>
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<p>DSC–EDS of ashes: (<b>a</b>) paper—P; (<b>b</b>) pine—S; (<b>c</b>) spruce—S’; (<b>d</b>) birch—B; (<b>e</b>) oak—D.</p>
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<p>FTIR of ashes.</p>
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<p>DSC of ashes.</p>
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<p>TGA and DTG of ashes.</p>
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<p>FTIR of foams with ashes: W—reference; PB9—with birch; PD7—witch oak; PS’9—with spruce; PS7—with pine; PP9—with paper.</p>
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<p>TGA and DTG of foams.</p>
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<p>Retention of foam content ashes.</p>
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<p>Dependence of flame range on ash content in foams.</p>
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<p>Dependence of water absorption on the content of ash in foam.</p>
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<p>Dependence of absorbability on the content of ash in foam.</p>
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<p>Dependence of compressive strength on ash content in foams.</p>
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<p>Foam structure.</p>
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16 pages, 3962 KiB  
Article
Ark Shell-Derived Peptides AWLNH (P3) and PHDL (P4) Mitigate Foam Cell Formation by Modulating Cholesterol Metabolism and HO-1/Nrf2-Mediated Oxidative Stress in Atherosclerosis
by Chathuri Kaushalya Marasinghe and Jae-Young Je
Mar. Drugs 2025, 23(3), 111; https://doi.org/10.3390/md23030111 - 5 Mar 2025
Viewed by 85
Abstract
Atherosclerosis, a leading contributor to cardiovascular diseases (CVDs), is characterized by foam cell formation driven by excessive lipid accumulation in macrophages and vascular smooth muscle cells. This study elucidates the anti-atherosclerotic potential of AWLNH (P3) and PHDL (P4) peptides by assessing their effects [...] Read more.
Atherosclerosis, a leading contributor to cardiovascular diseases (CVDs), is characterized by foam cell formation driven by excessive lipid accumulation in macrophages and vascular smooth muscle cells. This study elucidates the anti-atherosclerotic potential of AWLNH (P3) and PHDL (P4) peptides by assessing their effects on foam cell formation, lipid metabolism, and oxidative stress regulation. P3 and P4 effectively suppressed intracellular lipid accumulation in RAW264.7 macrophages and human aortic smooth muscle cells (hASMCs), thereby mitigating foam cell formation. Mechanistically, both peptides modulated cholesterol homeostasis by downregulating cholesterol influx mediators, cluster of differentiation 36 (CD36), and class A1 scavenger receptor (SR-A1), while upregulating cholesterol efflux transporters ATP-binding cassette subfamily A member 1 (ABCA1) and ATP-binding cassette subfamily G member 1 (ABCG1). The activation of peroxisome proliferator-activated receptor-gamma (PPAR-γ) and liver X receptor-alpha (LXR-α) further substantiated their role in promoting cholesterol efflux and restoring lipid homeostasis. Additionally, P3 and P4 peptides exhibited potent antioxidative properties by attenuating reactive oxygen species (ROS) generation through activation of the HO-1/Nrf2 signaling axis. HO-1 silencing via siRNA transfection abolished these effects, confirming HO-1-dependent regulation of oxidative stress and lipid metabolism. Collectively, these findings highlight P3 and P4 peptides as promising therapeutic agents for atherosclerosis by concurrently targeting foam cell formation, cholesterol dysregulation, and oxidative stress, warranting further exploration for potential clinical applications. Full article
(This article belongs to the Special Issue Bioactive Proteins and Peptides from Marine Mollusks)
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<p>Chemical structures of AWLNH (P3) and PHDL (P4).</p>
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<p>(<b>A</b>) Cell viability; quantitative analysis of intracellular lipid accumulation inhibition in (<b>B</b>) RAW264.7 macrophages and (<b>C</b>) hASMCs; and qualitative evaluation of AWLNH (P3) and PHDL (P4) in (<b>D</b>) oxLDL-treated RAW264.7 macrophages (40× magnification) and (<b>E</b>) hASMCs (20× magnification). For the MTT assay, macrophages were exposed to P3, P4, or positive controls (10 µM), including simvastatin (SIM) or rosiglitazone (RSG), along with oxLDLs (50 µg/mL). In Oil Red O (ORO) staining experiments, cells were pretreated with P3, P4, or positive controls (10 µM), including SIM or RSG, for 1 h before oxLDL exposure for 24 h. Data are presented as mean ± S.D. from three independent experiments (<span class="html-italic">n</span> = 3). Statistical significance is indicated as <span class="html-italic">** p</span> &lt; 0.001 versus the oxLDL-treated group and <span class="html-italic"><sup>##</sup> p</span> &lt; 0.001 versus the non-treated group. Numbers in the images denote concentrations in µM.</p>
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<p>The effects of 10–200 µM concentrations of AWLNH (P3) and PHDL (P4) peptides on (<b>A</b>) total cholesterol, (<b>B</b>) free cholesterol, (<b>C</b>) cholesterol ester, and (<b>D</b>) triglyceride content in oxLDL-treated RAW264.7 macrophages. Macrophages were treated with P3 and P4 peptides for 1 h, followed by a 24 h treatment with oxLDL. The results are based on three independent experiments (<span class="html-italic">n</span> = 3), with data expressed as mean ± S.D. Significant differences are indicated by <span class="html-italic">* p</span> &lt; 0.05, <span class="html-italic">** p</span> &lt; 0.001, comparing the P3 and P4 peptide treatments to the oxLDL-treated group, and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001, comparing the peptide treatments to the non-treated control group.</p>
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<p>The effect of 10–200 µM concentrations of AWLNH (P3) and PHDL (P4) peptides on (<b>A</b>) cholesterol influx, (<b>B</b>) cholesterol efflux, (<b>C</b>) protein expressions of ABCA-1, ABCG-1, SR-A1, and CD36 and (<b>D</b>) PPAR-γ and LXR-α expression in oxLDL-treated RAW264.7 macrophages. Macrophages were pretreated with P3 and P4 peptides for 1 h, followed by a 24 h treatment with oxLDL. The results are based on three independent experiments (<span class="html-italic">n</span> = 3), with data presented as mean ± S.D. Statistical significance is denoted as <span class="html-italic">** p</span> &lt; 0.001 when comparing the peptide treatments to the oxLDL-treated group and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001 when comparing to the non-treated group.</p>
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<p>The effect of 10–200 µM concentrations of AWLNH (P3) and PHDL (P4) peptides on (<b>A</b>) quantitative ROS generation, (<b>B</b>) qualitative ROS generation (20× magnification), and (<b>C</b>) HO-1 expression in oxLDL-treated RAW264.7 macrophages, as well as (<b>D</b>) Nrf2 activation. For ROS and HO-1 analysis, macrophages were treated with P3 and P4 peptides for 1 h, followed by oxLDL exposure for 24 h. For Nrf2 activation, macrophages were treated with P3 and P4 peptides for 1 h. Data are presented as the mean ± S.D. from three independent experiments (<span class="html-italic">n</span> = 3). Statistical significance is indicated by <span class="html-italic">** p</span> &lt; 0.001 compared to the oxLDL-treated group, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001 compared to the non-treated group in ROS and HO-1 analysis, <span class="html-italic">** p</span> &lt; 0.001 compared to the nuclear fraction of the non-treated group, and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001 compared to the cytoplasmic fraction of the non-treated group. The numbers in the images represent peptide concentrations in µM.</p>
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<p>The effect of 200 µM concentrations of AWLNH (P3) and PHDL (P4) peptides on (<b>A</b>) HO-1, PPAR-γ, and LXR-α expressions, and (<b>B</b>) ABCA-1, ABCG-1, CD36, and SR-A1 expressions with HO-1 siRNA transfection was assessed. RAW264.7 macrophages were transiently transfected with HO-1 siRNA or a negative control using Lipofectamine<sup>®</sup> 2000 for 24 h. The cells were then treated with 200 µM of P3 or P4 peptides for 1 h, followed by a 24 h treatment with oxLDLs (50 µg/mL). Data represent the mean ± S.D. from three independent experiments (<span class="html-italic">n</span> = 3). Statistical significance is indicated by ** <span class="html-italic">p</span> &lt; 0.001 compared to the P3-treated group and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001 compared to the P4-treated group in siRNA transfection.</p>
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<p>The effect of 200 µM concentrations of AWLNH (P3) and PHDL (P4) peptides on ROS generation, (<b>A</b>) quantitatively and (<b>B</b>) qualitatively (40× magnification), and intracellular lipid accumulation, (<b>C</b>) quantitatively and (<b>D</b>) qualitatively (20× magnification), with HO-1 siRNA transfection was assessed. RAW264.7 macrophages were transiently transfected with HO-1 siRNA or a negative control using Lipofectamine<sup>®</sup> 2000 for 24 h. The cells were then treated with 200 µM of P3 or P4 peptides for 1 h, followed by a 24 h treatment with oxLDLs (50 µg/mL). Data represent the mean ± S.D. from three independent experiments (<span class="html-italic">n</span> = 3). Statistical significance is indicated by ** <span class="html-italic">p</span> &lt; 0.001 compared to the P3-treated group and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.001 compared to the P4-treated group in siRNA transfection.</p>
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<p>Chemical structures of LLRLTDL (Bu1) and GYALPCDCL (Bu2).</p>
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21 pages, 3101 KiB  
Article
Microplastic Deposits Prediction on Urban Sandy Beaches: Integrating Remote Sensing, GNSS Positioning, µ-Raman Spectroscopy, and Machine Learning Models
by Anderson Targino da Silva Ferreira, Regina Célia de Oliveira, Eduardo Siegle, Maria Carolina Hernandez Ribeiro, Luciana Slomp Esteves, Maria Kuznetsova, Jessica Dipold, Anderson Zanardi de Freitas and Niklaus Ursus Wetter
Microplastics 2025, 4(1), 12; https://doi.org/10.3390/microplastics4010012 - 5 Mar 2025
Viewed by 166
Abstract
This study focuses on the deposition of microplastics (MPs) on urban beaches along the central São Paulo coastline, utilizing advanced methodologies such as remote sensing, GNSS altimetric surveys, µ-Raman spectroscopy, and machine learning (ML) models. MP concentrations ranged from 6 to 35 MPs/m [...] Read more.
This study focuses on the deposition of microplastics (MPs) on urban beaches along the central São Paulo coastline, utilizing advanced methodologies such as remote sensing, GNSS altimetric surveys, µ-Raman spectroscopy, and machine learning (ML) models. MP concentrations ranged from 6 to 35 MPs/m2, with the highest densities observed near the Port of Santos, attributed to industrial and port activities. The predominant MP types identified were foams (48.7%), fragments (27.7%), and pellets (23.2%), while fibers were rare (0.4%). Beach slope and orientation were found to facilitate the concentration of MP deposition, particularly for foams and pellets. The study’s ML models showed high predictive accuracy, with Random Forest and Gradient Boosting performing exceptionally well for specific MP categories (pellet, fragment, fiber, foam, and film). Polymer characterization revealed the prevalence of polyethylene, polypropylene, and polystyrene, reflecting sources such as disposable packaging and industrial raw materials. The findings emphasize the need for improved waste management and targeted urban beach cleanups, which currently fail to address smaller MPs effectively. This research highlights the critical role of combining in situ data with predictive models to understand MP dynamics in coastal environments. It provides actionable insights for mitigation strategies and contributes to global efforts aligned with the Sustainable Development Goals, particularly SDG 14, aimed at conserving marine ecosystems and reducing pollution. Full article
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<p>Flowchart of the steps in the methodology used in this research. RS: orbital remote sensing images; MNDWI: modified normalized difference water index; HD<sub>sat</sub>: horizontal distance derived by satellite; VD<sub>tide</sub>: vertical distance derived by tide; tanβ<sub>sat</sub>: slope derived by satellite; GNSS: global navigation satellite system; Alt<sub>GNSS</sub>: altitude derived by GNSS; tanβ<sub>GNSS</sub>: slope derived by GNSS; μ-Raman: micro-Raman analysis; ML: machine learning models; and MP deposits: microplastic deposits.</p>
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<p>Sediment sampling sites and GNSS positioning locations. Urban areas are highlighted in red, with emphasis on the Port of Santos and the industrial region of Cubatão.</p>
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<p>Beach sampling point (P1), modified from [<a href="#B1-microplastics-04-00012" class="html-bibr">1</a>]. Examples of GNSS base, rover surveys, and area (1 m<sup>2</sup>) of superficial sediment collection.</p>
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<p>SHAP analysis of variable contributions for predicting microplastic deposition using multiple machine learning models: (<b>a</b>) SVR—Support Vector Regression for pellets; (<b>b</b>) GB—Gradient Boosting for fragments; (<b>c</b>) RF—Random Forest for fibers; (<b>d</b>) RF—Random Forest for foams; and (<b>e</b>) GB—Gradient Boosting for total MP. The intensity of each variable is represented by the color scale, ranging from blue (low values) to red (high values), indicating the magnitude of the feature’s influence.</p>
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<p>GNSS sediment samples and transect models: (<b>a</b>) beach slope (tanβ); (<b>b</b>) beach face direction (Aspect).</p>
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<p>Modeled points and GNSS sediment sample points: (<b>a</b>) pellet, (<b>b</b>) foam, (<b>c</b>) fragment, (<b>d</b>) fiber, and (<b>e</b>) total MP (m<sup>2</sup>).</p>
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<p>Perceptual maps showing the standardized adjusted residual (ASR) values between the microplastic deposition models: (<b>a</b>) pellet, (<b>b</b>) foam, (<b>c</b>) fragment, and (<b>d</b>) total MP (m<sup>2</sup>) in relation to beaches’ modeled points (PG, SVS, GUA, and BER). The colored cells indicate significant relationships between variables (+1.96 ≤ good SAR). VL (very low), L (low), M (medium), H (high), and VH (very high) represent the different levels of MP/m<sup>2</sup> deposition by CA.</p>
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<p>Raman spectra of polymers: (<b>a</b>,<b>b</b>) polyethylene; (<b>c</b>) polypropylene; and (<b>d</b>) polystyrene.</p>
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20 pages, 5404 KiB  
Article
Design and Optimization of the Bionic Flexible Gripper Based on Magnetically Sensitive Rubber
by Xianhua Bian, Yu Ding, Rui Li, Mengjie Shou and Pingan Yang
Actuators 2025, 14(3), 124; https://doi.org/10.3390/act14030124 - 5 Mar 2025
Viewed by 141
Abstract
Flexible grippers based on magnetically sensitive rubber have garnered significant research attention due to their high gripping adaptability and ease of control. However, current research designs often separate the excitation device from the flexible finger, which can lead to potential interference or damage [...] Read more.
Flexible grippers based on magnetically sensitive rubber have garnered significant research attention due to their high gripping adaptability and ease of control. However, current research designs often separate the excitation device from the flexible finger, which can lead to potential interference or damage to other electronic components in the working environment and an inability to simultaneously ensure safety and gripping performance. In this paper, we propose an integrated magnetically controlled bionic flexible gripper that combines the excitation device and the flexible finger. We derive a formula for calculating the magnetic field generated by the excitation device, model and simulate the device, and find that the optimal magnetic field effect is achieved when the core-to-coil size ratio is 1:5. Additionally, we fabricated flexible fingers with different NdFeB volume ratios and experimentally determined that a volume ratio of 20% yields relatively better bending performance. The integrated magnetically controlled bionic flexible gripper described in this paper can adaptively grasp items such as rubber, column foam, and electrical tape, achieving maximum grasping energy efficiency of 0.524 g per millitesla (g/mT). These results highlight its potential advantages in applications such as robotic end-effectors and industrial automatic sorting. Full article
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<p>Conceptual diagram of magnetically controlled bionic flexible gripper. (<b>a</b>) Gripper in a non-operational state. (<b>b</b>) Gripper in working condition.</p>
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<p>Schematic diagram of the magnetic circuit of the magnetically controlled bionic flexible gripper. (<b>a</b>) Schematic diagram of the magnetic circuit and dimensional parameters of the magnetically controlled bionic flexible gripper. (<b>b</b>) The main dimensions of the magnetically controlled bionic gripper. (<b>c</b>) Elevation view and finger dimensions of the magnetically controlled bionic gripper. (<b>d</b>) Structural modeling of the excitation device. (<b>e</b>) Schematic of the finite element meshing of the simulation software.</p>
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<p>Schematic of the line segments required to calculate the optimization objective.</p>
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<p>Magnetic field strength versus structural parameters across varying <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> values. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.025; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.1; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.3; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.6; (<b>e</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.9; (<b>f</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>k</mi> </mrow> <mrow> <mi>h</mi> </mrow> </msub> </mrow> </semantics></math> = 0.975.</p>
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<p>Simulation modeling of fingers. (<b>a</b>) Modeling of a single finger of magnetically controlled bionic flexible gripper. (<b>b</b>) Simulation meshing. (<b>c</b>) Normalized width, length, and thickness versus bending angle. (<b>d</b>) Normalized reposition versus bending angle. (<b>e</b>) Effect of reverse magnetic field on bending. The arrow direction indicates the magnetic field direction, and the arrow length reflects the magnetic field strength. (<b>f</b>) Effect of forward magnetic field on bending.</p>
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<p>Effect of filling volume ratio of NdFeB on magnetron performance. (<b>a</b>) Schematic diagram of the preparation of magnetically controlled bionic flexible gripper. (<b>b</b>) Magnetic field versus bending angle of flexible fingers with different NdFeB volume fractions. (<b>c</b>) Variation in surface roughness of flexible fingers under magnetic field. (<b>d</b>) Pressure–strain curves of flexible fingers with different NdFeB volume fractions. (<b>e</b>) Variation in the surface profile of samples with NdFeB volume fraction of 20%.</p>
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<p>Test method and platform construction of magnetically controlled bionic flexible gripper. (<b>a</b>) Magnetic control bionic flexible gripper parts excitation device. (<b>b</b>) The iron core of the magnetically controlled bionic flexible gripper. (<b>c</b>) Fixed housing for the parts of the magnetically controlled bionic flexible gripper. (<b>d</b>) Fixed cover of the parts of the magnetically controlled bionic flexible gripper. (<b>e</b>) Assembly diagram of the magnetically controlled bionic flexible gripper. (<b>f</b>) Schematic diagram of the test platform of the magnetically controlled bionic flexible gripper.</p>
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<p>Relationship between the length of the flexible finger, the diameter of the spherical grasped object, and the maximum pulling force. (<b>a</b>) The relationship between the length of the flexible finger, the diameter of the spherical grasped object, and the maximum tensile force at a current of 0.5 A. (<b>b</b>) The relationship between the length of the flexible finger, the diameter of the spherical grasped object, and the maximum tensile force at a current of 1.5 A. (<b>c</b>) The relationship between the length of the flexible finger, the diameter of the spherical grasped object, and the maximum tensile force under 2.5 A current.</p>
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<p>Effect of the shape of the grasped object on the grasping force of a magnetically controlled bionic flexible gripper.</p>
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<p>Integrated magnetically controlled bionic flexible gripper for gripping household objects, the white dashed line represents the outline of the flexible finger. (<b>a</b>) Gripping hard rubber blocks with smooth surfaces. (<b>b</b>) Gripping soft cylindrical foam. (<b>c</b>) Gripping hollow electrical tape.</p>
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14 pages, 4386 KiB  
Article
Enhanced Cement Foam Composite with Biochar for Eriochrome Black T Dye Removal
by Mohammed Ettahar Boussalah, Malika Medjahdi, Sofiane Guella and Dominique Baillis
Materials 2025, 18(5), 1158; https://doi.org/10.3390/ma18051158 - 5 Mar 2025
Viewed by 201
Abstract
Cement-based foam composites have gained attention as innovative and high-performing adsorbents for wastewater treatment due to their lightweight, porous, and structurally robust properties. This study investigates the adsorption of Eriochrome Black T dye onto biochar-modified cement foam, providing a cost-effective solution for industrial [...] Read more.
Cement-based foam composites have gained attention as innovative and high-performing adsorbents for wastewater treatment due to their lightweight, porous, and structurally robust properties. This study investigates the adsorption of Eriochrome Black T dye onto biochar-modified cement foam, providing a cost-effective solution for industrial wastewater management. The integration of biochar into cement foam enhances its surface area and adsorption capabilities while maintaining structural stability and tunable porosity. The composites were characterized using scanning electron microscopy, Fourier-transform infrared spectroscopy, and energy-dispersive X-ray spectroscopy to verify quality and functionality. The adsorption process adhered to the Freundlich isotherm model (R2 = 0.967), indicating multilayer adsorption, with a maximum capacity of 13.33 mg/g under optimal conditions. Kinetic studies showed a pseudo-first-order fit (R2 = 0.981), while thermodynamic analysis revealed a spontaneous and endothermic process, with ΔH° = 28.84 KJ/mol and ΔG° values ranging from −0.457 to −2.36 KJ/mol. These results demonstrate the composite’s exceptional efficiency and scalability, making it a sustainable and practical option for removing persistent dyes such as Eriochrome Black T. This work contributes significantly to the advancement of environmentally friendly wastewater treatment technologies. Full article
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<p>Particle size distributions of JAC biochar and cement.</p>
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<p>SEM image of JAC biochar.</p>
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<p>Preparation steps of RM and CACC samples for characterization and application.</p>
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<p>EBT solutions with different concentrations.</p>
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<p>UV absorption spectrum of Eriochrome Black T (EBT).</p>
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<p>FTIR spectra of modified foam cement (CACC) and raw foam cement (RM).</p>
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<p>EDX spectra of foamed cement (RM) and modified foamed cement (CACC).</p>
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<p>EBT dye kinetic adsorption by CACC and RM (T = 29 ± 1 °C, adsorbent dose 0.3 g CACC15, C0 = 20 mg/L, stirring speed = 0 rpm).</p>
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<p>Langmuir and Freundlich isotherm for adsorption of EBT on CACC.</p>
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<p>Kinetic analysis modelling.</p>
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<p>Temperature effect of EBT dye adsorption on CACC15 (t = 150 min, C0 = 40 mg/L).</p>
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<p>Representation of Van’t Hoff equation for EBT adsorption on CACC15 and on RM.</p>
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15 pages, 2354 KiB  
Article
Moisture-Driven Morphology Changes in the Thermal and Dielectric Properties of TPU-Based Syntactic Foams
by Sabarinathan Pushparaj Subramaniyan, Partha Pratim Das, Rassel Raihan and Pavana Prabhakar
Polymers 2025, 17(5), 691; https://doi.org/10.3390/polym17050691 - 5 Mar 2025
Viewed by 127
Abstract
Syntactic foams are a promising candidate for applications in marine, oil and gas industries in underwater cables and pipelines due to their excellent insulation properties. The effective transmission of electrical energy through cables requires insulation materials with a low loss factor and low [...] Read more.
Syntactic foams are a promising candidate for applications in marine, oil and gas industries in underwater cables and pipelines due to their excellent insulation properties. The effective transmission of electrical energy through cables requires insulation materials with a low loss factor and low dielectric constant. Similarly, in transporting fluid through pipelines, thermal insulation is crucial. However, both applications are susceptible to potential environmental degradation from moisture exposure, which can significantly impact the material’s properties. This study addresses the knowledge gap by examining the implications of prolonged moisture exposure on thermoplastic polyurethane elastomer (TPU) and TPU-derived syntactic foam via various multi-scale material characterization methods. This research investigates a flexible syntactic foam composed of TPU and glass microballoons (GMBs) fabricated through selective laser sintering. The study specifically examines the effects of moisture exposure over periods of 90 and 160 days, in conjunction with varying GMB volume fractions of 0%, 20%, and 40%. It aims to elucidate the resulting microphase morphological changes, their underlying mechanisms, and the subsequent impact on thermal transport and dielectric properties, all in comparison to unaged samples of the same material. Our findings reveal that increasing the volume fraction of GMB in TPU-based syntactic foam reduces its thermal conductivity and specific heat capacity. However, moisture exposure did not significantly affect the foam’s thermal conductivity. Additionally, we found that the dielectric constant of the syntactic foams decreases with increasing volume fraction of GMB and decreasing frequency of the applied field, which is due to limited molecular orientation in response to the field. Finally, moisture exposure affects the dielectric loss factor of TPU-based syntactic foams with GMBs, possibly due to the distribution morphology of hard and soft segments in TPU. Full article
(This article belongs to the Special Issue Thermoplastic Foams: Processing, Manufacturing, and Characterization)
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<p>(<b>a</b>) Schematic illustration of laser flash analysis and (<b>b</b>) thermal diffusivity measurement using time vs. temperature rise plot.</p>
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<p>Graphical illustration of the hydrogen bonding present in thermoplastic polyurethane elastomer. (Reprinted with permission from [<a href="#B28-polymers-17-00691" class="html-bibr">28</a>], Copyright 2023, Elsevier).</p>
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<p>(<b>a</b>) Degree of phase mixing as a function of GMB volume fraction and moisture exposure duration. (<b>b</b>) The total melting enthalpy for different GMB volume fractions and moisture exposure times. (Reprinted with permission from [<a href="#B28-polymers-17-00691" class="html-bibr">28</a>], Copyright 2023, Elsevier).</p>
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<p>Illustration of moisture-induced mechanisms in TPU elastomer at different times of exposure.</p>
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<p>(<b>a</b>) Phonon–phonon scattering and (<b>b</b>) phonon–boundary scattering.</p>
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<p>(<b>a</b>) Thermal conductivity and (<b>b</b>) specific heat capacity of TPU with different volume fractions of GMB reinforcement and moisture exposure time.</p>
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<p>Moisture-driven changes in dielectric properties as a function of GMB volume fraction and frequency: (<b>a</b>) dielectric constant and (<b>b</b>) dielectric loss tangent.</p>
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<p>Summary of thermal and dielectric property evolution with exposure times.</p>
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<p>(<b>a</b>) Schematic illustration of dielectric analysis and (<b>b</b>) dielectric response and attributing mechanism at different frequencies [<a href="#B50-polymers-17-00691" class="html-bibr">50</a>].</p>
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<p>Electrical conductivity of TPU and TPU−based syntactic foam as a function of moisture aging time and frequency.</p>
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14 pages, 4361 KiB  
Article
Numerical and Experimental Analysis of Impact Force and Impact Duration with Regard to Radiosondes: Is a PUR Foam Shell an Effective Solution?
by Norbert Hegyi, János Jósvai and Gusztáv Fekete
Appl. Mech. 2025, 6(1), 19; https://doi.org/10.3390/applmech6010019 - 5 Mar 2025
Viewed by 105
Abstract
This study investigates the effect of a polyurethane (PUR) foam layer on impact force, impact duration, and deformation with regard to radiosondes during drop tests. Numerical (Finite Element Method) and experimental approaches were used to model collisions with and without protective PUR layers. [...] Read more.
This study investigates the effect of a polyurethane (PUR) foam layer on impact force, impact duration, and deformation with regard to radiosondes during drop tests. Numerical (Finite Element Method) and experimental approaches were used to model collisions with and without protective PUR layers. The numerical results demonstrated that adding a soft PUR foam layer reduced peak impact force by 10% while it increased impact duration up to 71%. Experimental drop tests confirmed the numerical outcomes as peak impact force difference was 7% between simulations and experiments, while impact duration differed only by 11%. Besides force and duration, impact deformation was also investigated by an FEM model and high-speed camera footage on radiosondes with a PUR foam layer. The FEM model was able to approximate well the deformation magnitude since the numerical deformation was only 2% lower compared to the experimental data. In summary, a reliable and validated FEM model was created. On the one hand, this model allows the analysis of different protective layers around a radiosonde. On the other hand, it can adequately predict the impact behavior of radiosondes by incorporating multiple important factors. In addition, it has been confirmed that incorporating a soft PUR foam layer significantly improves safety by reducing impact force and extending impact duration. Full article
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<p>The soft-shelled 3D model with numbered outside parts: (1) fixed force sensors, (2) soft shell, (3) soft shell (<b>a</b>); 3D model of a soft-shelled radiosonde: (3) soft shell, (4) EPS body part, (5) battery pack, (6) EPS body part, (7) inner (fiberglass) electronics, (8) meteorological sensor, (9) EPS body part, (10) EPS body part (<b>b</b>); normal radiosonde and target plate mesh (<b>c</b>); soft-shelled radiosonde and target plate mesh (<b>d</b>).</p>
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<p>Version A: parallel face-to-face impact (<b>a</b>); Version A: maximal contact during collision (<b>b</b>); Version A: bounce back (<b>c</b>); Version B: before parallel face-to-face impact (<b>d</b>); Version B: maximal deformation during collision (<b>e</b>); Version B: bounce back (<b>f</b>).</p>
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<p>Experimental setup of soft-shelled drop test.</p>
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<p>(<b>a</b>) FEM drop tests. Version A (average function denoted by the dashed blue line, variations caused by impact angles denoted by the light blue stripe). Version B (average function denoted by the red line, variations caused by impact angles denoted by the light red stripe). Version C (average function denoted by the dashed green line, variations caused by impact angles denoted by the light green stripe). (<b>b</b>) FEM drop test. Version A (average function denoted by the dashed blue line, variations caused by impact angles denoted by the light blue stripe). (<b>c</b>) FEM drop test. Version B (average function denoted by the dashed red line, variations caused by impact angles denoted by the light red stripe). (<b>d</b>) FEM drop test. Version C (average function denoted by the dashed green line, variations caused by impact angles denoted by the light green stripe).</p>
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<p>(<b>a</b>) FEM drop tests. Version A (average function denoted by the dashed blue line, variations caused by impact angles denoted by the light blue stripe). Version B (average function denoted by the red line, variations caused by impact angles denoted by the light red stripe). Version C (average function denoted by the dashed green line, variations caused by impact angles denoted by the light green stripe). (<b>b</b>) FEM drop test. Version A (average function denoted by the dashed blue line, variations caused by impact angles denoted by the light blue stripe). (<b>c</b>) FEM drop test. Version B (average function denoted by the dashed red line, variations caused by impact angles denoted by the light red stripe). (<b>d</b>) FEM drop test. Version C (average function denoted by the dashed green line, variations caused by impact angles denoted by the light green stripe).</p>
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<p>Experimental drop tests.</p>
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<p>Radiosonde (Version A): first contact with target (<b>a</b>); maximal contact and deformation (<b>b</b>); bounce back (<b>c</b>); Radiosonde (Version B): first contact with target (<b>d</b>); maximal contact and deformation (<b>e</b>); bounce back (<b>f</b>).</p>
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<p>Radiosonde (Version B): before deformation (<b>a</b>); maximal deformation (<b>b</b>).</p>
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<p>The first graph is the FEM Version A drop test mean function; the second graph is experimental Version A drop test mean function (<b>a</b>); The first graph is the FEM Version B drop test mean function, the second graph is experimental Version B drop test mean function (<b>b</b>).</p>
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17 pages, 10493 KiB  
Article
Modified Fe3O4 Nanoparticles for Foam Stabilization: Mechanisms and Applications for Enhanced Oil Recovery
by Dandan Yin, Judong Qiu, Dongfeng Zhao, Yongzheng Wang, Tao Huang, Yunqian Long and Xiaohe Huang
Nanomaterials 2025, 15(5), 395; https://doi.org/10.3390/nano15050395 - 4 Mar 2025
Viewed by 191
Abstract
Nanoparticles (NPs) have shown great potential in stabilizing foam for enhanced oil recovery (EOR). However, conventional NPs are difficult to recover and may contaminate produced oil, increasing operational costs. In contrast, superparamagnetic Fe3O4 NPs can be efficiently recovered using external [...] Read more.
Nanoparticles (NPs) have shown great potential in stabilizing foam for enhanced oil recovery (EOR). However, conventional NPs are difficult to recover and may contaminate produced oil, increasing operational costs. In contrast, superparamagnetic Fe3O4 NPs can be efficiently recovered using external magnetic fields, offering a sustainable solution for foam stabilization. In this study, Fe3O4 NPs were coated with SiO2 using tetraethyl orthosilicate (TEOS) and further modified with dodecyltrimethoxysilane to enhance their hydrophobicity. The modification effects were characterized, and the optimal foam-stabilizing Fe3O4@SiO2 NPs were found to have a contact angle of 77.01°. The foam system formed with α-olefin sulfonate (0.2 wt%) as the foaming agent and the optimal modified NPs exhibited a drainage half-life of 452 s. After foam-stabilization experiments, the NPs were recovered and reused, with the results indicating that three recovery cycles were optimal. Finally, visual microscopic displacement experiments demonstrated that the foam stabilized by modified NPs effectively mobilized clustered, membranous, and dead-end residual oil, increasing the recovery rate by 17.01% compared with unmodified NPs. This study identifies key areas for future investigation into the application of magnetic nanoparticles for enhanced oil recovery. Full article
(This article belongs to the Topic Nanomaterials for Energy and Environmental Applications)
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Graphical abstract

Graphical abstract
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<p>Schematic representation of the synthesis mechanism of Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub> NPs.</p>
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<p>Synthesis process of modified Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub> NPs.</p>
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<p>Flow chart of microscopic oil displacement experiment.</p>
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<p>SEM images of NPs: (<b>a</b>) Fe<sub>3</sub>O<sub>4</sub>; (<b>b</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-800; (<b>c</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-1000; (<b>d</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-1200.</p>
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<p>Size distribution of NPs: (<b>a</b>) Naked Fe<sub>3</sub>O<sub>4</sub>; (<b>b</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-1000; (<b>c</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-1200.</p>
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<p>TEM images and EDS of nanoparticles (<b>a</b>) Fe<sub>3</sub>O<sub>4</sub>; (<b>b</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-1000.</p>
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<p>Infrared spectrum of NPs.</p>
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<p>The contact angles of NPs with water as a function of amounts of silane coupling agent.</p>
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<p>The different wettability nanoparticles on stabilizing foam: (<b>a</b>) drainage half-life time; (<b>b</b>) foam volume.</p>
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<p>Confocal fluorescence image for the foams (Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub> NPs-AOS (0.2wt%)). (<b>a</b>) Wet foam; (<b>b</b>) dry foam; (<b>c</b>) dry foam stabilized by NPs with a contact angle of 77.01; (<b>d</b>) dry foam stabilized by NPs with a contact angle of 121.34°. The red circles are bubbles.</p>
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<p>Evaluation of recyclability of NPs: (<b>a</b>) the responsiveness of NPs to a magnet; (<b>b</b>) the drainage half-life time changes with the recycle number of NPs.</p>
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<p>Microscopic residual oil after flooding: (<b>a</b>) cluster residual oil; (<b>b</b>) membranous residual oil; (<b>c</b>) dead-end residual oil.</p>
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<p>The pressure of flooding experiments.</p>
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<p>Microscopic residual oil after Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-AOS foam flooding: (<b>a</b>) cluster residual oil; (<b>b</b>) membranous residual oil; (<b>c</b>) dead-end residual oil.</p>
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<p>Microscopic images of residual oil distributions in 2D micromodel. (<b>a</b>) The raw images of initial oil distribution, (<b>b</b>) residual oil distributions after water flooding, (<b>c</b>) AOS foam flooding and extended water flooding, and (<b>d</b>) Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub>-AOS foam flooding and extended water flooding, respectively, while (<b>e</b>–<b>h</b>) were processed versions of images (<b>a</b>–<b>d</b>) using Image J software to estimate trapped oil. The dark brown color is oil and the milky color is displacement fluid in (<b>a</b>–<b>d</b>) whereas red is oil and the ash color is displacement fluid in (<b>e</b>–<b>h</b>). The flow direction is from left to right.</p>
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19 pages, 10502 KiB  
Article
Flexible and Washable Poly(3,4-ethylenedioxythiophene): Polystyrene Sulfonate/Polyvinyl Alcohol Fabric Dry Electrode for Long-Term Electroencephalography Signals Measurement
by Fangmeng Zeng, Guanghua Wang, Chenyi Sun, Jiayi Gao, Shanqun Ji and Quanxi Zhang
Polymers 2025, 17(5), 683; https://doi.org/10.3390/polym17050683 - 4 Mar 2025
Viewed by 120
Abstract
Recent advancements in smart textiles have facilitated their extensive application in wearable health monitoring, particularly in brain activity measurement. This study introduces a flexible and washable fabric dry electroencephalography (EEG) electrode designed for brain activity measurement. The fabric dry electrode is constructed from [...] Read more.
Recent advancements in smart textiles have facilitated their extensive application in wearable health monitoring, particularly in brain activity measurement. This study introduces a flexible and washable fabric dry electroencephalography (EEG) electrode designed for brain activity measurement. The fabric dry electrode is constructed from electrically conductive polyester fabric with a resistivity of 0.09 Ω·cm, achieved by applying a PEDOT: PSS/PVA conductive paste coating on the textile substrate. A comparative analysis of the tensile properties between the conductive and untreated polyester fabric was conducted. The SEM images demonstrated that the PEDOT: PSS/PVA conductive polymer composite resulted in a uniform coating on the fabric surface. When enveloped in elastic foam, the fabric dry electrode maintained a low and stable electrode–skin contact impedance during prolonged EEG monitoring. Additionally, the short circuit noise level of the fabric dry electrode exhibited superior performance compared to both Ag/AgCl wet and finger dry electrode. The EEG signals acquired from the fabric dry electrode were comparable to those recorded by the Ag/AgCl wet electrode. Moreover, the fabric electrode effectively captured clear and reliable EEG signals, even after undergoing 10 washing cycles. The fabric dry electrode indicates good sweat resistance and biocompatibility during prolonged monitoring. Full article
(This article belongs to the Section Smart and Functional Polymers)
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Figure 1

Figure 1
<p>(<b>a</b>) Schematic illustration of the preparation process for conductive fabric; (<b>b</b>) structural design of the PEDOT: PSS/PVA fabric dry electrode; (<b>c</b>) model design of the electrode shell and its 3D-printed shell; (<b>d</b>) the assembled electrode and its components.</p>
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<p>(<b>a</b>) Schematic illustration of the preparation process for conductive fabric; (<b>b</b>) structural design of the PEDOT: PSS/PVA fabric dry electrode; (<b>c</b>) model design of the electrode shell and its 3D-printed shell; (<b>d</b>) the assembled electrode and its components.</p>
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<p>The schematic illustration of the setup for measuring EEG signals.</p>
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<p>(<b>a</b>) SEM image of the polyester fabric (×65); (<b>b</b>) SEM image of the polyester fabric (×500); (<b>c</b>) SEM image of PEDOT: PSS/PVA-coated conductive fabric (×65); (<b>d</b>) SEM image of PEDOT: PSS/PVA-coated conductive fabric (×500); (<b>e</b>) SEM image of PEDOT: PSS/PVA-coated conductive fabric after 10 washing cycles (×65); (<b>f</b>) SEM image of PEDOT: PSS/PVA-coated conductive fabric after 10 washing cycles (×500); (<b>g</b>) FTIR spectra of the polyester fabric, PEDOT: PSS-coated conductive fabric, and PEDOT: PSS/PVA-coated conductive fabric; (<b>h</b>) The resistance of PEDOT: PSS/PVA-coated conductive fabrics after various washing cycles.</p>
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<p>(<b>a</b>) Schematic illustration of the setup for measuring electrode–skin contact impedance using the OpenBCI Cyton Board; (<b>b</b>) The electrode–skin contact impedances of EEG electrodes over time, including Ag/AgCl wet electrode, finger dry electrode, and PEDOT: PSS/PVA fabric dry electrode.</p>
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<p>Results of the short circuit noise test: (<b>a</b>) noise measured with Ag/AgCl wet electrodes; (<b>b</b>) noise measured with finger dry electrodes; (<b>c</b>) noise measured with PEDOT: PSS/PVA fabric dry electrodes; (<b>d</b>) number of noises measured with Ag/AgCl wet electrodes at varying amplitudes; (<b>e</b>) number of noises measured with finger dry electrodes at varying amplitudes; (<b>f</b>) number of noises measured with PEDOT: PSS/PVA fabric dry electrodes at varying amplitudes.</p>
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<p>EEG signals were recorded for 30 s using the Ag/AgCl wet electrode and the PEDOT: PSS/PVA fabric dry electrode placed on the forehead of 5 subjects during a resting state. (<b>a</b>) Fp1; (<b>b</b>) Fp2.</p>
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<p>EEG artifacts were recorded for 30 s using the Ag/AgCl wet electrode and the PEDOT: PSS/PVA fabric dry electrode at Fp1 from 5 subjects. (<b>a</b>) Eye blinks; (<b>b</b>) teeth clenching.</p>
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<p>Results of EEG signal recordings for 30 s using the Ag/Ag/Cl wet electrode and the PEDOT: PSS/PVA fabric dry electrode from hairy areas (O1) from 5 subjects with the eyes closed/opened; (<b>a</b>) EEG signals; (<b>b</b>) PSD of EEG signals.</p>
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<p>Results of EEG signal recordings for 30 s using the Ag/Ag/Cl wet electrode and the PEDOT: PSS/PVA fabric dry electrode from hairy areas (O1) from 5 subjects with the eyes closed/opened; (<b>a</b>) EEG signals; (<b>b</b>) PSD of EEG signals.</p>
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<p>SNRs of the Ag/AgCl wet electrode and the PEDOT: PSS/PVA fabric dry electrode at Fp1, Fp2, and O1.</p>
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<p>Results of EEG signal recordings for 30 s using the PEDOT: PSS/PVA fabric dry electrode after 5 and 10 washing cycles at Fp1.</p>
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<p>Result of EEG signal recordings for 30 s using the PEDOT: PSS/PVA fabric dry electrode simulating insensible perspiration and sensible perspiration at Fp1.</p>
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<p>The skin condition test of wearing the PEDOT: PSS/PVA fabric dry electrode for 4 h.</p>
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