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21 pages, 2468 KiB  
Article
Mechanical Properties and Damage Constitutive Model of Saturated Sandstone Under Freeze–Thaw Action
by Meimei Feng, Xiaoxiao Cao, Taifeng Wu and Kangsheng Yuan
Materials 2024, 17(23), 5905; https://doi.org/10.3390/ma17235905 - 2 Dec 2024
Viewed by 284
Abstract
In order to investigate the impact of freeze–thaw damage on sandstone under the coupling of ground stress and pore water pressure, three types of porous sandstone were subjected to freezing at different negative temperatures (−5 °C, −10 °C, −15 °C, and −20 °C). [...] Read more.
In order to investigate the impact of freeze–thaw damage on sandstone under the coupling of ground stress and pore water pressure, three types of porous sandstone were subjected to freezing at different negative temperatures (−5 °C, −10 °C, −15 °C, and −20 °C). Subsequently, hydraulic coupling triaxial compression tests were conducted on the frozen and thawed sandstone. We analyzed the effects of porosity and freezing temperature on the mechanical properties of sandstone under hydraulic coupling and performed nuclear magnetic resonance tests on sandstone samples before and after freezing and thawing. The evolution of the pore structure in sandstone at various freezing and thawing stages was studied, and a statistical damage constitutive model was established to validate the test results. The results indicate that the stress–strain curves of sandstone samples under triaxial compression after a freeze–thaw cycle exhibit minimal changes compared to those without freezing at normal temperature. The peak deviator stress shows a decreasing trend with decreasing freezing temperature, particularly between −5 °C and −10 °C, and then gradually stabilizes. The elastic modulus of sandstone with different porosity decreases with the decrease in freezing temperature, and the decrease is more obvious in the range of −5 °C~−10 °C, decreasing by 2.33%, 6.11%, and 10.5%, respectively. Below −10 °C, the elastic modulus becomes similar to that at −10 °C, and the change tends to stabilize. The nuclear magnetic porosity of sandstone samples significantly increases after freezing and thawing. The smaller the initial porosity, the greater the rate of change in nuclear magnetic porosity after a freeze–thaw cycle. The effects of freeze–thaw damage on the T2 distribution of sandstone with different porosity levels vary. We established a statistical damage constitutive model considering the combined effects of freeze–thaw damage, ground stress, and pore water pressure. The compaction coefficient K was introduced into the constitutive model for optimization. The change trend of the theoretical curve closely aligns with that of the test curve, better characterizing the stress–strain relationship of sandstone under complex pressure environments. The research findings can provide a scientific basis for wellbore wall design and subsequent maintenance in complex environments. Full article
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Figure 1
<p>Sample preparation: (<b>a</b>) rock samples; (<b>b</b>) ultrasonic testing; (<b>c</b>) drying oven; (<b>d</b>) sample weighing; (<b>e</b>) saturation; (<b>f</b>) freezing–thawing box; (<b>g</b>) thawing of samples.</p>
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<p>Triaxial test system: (<b>a</b>) rock sample installation; (<b>b</b>) control and monitoring system; (<b>c</b>) pressure control system.</p>
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<p>Triaxial compression stress–strain curves of sandstone with different porosity: (<b>a</b>) <span class="html-italic">n</span> = 3.79%; (<b>b</b>) <span class="html-italic">n</span> = 11.61%; (<b>c</b>) <span class="html-italic">n</span> = 16.21%.</p>
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<p>Relationship curve between peak deviatoric stress and freezing temperature of sandstone.</p>
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<p>Relationship curve between sandstone strength loss rate and freezing temperature.</p>
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<p>Variation of elastic modulus and Poisson’s ratio with freezing temperature: (<b>a</b>) <span class="html-italic">E</span>; (<b>b</b>) Poisson’s ratio.</p>
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<p>T2 spectrum distribution curve and cumulative nuclear magnetic porosity of sandstone before and after freezing: (<b>a</b>) <span class="html-italic">n</span> = 3.79%; (<b>b</b>) <span class="html-italic">n</span> = 11.61%; (<b>c</b>) <span class="html-italic">n</span> = 16.21%.</p>
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<p>Porosity 3.79% sandstone statistical damage constitutive model validation: (<b>a</b>) T = −5 °C; (<b>b</b>) T = −10 °C; (<b>c</b>) T = −15 °C; (<b>d</b>) T = −20 °C.</p>
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<p>Porosity 11.61% sandstone statistical damage constitutive model validation: (<b>a</b>) T = −5 °C; (<b>b</b>) T = −10 °C; (<b>c</b>) T = −15 °C; (<b>d</b>) T = −20 °C.</p>
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<p>Porosity 16.21% sandstone statistical damage constitutive model validation: (<b>a</b>) T = −5 °C; (<b>b</b>) T = −10 °C; (<b>c</b>) T = −15 °C; (<b>d</b>) T = −20 °C.</p>
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<p>Porosity 16.21% sandstone statistical damage constitutive model validation: (<b>a</b>) T = −5 °C; (<b>b</b>) T = −10 °C; (<b>c</b>) T = −15 °C; (<b>d</b>) T = −20 °C.</p>
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30 pages, 5277 KiB  
Article
Sea Anemone Kunitz Peptide HCIQ2c1: Structure, Modulation of TRPA1 Channel, and Suppression of Nociceptive Reaction In Vivo
by Aleksandra N. Kvetkina, Sergey D. Oreshkov, Pavel A. Mironov, Maxim M. Zaigraev, Anna A. Klimovich, Yulia V. Deriavko, Aleksandr S. Menshov, Dmitrii S. Kulbatskii, Yulia A. Logashina, Yaroslav A. Andreev, Anton O. Chugunov, Mikhail P. Kirpichnikov, Ekaterina N. Lyukmanova, Elena V. Leychenko and Zakhar O. Shenkarev
Mar. Drugs 2024, 22(12), 542; https://doi.org/10.3390/md22120542 - 2 Dec 2024
Viewed by 417
Abstract
TRPA1 is a homotetrameric non-selective calcium-permeable channel. It contributes to chemical and temperature sensitivity, acute pain sensation, and development of inflammation. HCIQ2c1 is a peptide from the sea anemone Heteractis magnifica that inhibits serine proteases. Here, we showed that HCIQ2c1 significantly reduces AITC- [...] Read more.
TRPA1 is a homotetrameric non-selective calcium-permeable channel. It contributes to chemical and temperature sensitivity, acute pain sensation, and development of inflammation. HCIQ2c1 is a peptide from the sea anemone Heteractis magnifica that inhibits serine proteases. Here, we showed that HCIQ2c1 significantly reduces AITC- and capsaicin-induced pain and inflammation in mice. Electrophysiology recordings in Xenopus oocytes expressing rat TRPA1 channel revealed that HCIQ2c1 binds to open TRPA1 and prevents its transition to closed and inhibitor-insensitive ‘hyperactivated’ states. NMR study of the 15N-labeled recombinant HCIQ2c1 analog described a classical Kunitz-type structure and revealed two dynamic hot-spots (loops responsible for protease binding and regions near the N- and C-termini) that exhibit simultaneous mobility on two timescales (ps–ns and μs–ms). In modelled HCIQ2c1/TRPA1 complex, the peptide interacts simultaneously with one voltage-sensing-like domain and two pore domain fragments from different channel’s subunits, and with lipid molecules. The model explains stabilization of the channel in the open conformation and the restriction of ‘hyperactivation’, which are probably responsible for the observed analgetic activity. HCIQ2c1 is the third peptide ligand of TRPA1 from sea anemones and the first Kunitz-type ligand of this channel. HCIQ2c1 is a prototype of efficient analgesic and anti-inflammatory drugs. Full article
(This article belongs to the Special Issue Toxins as Marine-Based Drug Discovery, 2nd Edition)
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Figure 1
<p>Analgesic activity of HCIQ2c1 in vivo. (<b>A</b>) The pain threshold in the Hot plate test was detected as latency to withdraw or lick the fore or hind paw. (<b>B</b>) Time-dependent effect of HCIQ2c1 on the volume of paw subcutaneous injected with 0.05% AITC (<b>B1</b>) and Volume Growth Index (%) (<b>B2</b>). (<b>C</b>) Analgesic activity of HCIQ2c1 in a model where pain was induced by subplantar injection of 0.05% AITC. (<b>D</b>) Analgesic activity of HCIQ2c1 in a model where pain was induced by subplantar injection of 6 µg/mouse capsaicin. The pain threshold was detected as: (<b>C1</b>,<b>D1</b>) latency to pain-related response or nociceptive behavior (first licking, tucking, scratching, flicking, or biting the injected hind paw), (<b>C2</b>,<b>D2</b>) time spent tucking the injected paw, (<b>C3</b>,<b>D3</b>) the number of licking the injected paw, and (<b>C4</b>,<b>D4</b>) time spent licking. HCIQ2c1 or saline buffer (control) was administrated intramuscularly 60 min before start of the test (<b>A</b>), or AITC (<b>B</b>,<b>C</b>) or capsaicin (<b>D</b>) injection. Data are presented as mean ± S.E.M. (<span class="html-italic">n</span> = 7). * <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 indicate significant differences between the control and HCIQ2c1 groups according to one-way ANOVA/Dunnett’s multiple comparisons test.</p>
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<p>Recombinant HCIQ2c1 affects the diclofenac-evoked currents in <span class="html-italic">X. laevis</span> oocytes expressing rat TRPA1 in the experiment with 30-s HCIQ2c1 preincubation (<b>A</b>,<b>B</b>) and does not affect the currents in the experiment with 90-s pre-pulse of the agonist and second simultaneous 90-s HCIQ2c1+diclofenac pulse (<b>C</b>,<b>D</b>). (<b>A</b>,<b>C</b>) Average current traces normalized to the amplitude of the currents in the time interval labelled “norm.” (<span class="html-italic">n</span> = 12 (<b>A</b>), <span class="html-italic">n</span> = 6–7 (<b>C</b>), different oocytes were recorded, S.E.M. range is shown as the shade around the trace). Three (<b>A</b>) or two (<b>C</b>) consecutive responses (Control, HCIQ2c1, Wash) were measured on each oocyte at 5 min intervals. Direction of the current is shown by the labels “OUT” and “IN”. The application of compounds is shown by bars above the current traces. The amplitude of responses was measured at time points labeled “test”. The concentrations of diclofenac and HCIQ2c1 were 1 mM and 10 µM, respectively. (<b>B</b>,<b>D</b>) The normalized current amplitudes (mean ± S.E.M.). n.s., not significant. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 indicate significant differences between the “HCIQ2c1” and “Control” data groups with the same direction of currents based on one-sample (<b>B</b>, OUT) and two-sample (<b>B</b>, IN) two-sided <span class="html-italic">t</span>-tests. No significant differences were found for the data presented in panel (<b>D</b>). The non-normalized current traces for the data presented in this figure are shown in <a href="#app1-marinedrugs-22-00542" class="html-app">Figure S2</a>.</p>
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<p>Recombinant HCIQ2c1 affects the residual currents through rat TRPA1 in <span class="html-italic">X. laevis</span> oocytes after 90-s AITC pulse (<b>A</b>,<b>B</b>) and does not affect the currents in the experiment with 100-s AITC pre-pulse, the second simultaneous 100-s HCIQ2c1+AITC pulse, the third ‘readout’ 100-s AITC pulse, and the final application of the antagonist HC030031 (<b>C</b>,<b>D</b>). (<b>A</b>) Average current traces normalized to the amplitude of the currents in the time interval labelled “norm.” (<span class="html-italic">n</span> = 7–8 (<b>A</b>), <span class="html-italic">n</span> = 6–7 (<b>C</b>), each response was measured on a distinct oocyte, S.E.M. range is shown as the shade around the trace). Direction of the current is shown by the labels “OUT” and “IN”. The application of compounds is shown by bars above the current traces. The amplitude of responses was measured at time points labeled “test” or marked with arrows. The TRPA1 antagonist HC030031 was used as a negative control. The concentrations of AITC, HCIQ2c1, and HC030031 were 100 µM, 10 µM, and 50 µM, respectively. (<b>B</b>,<b>D</b>) The normalized current amplitudes (mean ± S.E.M.). * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 indicate significant differences between the “HCIQ2c1” and “Control” data groups with the same direction of currents based on two-sided <span class="html-italic">t</span>-tests. The only significant difference in panel (<b>D</b>) is the difference in residual current level after application of HC030031. The non-normalized current traces for the data presented in this figure are shown in <a href="#app1-marinedrugs-22-00542" class="html-app">Figure S3</a>.</p>
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<p>NMR data define the HCIQ2c1 secondary structure. (<b>A</b>) 2D <sup>15</sup>N-HSQC spectrum of 0.08 mM <sup>15</sup>N-labeled HCIQ2c1 (30 °C, pH 4.5). The resonances of side chain NH<sub>2</sub> groups are connected by dashed lines. The system of minor signals is shown in red color. (<b>B</b>–<b>D</b>) The ring-current contributions from the nearby aromatic side chains explain atypical up–field shifts of <sup>1</sup>H<sup>δ22</sup> Asn45 and <sup>1</sup>H<sup>N</sup> Gly38 resonances (<b>B</b>), <sup>1</sup>H<sub>2</sub>C<sup>β</sup> and <sup>1</sup>H<sub>2</sub>C<sup>γ</sup> resonances of the Lys10 side chain (<b>C</b>), and <sup>1</sup>H<sup>β3</sup> resonance of Cys56 (<b>D</b>). The secondary structure of HCIQ2c1 (<b>E</b>). Elements of the secondary structure were calculated using the STRIDE program [<a href="#B29-marinedrugs-22-00542" class="html-bibr">29</a>] from the determined spatial structure of HCIQ2c1 (see below). The β-strands are designated by arrows, α- and 3<sub>10</sub> helices by rectangles. The L<sub>1</sub> and L<sub>2</sub> loops are underlined. Possible position of the protease cleavage site is shown by red arrow. The probabilities of the residues to participate in the α-helix or β-strand (P<sub>α</sub> and P<sub>β</sub>) were calculated from the chemical shifts in the TALOS-N software [<a href="#B30-marinedrugs-22-00542" class="html-bibr">30</a>]. Asterisks indicate the residues with low amplitude of the amide proton temperature gradient (|Δδ<sup>1</sup>H<sup>N</sup>/ΔT| &lt; 4.5 ppb/°K). Small (&lt;6 Hz), large (&gt;8 Hz), and medium (others) <sup>3</sup>J<sub>H</sub><sup>N</sup><sub>H</sub><sup>α</sup> coupling constants are indicated by empty, filled triangles, and open squares, respectively. Map of NOE contacts (τ<sub>m</sub> = 100 ms) is shown as usual. (<b>F</b>) Topology of the HCIQ2c1 secondary structure. The residues possibly forming a protease binding site are marked.</p>
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<p>The spatial structure and backbone dynamics of HCIQ2c1 in aqueous solution. (<b>A</b>) Two–sided view of the HCIQ2c1 molecule. Positively charged (+His), negatively charged, hydrophobic, and aromatic residues are colored by blue, red, yellow, and green, respectively. The disulfide bonds are shown in orange. (<b>B</b>,<b>C</b>) Two-sided view of the molecular surface of HCIQ2c1. Electrostatic (<b>B</b>) and molecular hydrophobicity [<a href="#B34-marinedrugs-22-00542" class="html-bibr">34</a>] (<b>C</b>) potentials are shown. (<b>D</b>) Regions with high-amplitude mobility on the ps–ns time-scale (where S<sup>2</sup> &lt; 0.75 or <sup>15</sup>N–{<sup>1</sup>H} NOE &lt; 0.65) are shown in cyan color. (<b>E</b>) Regions with mobility on the μs–ms time-scale are shown in purple (R<sub>EX</sub> ≥ 3.0 s<sup>−1</sup> or R<sub>1</sub> × R<sub>2</sub> &gt; 20.0 s<sup>−2</sup>) and blue (3 ≥ R<sub>EX</sub> &gt; 0 s<sup>−1</sup>) colors. The residues demonstrating line-broadening due to intense μs–ms time-scale motions (Cys15 and Gly38) are shown in green color. Regions where signal doubling was observed due to mobility on the millisecond time-scale are shown in red color.</p>
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<p>Best docking solutions of the TRPA1/HCIQ2c1 complex, viewed from the extracellular side. The four subunits of the open rat TRPA1 channel are shown by differently colored surfaces (<b>A</b>–<b>D</b>). Each subunit includes a ¼ of the pore domain (PD; in center) and the voltage-sensing-like domain (VSLD; distal). The HCIQ2c1 backbone is spectrum colored from blue (<span class="html-italic">N</span>-terminus) to red (<span class="html-italic">C</span>-terminus). Disulfide bonds are shown in yellow. The glycans on the VSLDs were modeled in MD but omitted in docking.</p>
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<p>MD snapshot of the best TRPA1/HCIQ2c1 complex (5–1, see <a href="#app1-marinedrugs-22-00542" class="html-app">Table S5</a>). Colors and designations are the same as in <a href="#marinedrugs-22-00542-f006" class="html-fig">Figure 6</a>. The <span class="html-italic">N</span>-glycan groups attached to Asn749 and Asn755 on the S1–S2 loop of each VSLD are represented as sticks and colored by atom type. (<b>A</b>,<b>B</b>) Top and side view on the simulation system. Membrane lipids are shown as a surface; water and ions are omitted. In (<b>B</b>), the nearby membrane slab is hidden for clarity. (<b>C</b>,<b>D</b>) Close-up top and side views of the TRPA1/HCIQ2c1 complex. Active residues are shown as sticks and colored according to the residue type: positively charged—blue, negatively charged—red, polar—violet, hydrophobic/aromatic—green, cysteines—yellow. Channel residues are italicized and shown in thinner and lighter sticks. POPC lipids and glycine residues are shown with sticks colored by atom type.</p>
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<p>Comparison of HCIQ2c1 with other Kunitz-type peptides. (<b>A</b>) Multiple sequence alignment. Positively and negatively charged residues are indicated by blue and red squares respectively; cysteines are shown in yellow. The green arrow shows a site resistant to proteolytic cleavage, but not all listed peptides demonstrate protease inhibition activity. Cyan boxes indicate the residues involved in TRPV1 inhibition by HCRG21 and APHC1, and regions responsible for the HCIQ2c1 binding to rat TRPA1 in complex 5-1. Magenta boxes indicate the residues involved in interaction with K<sup>+</sup>-channels. Orange boxes show the residues critical for mambaquaretin-1 (MQ-1) interaction with the type-2 vasopressin receptor. Conserved disulfide bonds and secondary structure elements defining Kunitz-fold are shown. Black arrows and white box indicate the β-strands and α-helix, respectively; wavy lines show the L<sub>1</sub> and L<sub>2</sub> loops. Sequence identity with HCIQ2c1 (%), PDB codes, and root mean square deviation (RMSD) values calculated over C<sub>α</sub>-atoms in regions of conserved secondary structure (19–36, 45–57) are shown on the right. (<b>B</b>) Comparison of the spatial structures of HCIQ2c1 with other Kunitz-type peptides (see legend for color code). The backbones of the peptides are shown as ribbons, cysteines are shown in yellow, and conserved Arg/Lys residues at position P<sub>1</sub> of the protease binding site are shown as sticks.</p>
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16 pages, 2594 KiB  
Article
Structural Characterization of Mycobacterium tuberculosis Encapsulin in Complex with Dye-Decolorizing Peroxide
by Bonnie J. Cuthbert, Xiaorui Chen, Kalistyn Burley, Gaëlle Batot, Heidi Contreras, Shandee Dixon and Celia W. Goulding
Microorganisms 2024, 12(12), 2465; https://doi.org/10.3390/microorganisms12122465 - 30 Nov 2024
Viewed by 459
Abstract
Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the world’s deadliest infectious disease. Mtb uses a variety of mechanisms to evade the human host’s defenses and survive intracellularly. Mtb’s oxidative stress response enables Mtb to survive within activated macrophages, an environment with [...] Read more.
Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, the world’s deadliest infectious disease. Mtb uses a variety of mechanisms to evade the human host’s defenses and survive intracellularly. Mtb’s oxidative stress response enables Mtb to survive within activated macrophages, an environment with reactive oxygen species and low pH. Dye-decolorizing peroxidase (DyP), an enzyme involved in Mtb’s oxidative stress response, is encapsulated in a nanocompartment, encapsulin (Enc), and is important for Mtb’s survival in macrophages. Encs are homologs of viral capsids and encapsulate cargo proteins of diverse function, including those involved in iron storage and stress responses. DyP contains a targeting peptide (TP) at its C-terminus that recognizes and binds to the interior of the Enc nanocompartment. Here, we present the crystal structure of the Mtb-Enc•DyP complex and compare it to cryogenic-electron microscopy (cryo-EM) Mtb-Enc structures. Investigation into the canonical pores formed at symmetrical interfaces reveals that the five-fold pore for the Mtb-Enc crystal structure is strikingly different from that observed in cryo-EM structures. We also observe DyP-TP electron density within the Mtb-Enc shell. Finally, investigation into crystallographic small-molecule binding sites gives insight into potential novel avenues by which substrates could enter Mtb-Enc to react with Mtb-DyP. Full article
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Figure 1
<p>Crystallographic structure of Mtb-Enc•DyP. (<b>A</b>) The encapsulin shell generated by crystallographic symmetry is shown in cartoon representation and colored to highlight the five-fold axis. The nanocompartment has a diameter of ~24 nm as measured with Draw Protein Dimensions script [<a href="#B39-microorganisms-12-02465" class="html-bibr">39</a>]. (<b>B</b>) Structure of a single subunit of Mtb-Enc in cartoon representation colored by secondary structure: α-helices are in cyan, β-sheets in pink, and loops are wheat-colored. A- and P-domains, and E-loop are labelled, as are N- and C-termini and secondary structure elements. (<b>C</b>) Pores formed by two-fold, three-fold, and five-fold symmetry in the Mtb-Enc shell. The molecular surface of the protein is colored as in A. The two-fold, three-fold, and five-fold pores are indicated by diamond, triangle and pentamer symbols, respectively. A closer view of each pore is provided. Figures generated in PyMOL [<a href="#B39-microorganisms-12-02465" class="html-bibr">39</a>].</p>
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<p>Five-fold major pore and surrounding exterior surface of Mtb-Enc shell. (<b>A</b>) The electrostatic exterior surfaces of the five-fold point of symmetry at pH 4.5 and pH 7.5, generated by pdb2qr and APBS [<a href="#B41-microorganisms-12-02465" class="html-bibr">41</a>,<a href="#B42-microorganisms-12-02465" class="html-bibr">42</a>]. Surfaces are colored according to charge, ranging from red (negatively charged) to blue (positively charged). Pore diameter determined by CAVER [<a href="#B43-microorganisms-12-02465" class="html-bibr">43</a>]. (<b>B</b>) Stick representation of the charged residues that line the central pore as viewed from the exterior. For comparison with cryo-EM structures, the crystal structure is shown in white.</p>
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<p>The five-fold minor pore is formed between Mtb-Enc subunits along the five-fold symmetry axis. (<b>A</b>) Mtb-Enc is shown as a cyan cartoon, and ligand occupying the minor pores are shown in sphere representation with yellow carbon and red oxygen atoms. (<b>B</b>–<b>D</b>) The minor pore at the interface of the C (cyan) and F (white) subunits. Protein is shown in cartoon and residues that line the pore are shown as sticks. The PEG molecule occupying the pore is shown as stick representation with wheat-colored carbons in (<b>B</b>), while a depiction of the pore generated in MOLE is shown in (<b>C</b>,<b>D</b>). The pore is viewed from the side in (<b>B</b>), from the interior in (<b>C</b>), and from the exterior in (<b>D</b>).</p>
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<p>The five-fold minor pores across Enc structures. Shown here is the interior (<b>A</b>) and exterior (<b>B</b>) electrostatic surface of various Mtb, Msm, and Kpn cryo-EM structures in addition to the Mtb crystal structure at the five-fold minor pores. Notably, in the crystal structure the minor pores are occupied by small molecules (shown as spheres with yellow carbons). The green inset box indicates the region depicted below for comparison with the other structures. Surfaces are colored as in <a href="#microorganisms-12-02465-f002" class="html-fig">Figure 2</a>A.</p>
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<p>Enc recognition of the C-terminal targeting peptide (TP) of DyP. (<b>A</b>) Enc residues that coordinate the TP (subunit i, yellow stick) are shown. Enc (subunit I) is displayed as a cyan cartoon with residues involved in TP binding shown as sticks. H-bond contacts are highlighted as dashed black lines between Enc residues and DyP-TP. (<b>B</b>) A sequence alignment of the C-terminus of DyP for Mtb<span class="html-italic">,</span> Msm<span class="html-italic">,</span> and Kpn was generated by Clustal Omega [<a href="#B51-microorganisms-12-02465" class="html-bibr">51</a>]. A cartoon representation of the secondary structure elements for characterized DyP proteins is shown above the alignment, and a yellow line indicates the sequence modelled for DyP-TP-i (shown in (<b>A</b>)). Mtb-DyP is missing residues upstream of the DyP-TP when compared to DyP from other species. Symbols below the alignment indicate the degree of sequence conservation, where * denotes fully conserved residues, : strongly similar residues, and . weakly similar residues.</p>
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21 pages, 6957 KiB  
Article
Impact of Metal Source Structure on the Electrocatalytic Properties of Polyacrylonitrile-Derived Co-N-Doped Oxygen Reduction Reaction Catalysts
by Arseniy Kalnin, Ksenia Kharisova, Daniil Lukyanov, Sofia Filippova, Ruopeng Li, Peixia Yang, Oleg Levin and Elena Alekseeva
Nanomaterials 2024, 14(23), 1924; https://doi.org/10.3390/nano14231924 - 29 Nov 2024
Viewed by 386
Abstract
The oxygen reduction reaction (ORR) plays a central role in energy conversion and storage technologies. A promising alternative to precious metal catalysts are non-precious metal doped carbons. Considerable efforts have been devoted to cobalt-doped carbonized polyacrylonitrile catalysts, but the optimization of their catalytic [...] Read more.
The oxygen reduction reaction (ORR) plays a central role in energy conversion and storage technologies. A promising alternative to precious metal catalysts are non-precious metal doped carbons. Considerable efforts have been devoted to cobalt-doped carbonized polyacrylonitrile catalysts, but the optimization of their catalytic performance remains a key challenge. We have proposed a multifunctional active metal source strategy based on the cobalt complex with the ligand containing pyridine and azo-fragments. This complex simultaneously provides the nitrogenous environment for the Co atoms and acts as a blowing agent due to N2 extrusion, thus increasing the surface area and porosity of the material. This strategy provided the catalysts with a high surface area and pore volume, combined with the greater fraction of Co-N clusters, and a lesser amount and smaller size of Co metal particles compared to conventionally prepared catalysts, resulting in improved catalytic performance. In addition to strict 4-electron ORR kinetics and 383 mV overpotential, the novel catalysts exhibit limiting current values close to the Pt/C benchmark and greatly overcome the Pt in methanol tolerance. These results demonstrate the critical role of metal source structure and carbonization parameters in tailoring the structural and electrochemical properties of the catalysts. Full article
(This article belongs to the Special Issue Advanced Understanding of Metal-Based Catalysts)
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<p>Structure of the CoL<sub>2</sub> complex.</p>
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<p>The scheme of the catalyst preparation.</p>
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<p>Synchronized thermal analysis heating rate of 5 °C min<sup>−1</sup>.</p>
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<p>SEM images of the catalysts: (<b>A</b>) CN<sub>x</sub>; (<b>B</b>) CoAcCN<sub>x</sub>-700; (<b>C</b>) CoL<sub>2</sub>CN<sub>x</sub>-700; (<b>D</b>) CoL<sub>2</sub>CN<sub>x</sub>-900; (<b>E</b>) CoL<sub>2</sub>CN<sub>x</sub>-1100; (<b>F</b>,<b>G</b>) EDX images of CoL<sub>2</sub>CN<sub>x</sub>-900.</p>
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<p>(<b>A</b>) Nitrogen adsorption–desorption isotherm; (<b>B</b>) pore size distribution curves.</p>
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<p>XRD pattern of the catalysts.</p>
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<p>Raman spectra of the catalysts.</p>
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<p>FT-IR spectra of the catalysts.</p>
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<p>Core-level XPS spectra: (<b>A</b>) N<sub>1S</sub>; (<b>B</b>) Co<sub>2p</sub> of the catalysts.</p>
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<p>CVs of investigated materials in 0.1 M KOH electrolyte purged with Ar (dashed lines) and O<sub>2</sub> (solid lines).</p>
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<p>RDE voltammograms of investigated materials in 0.1 M KOH electrolyte purged with O<sub>2</sub> measured at 5000 rpm (dotted line indicated onset current). Insert is the magnification of onset current region of the CV.</p>
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<p>Kinetic currents: (<b>A</b>) normalized to the geometric surface area; (<b>B</b>) normalized to the real surface area.</p>
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<p>RDE cyclic voltammetry of CoL<sub>2</sub>CN<sub>x</sub>-1100 in 0.1 M KOH electrolyte purged with O<sub>2</sub>.</p>
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<p>Levich–Koutecky analysis of RDE CVs of investigated materials in 0.1 M KOH electrolyte purged with O<sub>2</sub>.</p>
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<p>(<b>A</b>) Comparative methanol tolerance of CoL<sub>2</sub>CN<sub>x</sub>-1100 C and Pt/C. For each material, the current is normalized to its maximum value. (<b>B</b>) Long-term stability test of CoL<sub>2</sub>CN<sub>x</sub>-1100 °C.</p>
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24 pages, 16131 KiB  
Article
Characteristics and Controlling Factors of Natural Fractures in Lacustrine Mixed Shale Oil Reservoirs: The Upper Member of the Lower Ganchaigou Formation in the Ganchaigou Area, Qaidam Basin, Western China
by Xing Zhao, Guiwen Wang, Dong Li, Song Wang, Quanwei Sun, Jin Lai, Zongyan Han, Yafeng Li, Yinghao Shen and Kunyu Wu
Energies 2024, 17(23), 5996; https://doi.org/10.3390/en17235996 - 28 Nov 2024
Viewed by 349
Abstract
Natural fractures within the lacustrine mixed shale oil reservoirs of the upper member of the Lower Ganchaigou Formation (E32) in the Ganchaigou area of the Qaidam Basin are pivotal to the exploration and development of shale oil and gas. This [...] Read more.
Natural fractures within the lacustrine mixed shale oil reservoirs of the upper member of the Lower Ganchaigou Formation (E32) in the Ganchaigou area of the Qaidam Basin are pivotal to the exploration and development of shale oil and gas. This research investigates the developmental characteristics and controlling factors of natural fractures and their impact on the reservoir quality based on cores, image logs, thin sections, scanning electron microscopy observations, and experimental and production data. The results indicate that natural fractures in the E32 are categorized into tectonic fractures, diagenetic fractures, and abnormal high-pressure fractures. Tectonic fractures are characterized by a significant variation in dip angles, a wide range of apertures, low density, and a high filling degree. Diagenetic fractures typically exhibit low dip angles, small apertures, high density, and a low filling degree. Abnormal high-pressure fractures display chaotic orientations and complex styles, often consisting of filled fractures. The development and distribution of natural fractures are jointly influenced by mineral composition and brittleness, lamination structure, organic matter content and maturity, diagenesis, tectonic factors, and abnormal high pressure. A high content of dolomite, thin-bedded structures comprising carbonate laminae and felsic laminae, and abundant mature organic matter provide a favorable foundation for fracture development. Diagenesis, including dissolution, pressure solution, and mineral dehydration shrinkage, acts as a beneficial guarantee for fracture development. Tectonic locations near the hanging wall of faults and the core of anticlines are the main regions for fracture development. Abnormal high pressure is a crucial driving force for fracture development. Interconnected natural fractures of various types and scales significantly expand reservoir space and enhance pore connectivity and flow capacity, serving a vital function in maintaining high and stable production in lacustrine mixed shale oil reservoirs. Full article
(This article belongs to the Section H: Geo-Energy)
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Figure 1
<p>A regional index map showing the study area. (<b>A</b>) The location of Qaidam Basin in China. (<b>B</b>) A map showing the division of tectonic units in Qaidam Basin and the location of the Ganchaigou area in the Yingxiongling structural belt (modified from Li et al., 2022) [<a href="#B9-energies-17-05996" class="html-bibr">9</a>]. (<b>C</b>) A structural map showing key well locations and major faults in the Ganchaigou area (modified from Guo et al., 2023) [<a href="#B41-energies-17-05996" class="html-bibr">41</a>].</p>
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<p>Sedimentary facies and stratigraphic column in the Ganchaigou area, Qaidam Basin (modified from Li et al., 2022) [<a href="#B9-energies-17-05996" class="html-bibr">9</a>].</p>
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<p>Mineral composition of the upper member of the Lower Ganchaigou Formation in the study area (well C908). (<b>A</b>) Mineral composition at different depths; (<b>B</b>) average content of minerals.</p>
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<p>Petrological characteristics of shale oil reservoirs in upper member of Lower Ganchaigou Formation. (<b>A</b>) Argillaceous shale, well C908, 2796.47–2796.62 m, external surface of core; (<b>B</b>) calcareous dolomitic shale, well C13, 3725.67–3725.82 m, external surface of core; (<b>C</b>) dolomitic calcareous shale, well C2-4, 2822.08–2822.23 m, external surface of core; (<b>D</b>) calcareous dolomite, well C12, 3559.30–3559.45 m, external surface of core; (<b>E</b>) argillaceous shale, well C13, 3726.07 m, cross-polarized light; (<b>F</b>) dolomitic calcareous shale, well C2-4, 2844.47 m, cross-polarized light; (<b>G</b>) calcareous dolomitic shale, well C14, 3846.86 m, cross-polarized light; (<b>H</b>) argillaceous shale, well C12, 3600.78 m, cross-polarized light; (<b>I</b>) calcareous dolomite, well C908, 2772.46 m, cross-polarized light; (<b>J</b>) argillaceous siltstone, well C14, 3845.82 m, cross-polarized light.</p>
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<p>Scanning electron microscope (SEM) images show pore types in upper member of Lower Ganchaigou Formation. (<b>A</b>) Dolomite intercrystalline pores, well C2-4, 2817.18 m; (<b>B</b>) dolomite intercrystalline pores, well C906, 3229.29 m; (<b>C</b>) pyrite intercrystalline pores, well C14, 3831.82 m; (<b>D</b>) intercrystalline pores in clay minerals, well C14, 3845.61 m; (<b>E</b>) weak dissolution occurred along edges of intercrystal pores, well C908, 3275.91 m; (<b>F</b>) organic matter pores, well C2-4, 2822.69 m.</p>
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<p>A cross-plot of porosity versus permeability for shale oil reservoirs in the upper member of the Lower Ganchaigou Formation.</p>
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<p>Core photos show natural fractures in upper member of Lower Ganchaigou Formation. (<b>A</b>) High-angle unfilled shear fractures, well C12, 3599.58–3599.71 m, external surface of core; (<b>B</b>) low-angle unfilled shear fractures, well C13, 3718.19–3718.32 m, external surface of core; (<b>C</b>) vertical tensional fractures are filled with anhydrite and calcite, well C908, 2796.78–2796.91 m, external surface fluorescence image of core; (<b>D</b>) low-angle shear fractures are filled with anhydrite and calcite, well C908, 2786.50–2786.82 m, circumferential surface fluorescence image of core; (<b>E</b>) V-shaped shrinkage fractures are filled with calcite, well C13, 3723.48–3723.61 m, external surface of core; (<b>F</b>) dissolution fractures are filled with calcite, well C12, 3530.32–3530.45 m, external surface of core; (<b>G</b>) bedding fractures parallel to bedding planes, well C2-4, 2799.50–2799.65 m, longitudinal section of core; (<b>H</b>) bedding fractures parallel to bedding planes, well C14, 3847.00–3847.19 m, circumferential surface of core; (<b>I</b>) abnormal high-pressure fractures are filled with anhydrite, well C908, 2785.11–2785.39 m, circumferential surface fluorescence image of core.</p>
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<p>Image log responses of natural fractures in upper member of Lower Ganchaigou Formation of Ganchaigou area. (<b>A</b>) Calcite-filled high-angle fractures, well C14; (<b>B</b>) high-angle fractures, well C908; (<b>C</b>) induced fracture, well C2-4; (<b>D</b>) anhydrite-filled low-angle fractures, well C14; (<b>E</b>) low-angle fractures, well C908; (<b>F</b>) bedding fractures parallel to bedding planes, well C908.</p>
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<p>Occurrence parameters of fractures in upper member of Lower Ganchaigou Formation of Ganchaigou area. (<b>A</b>) Strike rose diagram of natural fractures derived from core samples and image logs; red represents conductive fractures (unfilled fractures), green represents resistive fractures (filled fractures). (<b>B</b>) Strike rose diagram of induced fractures derived from image logs; (<b>C</b>) frequency distribution of the dip angle for natural fractures measured from core samples and image logs.</p>
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<p>Thin sections and SEM images show natural fractures in upper member of Lower Ganchaigou Formation. (<b>A</b>–<b>F</b>) Casting thin section images, (<b>G</b>) SEM images of freshly broken rock samples, (<b>H</b>,<b>I</b>) SEM images of argon ion-milled samples. (<b>A</b>) Tectonic microfracture is filled with minerals such as anhydrite, calcite, and pyrite (Py), well C12, 3529.90 m, polarized light; (<b>B</b>) microfracture parallel to bedding, well C14, 3861.23 m, polarized light; (<b>C</b>) microfracture parallel to bedding, well C12, 3609.03 m, vertical section, polarized light; (<b>D</b>) shrinkage microfractures are filled with anhydrite and calcite, well C906, 3227.21 m, polarized light; (<b>E</b>) dissolution microfractures, well C2-4, 2828.69 m, polarized light; (<b>F</b>) abnormal high-pressure fractures (yellow arrow), stylolite (red arrow), and open microfractures (blue arrow), well C2-4, 2818.45 m, polarized light; (<b>G</b>) tectonic microfracture, well C2-4, 2822.69 m; (<b>H</b>) shrinkage microfracture, well C14, 3842.21 m; (<b>I</b>) dissolution microfracture, partially filled with organic matter (OM), well C13, 4216.26 m.</p>
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<p>Relationship between fracture density, mineral composition, and rock brittleness. (<b>A</b>) Cross-plot of carbonate content versus brittleness index; (<b>B</b>) cross-plot of felsic (quartz+feldspar) content versus brittleness index; (<b>C</b>) cross-plot of clay content versus brittleness index; (<b>D</b>) cross-plot of fracture density versus brittleness index; (<b>E</b>) cross-plot of carbonate content versus fracture density; (<b>F</b>) cross-plot of dolomite and calcite versus fracture density; (<b>G</b>) cross-plot of felsic content versus fracture density; (<b>H</b>) cross-plot of quartz and feldspar content versus fracture density. n, number of samples; r, correlation coefficient.</p>
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<p>Relationship between lamination structure and fracture development. (<b>A</b>) Boxplot showing fracture density of different mineral laminae; (<b>B</b>) boxplot showing fracture density of different mineral laminae combinations; (<b>C</b>) boxplot showing fracture density of different bedding structures; (<b>D</b>) bar chart showing average fracture density of different mineral lamina combinations and bedding structure. I+F, combination of clay laminae and felsic laminae; C+I, combination of carbonate laminae and clay laminae; C+F, combination of carbonate laminae and felsic laminae; C+F+I, combination of carbonate laminae, felsic laminae, and clay laminae; LS, laminated structure; TBS, thin-bedded structure; THBS, thick-bedded structure.</p>
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<p>Relationship between organic matter content and fracture development. (<b>A</b>) Cross-plot of total fracture density versus total organic carbon (TOC) content; (<b>B</b>) cross-plot of tectonic fracture density versus TOC; (<b>C</b>) cross-plot of non-tectonic fracture density versus TOC; (<b>D</b>) boxplot showing non-tectonic fracture density of different TOC distribution range.</p>
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<p>Relationship between organic matter maturity and fracture development. (<b>A</b>) Cross-plot of tectonic fracture density versus vitrinite reflectance (Ro); (<b>B</b>) cross-plot of non-tectonic density versus Ro.</p>
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<p>Relationship between tectonic position and fracture development. (<b>A</b>) Cross-plot showing density of tectonic fractures at different segments and distances from fault; (<b>B</b>) cross-plot showing density of tectonic fractures at different distances from anticline core. Solid line in (<b>A</b>,<b>B</b>) represents trend line based on statistics of all data points, dashed lines in (<b>A</b>) represents trend line based on the corresponding series of data points.</p>
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<p>The relationship between oil production and fracture development.</p>
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11 pages, 4179 KiB  
Article
Water Sorption Properties and Hydrothermal Stability of Al-Containing Metal–Organic Frameworks CAU-10 and MIL-96 Studied Using Quasi-Equilibrated Thermodesorption
by Waclaw Makowski, Patrycja Gryta, Gabriela Jajko-Liberka, Monika Cieślik-Górna and Aleksandra Korzeniowska
Molecules 2024, 29(23), 5625; https://doi.org/10.3390/molecules29235625 - 28 Nov 2024
Viewed by 253
Abstract
A novel experimental technique, quasi-equilibrated temperature-programmed desorption and adsorption (QE-TPDA), was used to study the water sorption properties and hydrothermal stability of aluminum trimesate MIL-96 and aluminum isophthalate CAU-10, which have been selected due to their remarkable sorption properties. The QE-TPDA profiles of [...] Read more.
A novel experimental technique, quasi-equilibrated temperature-programmed desorption and adsorption (QE-TPDA), was used to study the water sorption properties and hydrothermal stability of aluminum trimesate MIL-96 and aluminum isophthalate CAU-10, which have been selected due to their remarkable sorption properties. The QE-TPDA profiles of water observed for MIL-96 and CAU-10 confirmed the hydrophilic nature of these materials. Complex QE-TPDA profiles indicate that water sorption in MIL-96 follows a three-step pore filling mechanism. The shape of single desorption peaks in the QE-TPDA profiles for CAU-10 confirms that water sorption involves a reversible phase transition. Based on the QE-TPDA profiles, the water adsorption heat was determined: 45–46 kJ/mol for CAU-10 and 43–56 kJ/mol for MIL-96, in the latter case depending on the adsorption extent. Hydrothermal stability tests revealed that MIL-96 retained its stable porosity-related sorption capacity for water after hydrothermal treatment up to 290 °C. Gradual changes in the QE-TPDA profiles due to the hydrothermal treatment above 290 °C, with decreasing the high-temperature desorption peak and increasing the low-temperature one, indicate minor structural changes occurring in this material. Only after 410 °C treatment was fast degradation of MIL-96 observed. CAU-10 exhibited high and unchanged hydrothermal stability up to 400 °C. Full article
(This article belongs to the Special Issue Porous Organic Materials: Design and Applications: Volume II)
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<p>The isotherms of water adsorption and desorption measured at 25 °C (<b>A</b>) and QE-TPDA profiles (<b>B</b>) of water observed for CAU-10, as well as the integral adsorption and desorption curves (<b>C</b>), based on the thermodesorption profiles. Experimental details of QE-TPDA: inlet partial pressure of water p<sub>in</sub> = 1.9 kPa, sample mass m = 3.3 mg, carrier gas (He) flowrate F = 7.2 cm<sup>3</sup>/min.</p>
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<p>The QE-TPDA profiles from <a href="#molecules-29-05625-f001" class="html-fig">Figure 1</a>B transformed according to the van’t Hoff equation. The formulae in the insets indicate the values of the adsorption enthalpy and entropy and correlation coefficients obtained by linear regression of overlapping fragments of the profiles.</p>
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<p>The isotherms of water adsorption and desorption (<b>A</b>) and QE-TPDA profiles (<b>B</b>) of water observed for MIL-96, as well as the integral adsorption and desorption curves (<b>C</b>), based on the QE-TPDA profiles from B. Experimental details of QE-TPDA: inlet partial pressure of water p<sub>in</sub> = 2.4 kPa, sample mass m = 5.7 mg, carrier gas (He) flowrate F = 7.2 cm<sup>3</sup>/min.</p>
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<p>The QE-TPDA profiles (<b>A</b>) of water observed in the new experimental system for MIL-96 at a heating/cooling rate of 2 °C/min at different inlet partial pressures, and the corresponding integral desorption curves (<b>B</b>). The points indicate data found for the preset adsorbed amount values (from 25.5 to 209.5 mg/g, with 11.5 mg/g interval). Experimental details: sample mass m = 5.5 mg, carrier gas (N<sub>2</sub>) flowrate F = 8.0 cm<sup>3</sup>/min.</p>
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<p>(<b>A</b>) The transformed adsorption isosteres of water on MIL-96 calculated from data indicated as points in <a href="#molecules-29-05625-f004" class="html-fig">Figure 4</a>. (<b>B</b>) Isosteric adsorption heat of water on MIL-96 obtained from analysis of the adsorption isosteres. The blue line indicates the values of the condensation heat of water, corresponding to the average temperatures of particular isosteres.</p>
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<p>Illustration of the principle of the hydrothermal stability test: the evolution of the sample temperature and the detector signal during a single desorption–adsorption cycle. This example corresponds to the first cycle recorded for MIL-96 (see <a href="#molecules-29-05625-f007" class="html-fig">Figure 7</a>). The diagnostic segment and the hydrothermal treatment segment are indicated by thick black and dark red lines, respectively.</p>
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<p>Results of the hydrothermal stability test for MIL-96: selected QE-TPD profiles corresponding to the last cycle in the 3-cycle sequences (<b>A</b>) and evolution of the hydrothermal treatment temperature and sorption capacity with the cycle number (<b>B</b>). Experimental details: heating rate β = 2 °C/min, inlet partial pressure of water p<sub>in</sub> = 2.8 kPa, sample mass m = 3.0 mg, carrier gas (N<sub>2</sub>) flowrate F = 8.0 cm<sup>3</sup>/min.</p>
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<p>Powder XRD patterns of MIL-96 samples after the QE-TPDA hydrothermal stability tests interrupted at different temperatures compared with the pattern recorded for the as-synthesized sample.</p>
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<p>Results of the hydrothermal stability test for CAU-10: selected QE-TPD profiles corresponding to the last cycle in the 3-cycle sequence (<b>A</b>) and evolution of the hydrothermal treatment temperature and sorption capacity with the cycle number (<b>B</b>). Experimental details: heating rate β = 1 °C/min, inlet partial pressure of water p<sub>in</sub> = 2.8 kPa, sample mass m = 3.0 mg, carrier gas flowrate F = 8.0 cm<sup>3</sup>/min.</p>
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<p>Powder XRD patterns of CAU-10 samples before and after the QE-TPDA of H<sub>2</sub>O measurements.</p>
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15 pages, 2394 KiB  
Article
Structures and Luminescent Sensing Properties of Terbium Metal–Organic Frameworks with Methyl-Decorated Phenanthroline Ligand
by Anna A. Ovchinnikova, Pavel A. Demakov, Alexey A. Ryadun, Vladimir P. Fedin and Danil N. Dybtsev
Crystals 2024, 14(12), 1026; https://doi.org/10.3390/cryst14121026 - 27 Nov 2024
Viewed by 340
Abstract
Two new Tb(III) metal–organic frameworks based on 4,7-dimethylphenanthroline (dmphen) and flexible ligand trans-1,4-cyclohexanedicarboxylate (chdc2−) were synthesized and characterized. Their crystallographic formulae are [Tb2(dmphen)2(H2O)2(chdc)3]·2DMF (1; DMF = N,N-dimethylformamide) and [...] Read more.
Two new Tb(III) metal–organic frameworks based on 4,7-dimethylphenanthroline (dmphen) and flexible ligand trans-1,4-cyclohexanedicarboxylate (chdc2−) were synthesized and characterized. Their crystallographic formulae are [Tb2(dmphen)2(H2O)2(chdc)3]·2DMF (1; DMF = N,N-dimethylformamide) and [Tb2(dmphen)2(NO3)2(chdc)2]·2DMF (2). Among some differences in their synthetic conditions, the most important one is apparently the using of terbium(III) nitrate instead of terbium(III) chloride as a metal precursor in the synthesis of 2, providing a nitrate coordination to Tb3+, and its subsequent notable structural differences to 1. Compound 1 was found to have a layered hcb structure with intralayer windows ca. 10 × 8 Å2 in size. Its layer-to-layer packing leaves narrow channels running across these windows, with 18% as a total solvent-accessible volume in the coordination structure. Compound 2 was found to have a layered sql structure with smaller intralayer windows of ca. 8 × 6 Å2 in size. Methyl substituents on the phen ligands do not affect the topology of the framework but seem to have a substantial effect on the packing density, as well as the pore volume of the resulting MOF. A high 18.4% luminescence quantum yield was found for 2. Its emission lifetime of 0.695(12) ms belongs to a typical range for phosphorescent Tb(III)-carboxylate complexes. A quenching of its emission by different nitroaromatic molecules was found. A linear concentration dependence on 3-nitrotoluene and 4-nitro-m-xylene at micromolar concentrations was found during luminescent titration experiments (LOD values ca. 350 nM), suggesting this MOF to be a viable and highly sensitive luminescent sensor for such substrates. Full article
(This article belongs to the Section Organic Crystalline Materials)
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Figure 1
<p>Coordination environment of Tb(III) in <b>1</b> (<b>a</b>) and view of coordination layer (<b>b</b>). Tb atoms are shown in green, O in red, N in blue; H atoms of water molecules are shown in orange. Two adjacent layers in 3D packing of <b>1</b> (<b>c</b>). Atoms of independent layers are shown in different colors. The hydrogen atoms of the organic ligands are omitted for clarity.</p>
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<p>Binuclear carboxylate block in <b>2</b> (<b>a</b>) and view of coordination layer (<b>b</b>). Tb atoms are shown in green, O in red, and N in blue. Two adjacent layers in 3D package of <b>2</b> (<b>c</b>). Atoms of independent layers are shown in different colors.</p>
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<p>Experimental PXRD pattern of sample <b>2</b> compared to the theoretical one (<b>a</b>). TGA plot of sample <b>2</b> (<b>b</b>).</p>
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<p>Solid-state excitation and emission spectra for compound <b>2</b>.</p>
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<p>Emission spectra of <b>2</b> dispersion in the presence of analytes with the concentrations shown in the legend: nitrobenzene (<b>a</b>); 2-nitrotoluene (<b>b</b>); 3-nitrotoluene (<b>c</b>); and 4-nitro-<span class="html-italic">m</span>-xylene (<b>d</b>).</p>
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<p>Stern–Volmer plots for <b>2</b> dispersion in the presence of analytes: nitrobenzene (<b>a</b>); 2-nitrotoluene (<b>b</b>); 3-nitrotoluene (<b>c</b>); and 4-nitro-<span class="html-italic">m</span>-xylene (<b>d</b>).</p>
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26 pages, 9559 KiB  
Article
Damage Evolution and NOx Photocatalytic Degradation Performance of Nano-TiO2 Concrete Under Freeze–Thaw Cycles
by Zongming Jia, Yanru Zhao and Hengmao Niu
Buildings 2024, 14(12), 3763; https://doi.org/10.3390/buildings14123763 - 26 Nov 2024
Viewed by 313
Abstract
The internal pore structure of nano-TiO2 concrete deteriorates gradually during freeze–thaw (F–T) cycles. The deterioration process can reveal the F–T damage mechanism and the deterioration law of photocatalytic performance. The evolution law of the pore structure of nano-TiO2 concrete during F–T [...] Read more.
The internal pore structure of nano-TiO2 concrete deteriorates gradually during freeze–thaw (F–T) cycles. The deterioration process can reveal the F–T damage mechanism and the deterioration law of photocatalytic performance. The evolution law of the pore structure of nano-TiO2 concrete during F–T damage was investigated. Moreover, this paper defined the microscopic F–T damage factor based on porosity and fractal dimension. The results showed that a 2% dosage of nano–TiO2 concrete had better frost resistance and lower porosity in this experiment. Its porosity only increased by 13.3% after 200 F–T cycles, which was much smaller than that of ordinary concrete. Furthermore, the presence of nano-TiO2 enhanced the volume fractal dimension of concrete pores larger than 100 nm, increasing the complexity of the pore structure and contributing to improved frost resistance. F–T damage led to a decrease in the photocatalytic performance of nano–TiO2 concrete. Still, it helped the nitrate on the surface of the concrete to dissolve and disappear more quickly under rainwater washout. Finally, a thermodynamic theory-based concrete F–T damage correction model was constructed, and the model was used to predict F–T damage values for some scholars. The results showed that the correlation between the model values and the experimental values was more than 0.95, which could accurately reflect the degree of F–T damage of concrete. In addition, a prediction model of photocatalytic NO reduction by nano-TiO2 concrete based on microscopic damage factor was established. It provides a theoretical basis for the application of nano-TiO2 concrete in the field of gas pollutant treatment. Full article
(This article belongs to the Section Building Materials, and Repair & Renovation)
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<p>Forming and curing process of nano-TiO<sub>2</sub> concrete specimens.</p>
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<p>Rapid F–T test: (<b>a</b>) F–T testing machine, (<b>b</b>) concrete dynamic modulus of elasticity tester, and (<b>c</b>) F–T cycle regime.</p>
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<p>(<b>a</b>) NOx photocatalytic degradation experiment system. (<b>b</b>) Schematic diagram of gas flow in the reactor.</p>
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<p>Variation of NOx and NO concentration in photocatalytic test.</p>
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<p>Flow chart of nitrate elution test.</p>
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<p>(<b>a</b>) NMR specimen preparation process. (<b>b</b>) MesoMR23-060H-I NMR tester.</p>
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<p>The mass loss rate of nano-TiO<sub>2</sub> concrete during F–T cycles.</p>
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<p>Mechanism of the effect of nano-TiO<sub>2</sub> admixture on concrete mass loss during F–T cycles.</p>
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<p>RDEM change of nano-TiO<sub>2</sub> concrete in F–T cycles.</p>
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<p>NO removal from nano-TiO<sub>2</sub> concrete for various numbers of F–T cycles.</p>
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<p>NOx removal rate of nano-TiO<sub>2</sub> concrete for various numbers of F–T cycles.</p>
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<p>Nitrogen content in nano-TiO<sub>2</sub> concrete eluent in a freeze–thaw environment.</p>
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<p>Porosity of nano-TiO<sub>2</sub> concrete at various numbers of F–T cycles.</p>
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<p>Volume fraction of different pore sizes of concrete before F–T cycles.</p>
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<p>Pore volume fraction of nano-TiO<sub>2</sub> concrete at various numbers of F–T cycles. (<b>a</b>) NC. (<b>b</b>) NT-2. (<b>c</b>) NT-4. (<b>d</b>) NT-6.</p>
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<p>Pore volume fraction of nano-TiO<sub>2</sub> concrete at various numbers of F–T cycles. (<b>a</b>) NC. (<b>b</b>) NT-2. (<b>c</b>) NT-4. (<b>d</b>) NT-6.</p>
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<p>Growth rate of volume fraction of pores larger than 100 nm after 200 F–T cycles of concrete.</p>
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<p>Evolution law of fractal dimension of pores above 100 nm during the F–T cycle of concrete.</p>
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<p>Evolution law of the macroscopic F–T damage factor of concrete during the F–T process.</p>
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<p>Evolution law of microscopic freeze–thaw damage factor of concrete during freeze–thaw process.</p>
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<p>Comparison of modeled and experimental values of concrete damage at different numbers of F–T cycles.</p>
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<p>Comparison between the modified and experimental values of concrete damage models for different numbers of F–T cycles.</p>
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<p>Comparison of F–T damage test values of some scholars with the damage prediction model values in this paper. (<b>a</b>) R0, R50, and R100. (<b>b</b>) R50P, R50T, R100P, and R100.</p>
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<p>Correlation analysis of NO removal from nano-TiO<sub>2</sub> concrete with dosage and pore structure damage influence coefficient. (<b>a</b>) NT-2. (<b>b</b>) NT-4. (<b>c</b>) NT-6.</p>
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<p>Comparison between experimental and model-predicted values of NO removal of nano-TiO<sub>2</sub> concrete.</p>
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14 pages, 3297 KiB  
Article
Quantitative Relationship Between Strength and Porosity of Nano-Silica-Modified Mortar Based on Fractal Theory
by Shaowei Hu, Yi Liao, Yaoqun Xu and Juan Wang
Fractal Fract. 2024, 8(12), 694; https://doi.org/10.3390/fractalfract8120694 - 26 Nov 2024
Viewed by 341
Abstract
Nano-silica (NS) is an ideal modifier for mortar materials, and exploring the evolution of the fractal dimension of the pore structure in NS-modified mortar is crucial for elucidating the mechanism by which NS enhances mortar strength. In this study, NS reinforced mortar was [...] Read more.
Nano-silica (NS) is an ideal modifier for mortar materials, and exploring the evolution of the fractal dimension of the pore structure in NS-modified mortar is crucial for elucidating the mechanism by which NS enhances mortar strength. In this study, NS reinforced mortar was prepared using an NS sol solution, which inhibited the aggregation of NS particles. The relationship between the strength and pore structure of NS-modified mortar was quantitatively analyzed based on fractal dimension theory and gray correlation degree. The experimental system evaluated the mortar strength, pore structure distribution, and micro-morphology. Based on this evaluation, the fractal dimension of the mortar pore volume was calculated in detail. Subsequently, models for mortar strength and NS content were further established using grey analysis. The results indicate that NS significantly enhances the strength of mortar while also increasing its porosity due to reduced fluidity. NS can improve the compressive strength of mortar by up to 35%. The curve fitting of volume fractal dimension and box dimension is effective and can accurately reflect the complexity of the pore structure. The calculation of the grey correlation analysis model shows that the impact of varying silica content on the mechanical properties of mortar specimens is not linear; the distribution and quantity of bubbles are the main factors affecting the strength of the specimen. Full article
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<p>Appearance of NS: (<b>a</b>) NS sol; (<b>b</b>) SEM image of NS particles precipitated.</p>
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<p>Overview of pore structure test.</p>
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<p>Mortar fluidity.</p>
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<p>Development of mortar strength.</p>
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<p>Pore size distributions.</p>
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<p>Microstructure images of three mortar samples.</p>
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<p>Calculation of volume fractal dimension.</p>
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<p>Calculation of box dimension.</p>
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18 pages, 11099 KiB  
Article
The Influence of Sand Pore Structure on Air Migration During Air-Injected Desaturation Process
by Yumin Chen, Chengzhao Qin, Saeed Sarajpoor, Runze Chen, Yi Han and Zijun Wang
Buildings 2024, 14(12), 3730; https://doi.org/10.3390/buildings14123730 - 23 Nov 2024
Viewed by 432
Abstract
The air injection method serves as a liquefaction mitigation technique to improve the liquefaction resistance of the foundations by decreasing the degree of saturation. To investigate the desaturation effect of this technique in various soil strata of the foundation, thin plate model tests [...] Read more.
The air injection method serves as a liquefaction mitigation technique to improve the liquefaction resistance of the foundations by decreasing the degree of saturation. To investigate the desaturation effect of this technique in various soil strata of the foundation, thin plate model tests were conducted, considering the impacts of gradation and relative density, to visualize the air migration process and distribution. The findings reveal the following: (1) The air migration process, delineated by air injection parameters, comprises four distinct phases, with stages II and III notably influenced by the pore structure; (2) air migration is governed by the pore throat dimensions, particle arrangement, and connectivity within the pore structure, exhibiting two predominant patterns: channel flow, primarily driven by inertial forces, and chamber flow, predominantly influenced by viscous and capillary forces; (3) referring to the air injection port, the gas phase distribution within the sand samples is consistent in the horizontal direction but not in the vertical direction. The concentration area and uniformity of the gas phase distribution are controlled by the pore structure. These results suggest potential enhancements in the positioning of air injection ports within complex soil layers, as well as improvements in the construction process, both aimed at optimizing the desaturation effect. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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<p>Test Schematic.</p>
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<p>Fujian sand samples: (<b>a</b>) samples of different gradations; (<b>b</b>) grain size distribution curves.</p>
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<p>Experimental preparation flowchart.</p>
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<p>Image processing.</p>
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<p>Air migration process inside the sand samples. (<b>a</b>) The process of air injection; (<b>b</b>) changes in air pressure, drainage, and injection volume during the air injection process.</p>
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<p>The degree of desaturation after injecting gas into the sand samples. (<b>a</b>) Average optical density versus gas phase saturation under sand samples; (<b>b</b>) the variation trend of gas saturation in air-injected sand samples.</p>
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<p>Air migration morphology of sand samples.</p>
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<p>Procedure for quantifying air migration patterns.</p>
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<p>Vertical division results. (<b>a</b>) 1–2 mm coarse sand; (<b>b</b>) 0.5–1 mm medium sand; (<b>c</b>) 0.5–2 mm coarse-medium sand; (<b>d</b>) 0.25–0.5 mm fine sand; (<b>e</b>) 0.1–0.25 mm very fine sand; and (<b>f</b>) 0.1–1 mm medium-fine sand.</p>
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<p>Horizontal division results. (<b>a</b>) 1–2 mm coarse sand (<b>b</b>) 0.5–1 mm medium sand (<b>c</b>) 0.5–2 mm coarse-medium sand (<b>d</b>) 0.25–0.5 mm fine sand (<b>e</b>) 0.1–0.25 mm very fine sand (<b>f</b>) 0.1–1 mm medium-fine sand.</p>
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<p>Compare the proportion of desaturation degrees under different gradations. (<b>a</b>) Vertical zones (1.5–4.5–7.5–10.5–13.5 cm); (<b>b</b>) horizontal zones (4–12–20–28–36 cm). The positions of each region are reflected by the centroid abscissa or ordinate.</p>
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<p>Compare the proportion of desaturation degree under different relative densities (<b>a</b>) vertical zones (1.5–4.5–7.5–10.5–13.5 cm) and (<b>b</b>) horizontal zones (4–12–20–28–36 cm).</p>
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<p>Influence mechanism of gradation.</p>
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<p>The mechanism of the effect of relative density.</p>
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<p>Examples of pore structures affecting air migration.</p>
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24 pages, 5064 KiB  
Article
High-Precision Permeability Evaluation of Complex Carbonate Reservoirs in Marine Environments: Integration of Gaussian Distribution and Thomeer Model Using NMR Logging Data
by Hengyang Lv, Jianhong Guo, Baoxiang Gu, Yuhan Liu, Li Wang, Long Wang, Zuomin Zhu and Zhansong Zhang
J. Mar. Sci. Eng. 2024, 12(12), 2135; https://doi.org/10.3390/jmse12122135 - 22 Nov 2024
Viewed by 672
Abstract
Accurate evaluation of permeability parameters is critical for the exploration and development of oil and gas fields. Among the available techniques, permeability assessment based on nuclear magnetic resonance (NMR) logging data is one of the most widely used and precise methods. However, the [...] Read more.
Accurate evaluation of permeability parameters is critical for the exploration and development of oil and gas fields. Among the available techniques, permeability assessment based on nuclear magnetic resonance (NMR) logging data is one of the most widely used and precise methods. However, the rapid biochemical variations in marine environments give rise to complex pore structures and strong reservoir heterogeneity, which diminish the effectiveness of traditional SDR and Timur–Coates models. To address these challenges in complex carbonate reservoirs, this study proposes a high-precision permeability evaluation method that integrates the Gaussian distribution model with the Thomeer model for more accurate permeability calculations using NMR logging data. Multimodal Gaussian distributions more accurately capture the size and distribution of multiscale pores. In this study, we innovatively employ the Gaussian distribution function to construct NMR-derived pseudo-pore size distribution curves. Subsequently, Thomeer model parameters are derived from Gaussian distribution parameters, enabling precise permeability calculation. The application of this method to the marine dolomite intervals of the Asmari Formation, Section A, within Oilfield A in southeastern Iraq, demonstrates its superior performance under both bimodal and unimodal pore size distributions. Compared to traditional models, this approach significantly reduces errors, providing crucial support for the accurate evaluation of complex reservoirs and the development of hydrocarbon resources. Full article
(This article belongs to the Special Issue Petroleum and Gas Hydrate Exploration and Marine Geology)
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<p>The acquisition of nuclear magnetic resonance (NMR) logging data and mercury injection capillary pressure (MICP) experiments. (<b>a</b>) Schematic diagram of NMR logging; (<b>b</b>) NMR logging T2 distribution spectrum; (<b>c</b>) ① schematic diagram of coring sample, ② schematic diagram of plunger sample acquisition; (<b>d</b>) mercury injection instrument; (<b>e</b>) MICP experimental results schematic.</p>
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<p>Comparison of pore size distribution curves and NMR logging spectra. (<b>a</b>) MICP pore size distribution curve; (<b>b</b>) NMR porosity distribution spectrum.</p>
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<p>Fitting results and accuracy. (<b>a</b>–<b>d</b>) the pore size distribution processing results for core sample ①; (<b>e</b>–<b>h</b>) the processing results of the NMR distribution spectrum for core sample ①; (<b>i</b>–<b>l</b>) the pore size distribution processing results for core sample ②; (<b>m</b>–<b>p</b>) the processing results of the NMR distribution spectrum for core sample ②.</p>
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<p>An analysis of the weight and mean. (<b>a</b>) comparison of MICP Gaussian weights and NMR Gaussian weights; (<b>b</b>) relationship between MICP Gaussian Mean and NMR Gaussian Mean.</p>
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<p>An analysis of StdDev for large and small pores. (<b>a</b>) Fitting results of <math display="inline"><semantics> <mrow> <mi>log</mi> <msub> <mi>σ</mi> <mrow> <msub> <mn>1</mn> <mrow> <mrow> <mo>(</mo> <mrow> <mi>N</mi> <mi>M</mi> <mi>R</mi> </mrow> <mo>)</mo> </mrow> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>log</mi> <msub> <mi>σ</mi> <mn>1</mn> </msub> </mrow> </semantics></math> for large pores; (<b>b</b>) fitting results of <math display="inline"><semantics> <mrow> <mi>log</mi> <msub> <mi>σ</mi> <mrow> <msub> <mn>2</mn> <mrow> <mrow> <mo>(</mo> <mrow> <mi>N</mi> <mi>M</mi> <mi>R</mi> </mrow> <mo>)</mo> </mrow> </mrow> </msub> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>log</mi> <msub> <mi>σ</mi> <mn>2</mn> </msub> </mrow> </semantics></math> for small pores.</p>
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<p>Thomeer hyperbolic curve.</p>
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<p>The effect of Thomeer parameters on the pore size distribution curve. (<b>a</b>) Characterization of displacement pressure (<math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mi>d</mi> </msub> </mrow> </semantics></math>) on pore throat size; (<b>b</b>) characterization of pore throat characteristics by geometric factors (<math display="inline"><semantics> <mi>G</mi> </semantics></math>); (<b>c</b>) invisible characterization of rock samples by maximum mercury injection volume (<math display="inline"><semantics> <mrow> <msub> <mi>B</mi> <mrow> <mi>v</mi> <mo>∞</mo> </mrow> </msub> </mrow> </semantics></math>).</p>
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<p>Permeability calculation. (<b>a</b>) Fitting results of <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mi>d</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mi>k</mi> </semantics></math>; (<b>b</b>) comparison of predicted <math display="inline"><semantics> <mi>k</mi> </semantics></math> and actual <math display="inline"><semantics> <mi>k</mi> </semantics></math>.</p>
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<p>A flowchart of the permeability logging evaluation process.</p>
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<p>Gaussian parameters and permeability calculation results. (<b>a</b>) Fitting Gaussian parameter results; (<b>b</b>) permeability results based on Gaussian parameters vs. core experiment results; (<b>c</b>) permeability results from the Timur–Coates model vs. core experiment results; (<b>d</b>) the permeability results from the SDR model vs. core experiment results; (<b>e</b>) the permeability results from the pore–permeability relationship vs. core experiment results.</p>
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<p>A comparison of four permeability calculation models. (<b>a</b>) Permeability results based on Gaussian parameters versus actual values; (<b>b</b>) Permeability results from pore permeability relationships versus actual values; (<b>c</b>) Permeability results from the Timur-Coates model versus actual values; (<b>d</b>) Permeability results from the SDR model versus actual values.</p>
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15 pages, 5198 KiB  
Article
Study on the Structural Changes of Boneless Chicken Claw Collagen and Its Effect on Water Retention Performance
by Zheng Tang, Yiguo He, Jing Zhang, Zhifeng Zhao, Yiming Nie and Xingxiu Zhao
Foods 2024, 13(22), 3682; https://doi.org/10.3390/foods13223682 - 19 Nov 2024
Viewed by 538
Abstract
The purpose of this study was to explore the water retention mechanism of chicken claws by detecting the structural changes in collagen in boneless chicken claws under different expansion rates. Firstly, boneless chicken claw collagen with different expansion rates (0%, 10%, 20%, 30%, [...] Read more.
The purpose of this study was to explore the water retention mechanism of chicken claws by detecting the structural changes in collagen in boneless chicken claws under different expansion rates. Firstly, boneless chicken claw collagen with different expansion rates (0%, 10%, 20%, 30%, 40%, 50%) was extracted by the acid–enzyme complex method, and the changes in collagen were determined by scanning electron microscopy (SEM), ultraviolet spectroscopy (UV), Fourier transform infrared spectroscopy (FTIR), circular dichroism (CD), low-field nuclear magnetic resonance LF-NMR) and surface hydrophobicity to explore the mechanism that leads to changes in the water retention performance. The results of scanning electron microscopy showed that with the increase in the expansion rate, collagen molecules showed curling, shrinking, breaking and crosslinking, forming a loose and irregular pore-like denatured collagen structure. UV analysis showed that the maximum absorption wavelength of chicken claw collagen was blue shifted under different expansion rates, and the maximum absorption peak intensity increased first and then decreased with the increase in expansion rate. The FTIR results showed that collagen had obvious characteristic absorption peaks in the amide A, B, I, II and III regions under different expansion rates, and that the intensity and position of the characteristic absorption peaks changed with the expansion rate. The results of the CD analysis showed that collagen at different expansion rates had obvious positive absorption peaks at 222 nm, and that the position of negative absorption peaks was red shifted with the increase in expansion rate. This shows that the expansion treatment makes the collagen of chicken claw partially denatured, and that the triple helix structure becomes relaxed or unwound, which provides more space for the combination of water molecules, thus enhancing the water absorption capacity of boneless chicken claw. The results of the surface hydrophobicity test showed that the surface hydrophobicity of boneless chicken claw collagen increased with the increase in expansion rate and reached the maximum at a 30% expansion rate, and then decreased with the further increase in the expansion rate. The results of LF-NMR showed that the water content of boneless chicken claws increased significantly after the expansion treatment, and that the water retention performance of chicken claws was further enhanced with the increase in the expansion rate. In this study, boneless chicken claws were used as raw materials, and the expansion process of boneless chicken claws was optimized by acid combined with a water-retaining agent, which improved the expansion rate of boneless chicken claws and the quality of boneless chicken claws. The effects of the swelling degree on the collagen structure, water absorption and water retention properties of boneless chicken claws were revealed by structural characterization. These findings explain the changes in the water retention of boneless chicken claws after expansion. By optimizing the expansion treatment process, the water retention performance and market added value of chicken feet products can be significantly improved, which is of great economic significance. Full article
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<p>Collagen extraction process.</p>
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<p>Scanning electron microscope images of chicken claw collagen under different expansion rates. Note: (<b>A1</b>–<b>F1</b>): Boneless chicken claw collagen (×1000); (<b>A2</b>–<b>F2</b>): boneless chicken claw collagen (×500); among them, (<b>A1</b>,<b>A2</b>): 0%; (<b>B1</b>,<b>B2</b>): 10%; (<b>C1</b>,<b>C2</b>): 20%; (<b>D1</b>,<b>D2</b>): 30%; (<b>E1</b>,<b>E2</b>): 40%; (<b>F1</b>,<b>F2</b>): 50%.</p>
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<p>Scanning electron microscope images of chicken claw collagen under different expansion rates. Note: (<b>A1</b>–<b>F1</b>): Boneless chicken claw collagen (×1000); (<b>A2</b>–<b>F2</b>): boneless chicken claw collagen (×500); among them, (<b>A1</b>,<b>A2</b>): 0%; (<b>B1</b>,<b>B2</b>): 10%; (<b>C1</b>,<b>C2</b>): 20%; (<b>D1</b>,<b>D2</b>): 30%; (<b>E1</b>,<b>E2</b>): 40%; (<b>F1</b>,<b>F2</b>): 50%.</p>
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<p>UV–visible spectra of collagen under different expansion rates.</p>
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<p>Infrared spectra of collagen under different expansion rates.</p>
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<p>CD spectra of collagen under different expansion rates.</p>
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<p>Surface hydrophobicity of collagen under different expansion rates. Note: ** means extremely significant (<span class="html-italic">p</span> &lt; 0.01), ns means not significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Moisture migration of chicken claws under different expansion rates.</p>
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15 pages, 6112 KiB  
Article
Self-Exfoliated Guanidinium Covalent Organic Nanosheets as High-Capacity Curcumin Carrier
by Archita Sharma, Dhavan Sharma, Hengyu Lin, Hongcai (Joe) Zhou and Feng Zhao
Biomimetics 2024, 9(11), 709; https://doi.org/10.3390/biomimetics9110709 - 19 Nov 2024
Viewed by 523
Abstract
Drug administration is commonly used to treat chronic wounds but faces challenges such as poor bioavailability, instability, and uncontrollable release. Existing drug delivery platforms are limited by chemical instability, poor functionality, complex synthesis, and toxic by-products. Presently, research efforts are focused on developing [...] Read more.
Drug administration is commonly used to treat chronic wounds but faces challenges such as poor bioavailability, instability, and uncontrollable release. Existing drug delivery platforms are limited by chemical instability, poor functionality, complex synthesis, and toxic by-products. Presently, research efforts are focused on developing novel drug carriers to enhance drug efficacy. Guanidinium Covalent Organic Nanosheets (gCONs) offer promising alternatives due to their high porosity, surface area, loading capacity, and ability to provide controlled, sustained, and target-specific drug delivery. Herein, we successfully synthesized self-exfoliated gCONs using a Schiff base condensation reaction and embedded curcumin (CUR), a polyphenolic pleiotropic drug with antioxidant and anti-inflammatory properties, via the wet impregnation method. The BET porosimeter exhibited the filling of gCON pores with CUR. Morphological investigations revealed the formation of sheet-like structures in gCON. Culturing human dermal fibroblasts (hDFs) on gCON demonstrated cytocompatibility even at a concentration as high as 1000 µg/mL. Drug release studies demonstrated a controlled and sustained release of CUR over an extended period of 5 days, facilitated by the high loading capacity of gCON. Furthermore, the inherent antioxidant and anti-inflammatory properties of CUR were preserved after loading into the gCON, underscoring the potential of CUR-loaded gCON formulation for effective therapeutic applications. Conclusively, this study provides fundamental information relevant to the performance of gCONs as a drug delivery system and the synergistic effect of CUR and CONs addressing issues like drug bioavailability and instability. Full article
(This article belongs to the Special Issue Biomimetic Drug Delivery Systems 2024)
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Graphical abstract
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<p>(<b>A</b>–<b>G</b>): <b>Material characterization of pristine gCON:</b> (<b>A</b>) FTIR Spectra depicting characteristic functional groups on the surface of gCON, confirming its chemical composition and successful synthesis. (<b>B</b>) N<sub>2</sub> adsorption isotherm analyzed via BET determining gCON’s porosity. (<b>C</b>) PXRD pattern displays the crystallinity of the gCON. (<b>D</b>,<b>E</b>) FE-SEM (scale bar: 100 μm) and TEM (scale bar: 100 nm) exhibit gCON’s marginally rippled sheet-like surface topography. (<b>F</b>) EDS for compositional analysis, revealing the elemental distribution of gCON. (<b>G</b>) A 3D AFM image depicting the multi-layer stacked morphology of self-exfoliated gCON layers.</p>
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<p><b>Cytocompatibility testing of pristine gCON:</b> Live/Dead assay of hDFs exposed to 1000 µg/mL of pristine gCON for 48 h and 72 h. Fewer dead cells (red fluorescence) and increased cell density (green fluorescence) at 72 h indicating low toxicity and biocompatibility even at higher concentrations. DMSO-treated cells serve as positive control. Scale bar: 200 μm.</p>
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<p><b>FTIR spectra of pristine CUR, pristine gCON, and CUR@gCON formulations.</b> The spectrum confirms the successful loading of CUR into gCON. The distinct peaks for each component and CUR@gCON formulations indicate the interactions between CUR and gCON, verifying effective loading.</p>
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<p>(<b>A</b>–<b>F</b>): <b>Material characterization pristine CUR and CUR@gCON formulations:</b> (<b>A</b>) N<sub>2</sub> adsorption isotherm via BET showing almost complete filling of gCON pores after CUR loading, indicating successful incorporation; (<b>B</b>) Particle size analysis indicating increased hydrodynamic diameter incorporation of CUR into the gCON; (<b>C</b>) Zeta potential measurements reveal the near-neutral surface charge of CUR@gCON due to charge neutralization effects; (<b>D</b>) PXRD spectra illustrating changes in the crystalline structures upon CUR loading onto gCON; (<b>E</b>) FE-SEM image of pristine CUR shows spherical morphology with an average diameter of 17 μm. Scale bar: 1 μm, and (<b>F</b>) FE-SEM image of CUR@gCON (80%) displays altered gCON topography due to pore saturation and CUR loading, highlighting differences in structure, post-loading. Scale bar: 10 μm.</p>
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<p>(<b>A</b>–<b>C</b>): <b>Bioactivity testing of pristine gCON, pristine CUR, and CUR@gCON formulation:</b> (<b>A</b>) Release rate profiles of CUR from CUR@gCON (80%) at two different pH levels, 7.2 and 5.0, illustrating the pH-dependent release behavior of CUR in different biological environments; (<b>B</b>) Antioxidant activity assessment via DPPH assay comparing the relative scavenging effects of each formulation in neutralizing free radicals; and (<b>C</b>) Anti-inflammatory activity evaluation via the Griess reagent reaction, measuring nitric oxide production as a marker of inflammatory response. CUR@gCON exhibits potent anti-inflammatory properties compared to pristine gCON (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>(<b>A</b>,<b>B</b>): <b>Diagrammatic representation of the synthesis and incorporation method of CUR onto gCON:</b> (<b>A</b>) Step-by-step synthesis of gCON via the Schiff base condensation method. This schematic outlines the key stages of the reaction process, including reactants, intermediates, and final product, illustrating how gCON is formed through the condensation of amine and aldehyde precursors. (<b>B</b>) Incorporation of CUR into gCON via the wet impregnation method. This schematic illustrates the process by which CUR is introduced into the gCON, detailing the steps involved in ensuring effective loading and distribution of CUR within the gCON structure.</p>
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31 pages, 7065 KiB  
Review
NMR Relaxation to Probe Zeolites: Mobility of Adsorbed Molecules, Surface Acidity, Pore Size Distribution and Connectivity
by Marina G. Shelyapina
Molecules 2024, 29(22), 5432; https://doi.org/10.3390/molecules29225432 - 18 Nov 2024
Viewed by 707
Abstract
Unique structural and chemical properties, such as ion exchange, developed inner surface, etc., as well as the wide possibilities and flexibility of regulating these properties, cause a keen interest in zeolites. They are widely used in industry as molecular sieves, ion exchangers and [...] Read more.
Unique structural and chemical properties, such as ion exchange, developed inner surface, etc., as well as the wide possibilities and flexibility of regulating these properties, cause a keen interest in zeolites. They are widely used in industry as molecular sieves, ion exchangers and catalysts. Current trends in the development of zeolite-based catalysts include the adaptation of their cationic composition, acidity and porosity for a specific catalytic process. Recent studies have shown that mesoporosity is beneficial to the rational design of catalysts with controlled product selectivity and an improved catalyst lifetime due to its efficient mass-transport properties. Nuclear magnetic resonance (NMR) has proven to be a reliable method for studying zeolites. Solid-state NMR spectroscopy allows for the quantification of both Lewis and Brønsted acidity in zeolite catalysts and, nowadays, 27Al and 29Si magic angle spinning NMR spectroscopy has become firmly established in the set of approved methods for characterizing zeolites. The use of probe molecules opens up the possibility for the indirect measurement of the characteristics of acid sites. NMR relaxation is less common, although it is especially informative and enlightening for studying the mobility of guest molecules in the porous matrix. Moreover, the NMR relaxation of guest molecules and NMR cryoporometry can quantify pore size distribution on a broader scale (compared to traditional methods), which is especially important for systems with complex pore organization. Over the last few years, there has been a growing interest in the use of 2D NMR relaxation techniques to probe porous catalysts, such as 2D T1T2 correlation to study the acidity of the surface of catalysts and 2D T2T2 exchange to study pore connectivity. This contribution provides a comprehensive review of various NMR relaxation techniques for studying porous media and recent results of their applications in probing micro- and mesoporous zeolites, mainly focused on the mobility of adsorbed molecules, the acidity of the zeolite surface and the pore size distribution and connectivity of zeolites with hierarchical porosity. Full article
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<p>Selected zeolite frameworks and information about their pore structure: channel dimensionality; the maximum diameter of a sphere that can be included (<span class="html-italic">D</span><sub>incl</sub>) and that diffuses in a specific direction <span class="html-italic">x</span> (<span class="html-italic">D<sub>x</sub></span>); the channel size and the <span class="html-italic">N</span>-membered ring it is formed by (in parenthesis).</p>
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<p>Basic NMR sequences for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> <mi mathvariant="sans-serif">ρ</mi> </mrow> </msub> </mrow> </semantics></math> measurements: (<b>a</b>) inversion-recovery; (<b>b</b>) saturation-recovery; (<b>c</b>) spin-locking; (<b>d</b>) field cycling.</p>
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<p>Basic NMR sequences for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> measurements: (<b>a</b>) Hahn spin echo; (<b>b</b>) CPMG pulse train.</p>
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<p>Basic NMR sequences for diffusion measurements: (<b>a</b>) PGSE experiment; (<b>b</b>) PFG STE experiment.</p>
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<p>Pulse sequences used for the <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> correlation (<b>a</b>) and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> exchange (<b>b</b>) experiments.</p>
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<p>Water self-diffusion coefficient versus inverse temperature in sodium- and copper-exchanged mordenite (the <sup>1</sup>H SFG STE experiment). The open and solid symbols correspond to the diffusion coefficient obtained applying the 1D and 3D diffusion model, respectively. Reproduced with permission from Krylova, E.A. et al. <span class="html-italic">Micropor. Mesopor. Mat.</span>; Elsevier Inc., 2018 [<a href="#B68-molecules-29-05432" class="html-bibr">68</a>].</p>
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<p>Restricted diffusion model: (<b>a</b>) motion of particles in a restricted area; (<b>b</b>) the mean square displacement of the particle in a restricted area (above) and the apparent diffusion coefficient (below) depending on time. Adapted with permission from Shelyapina M.G. et al. <span class="html-italic">Int. J. Hydrogen Energy</span>; Hydrogen Energy Publications, LLC. Published by Elsevier Ltd., 2015 [<a href="#B124-molecules-29-05432" class="html-bibr">124</a>].</p>
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<p>Effective diffusivities of water at 298 K (<b>a</b>) and of Li<sup>+</sup> at 373 K (<b>b</b>) in hydrated zeolite Li-LSX. The straight lines show the fit of Equation (21) to the experimental data in the short- and long-time ranges. Reproduced with permission from Beckert, S. et al. <span class="html-italic">J. Phys. Chem. C</span>; American Chemical Society, 2013 [<a href="#B126-molecules-29-05432" class="html-bibr">126</a>].</p>
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<p><sup>1</sup>H spin–lattice relaxation rate in laboratory frame (<b>a</b>) and rotating frame (<b>b</b>) versus inverse temperature in pillared mordenite (triangles) and pillared ZSM-5 (circles). Reproduced with permission from Shelyapina, M.G. et al. <span class="html-italic">Int. J. Mol. Sci.</span>; published by MDPI, Basel, Switzerland. Creative Common CC BY license, 2023 [<a href="#B45-molecules-29-05432" class="html-bibr">45</a>].</p>
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<p>(<b>a</b>) <sup>1</sup>H <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> correlation plots for pyridine in HZSM-5 with varying SiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> ratios. The diagonal line indicates the parity ratio <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>/</mo> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>; bulk pyridine data are also shown; (<b>b</b>) <math display="inline"><semantics> <mrow> <mo>−</mo> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>1</mn> </mrow> </msub> <mo>/</mo> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> plotted versus enthalpy of pyridine adsorption; the red line shows a linear fit. SiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub> values are indicated next to each correlation peak or point. Reproduced with permission from Robinson, N. et al. <span class="html-italic">Phys. Chem. Chem. Phys.</span>; published by the Royal Society of Chemistry. Creative Common CC BY license, 2021 [<a href="#B71-molecules-29-05432" class="html-bibr">71</a>].</p>
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<p>Scratch to illustrate relationship between the freezing–melting hysteresis form and model pore geometries in the large pore limit (&gt;10 nm); dashed and solid lines correspond to freezing and melting, respectively. Reproduced with permission from Petrov, O.V., Furó, I. <span class="html-italic">Prog. Nucl. Magn. Reson. Spectrosc.</span>; Elsevier B.V. 2008, [<a href="#B156-molecules-29-05432" class="html-bibr">156</a>].</p>
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<p>Pore size distribution for a cement paste determined by NMR cryoporometry (solid symbols) and NMR relaxometry (open symbols). Reproduced with permission from Jehng, J.Y. et al. <span class="html-italic">Magn. Reson. Imaging</span>; Elsevier Science Inc., 1996 [<a href="#B159-molecules-29-05432" class="html-bibr">159</a>].</p>
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<p>(<b>a</b>) A schematic <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> map showing diagonal and off-diagonal peaks at a certain exchange time <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>e</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) calculated <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math>–<math display="inline"><semantics> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> maps for slow (<b>left</b>), intermediate (<b>middle</b>) and fast (<b>right</b>) exchange rates <math display="inline"><semantics> <mrow> <mi>k</mi> </mrow> </semantics></math> and short (<b>bottom</b>), intermediate (<b>middle</b>) and long exchange time <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>τ</mi> </mrow> <mrow> <mi>e</mi> </mrow> </msub> </mrow> </semantics></math>. Reproduced with permission from Monteilhet, L. et al. <span class="html-italic">Phys. Rev. E</span>; The American Physical Society, 2006 [<a href="#B161-molecules-29-05432" class="html-bibr">161</a>].</p>
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<p>Relaxation exchange experiments with squalane (<b>a</b>,<b>c</b>) and 2-propanol (<b>b</b>,<b>d</b>) adsorbed by UZY zeolites with low (<b>a</b>,<b>c</b>) and high (<b>b</b>,<b>d</b>) mesoporosity. The off-diagonal amplitudes indicate the diffusive coupling between micro- and mesopores, as well as between meso- and macropores. (<b>e</b>,<b>f</b>) show squalane and 2-propanol molecules, respectively. Adopted with permission from Fleury, M. et al. <span class="html-italic">Micropor. Mesopor. Mat.</span>; Elsevier Inc., 2023 [<a href="#B74-molecules-29-05432" class="html-bibr">74</a>].</p>
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14 pages, 2827 KiB  
Article
Adsorption Properties of Fishbone and Fishbone-Derived Biochar for Cadmium in Aqueous Solution
by Nan Pei, Wenwen Luo, Qingqing Huang and Yuebing Sun
Agronomy 2024, 14(11), 2717; https://doi.org/10.3390/agronomy14112717 - 18 Nov 2024
Viewed by 360
Abstract
Cadmium (Cd) contamination in aquatic ecosystems is a serious global environmental issue. Biochar derived from agricultural wastes has recently attracted remarkable attention as it is used as an absorbent in combating heavy metal contamination of water bodies. In the present study, the absorption [...] Read more.
Cadmium (Cd) contamination in aquatic ecosystems is a serious global environmental issue. Biochar derived from agricultural wastes has recently attracted remarkable attention as it is used as an absorbent in combating heavy metal contamination of water bodies. In the present study, the absorption efficacy of fish bone (FBM) and fishbone-derived biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C (referred to as B200, B400, B600, and B800, respectively) for the Cd ion (Cd2+) in aqueous solution was investigated. The results showed that high-temperature pyrolysis could optimize the pore structure and specific surface area of FBM, and Cd2+ successfully adsorbed onto FBM and fishbone-derived biochar. High-temperature pyrolysis significantly increased the FBM adsorption capacity for Cd2+ by 49.5–135.1%, with the optimal pyrolysis temperature being 600 °C. Furthermore, the kinetic data of FBM and fishbone-derived biochar for Cd2+ were in better alignment with the pseudo-second-order model, their adsorption isotherms were better in accordance with the Langmuir models, and the thermodynamic analysis showed that the adsorption process was monolayer and favorable adsorption. Moreover, the potential adsorption mechanisms of Cd2+ on FBM and fishbone-derived biochar might be related to pore filling, ion exchange, complexation with oxygen functional groups, and precipitation with the minerals on the biochar surface. Fishbone-derived biochar has significant potential for wastewater treatment and agricultural waste applications. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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Figure 1

Figure 1
<p>The DTA/TGA analysis of fish bone powder at different heating rates (<b>a</b>); FTIR spectra of fishbone and fishbone biochar (<b>b</b>); and Cd-absorbed biochar (<b>c</b>). FBM represents fishbone; B<sub>200</sub>, B<sub>400</sub>, B<sub>600</sub>, and B<sub>800</sub> represent fishbone biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C, respectively; B<sub>600</sub>-Cd represents Cd-absorbed biochar prepared at 600 °C.</p>
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<p>The N<sub>2</sub> adsorption–desorption isotherms (<b>a</b>) and pore size distribution of fishbone and fishbone biochar (<b>b</b>). FBM represents fishbone; B<sub>200</sub>, B<sub>400</sub>, B<sub>600</sub>, and B<sub>800</sub> represent fishbone biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C, respectively.</p>
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<p>Kinetics and isotherm models describing the Cd<sup>2+</sup> adsorption: (<b>a</b>) Fitting results of the pseudo-first-order and pseudo-second-order kinetics model fitting curves for Cd<sup>2+</sup> adsorption; (<b>b</b>) Fitting results of the Langmuir and Freundlich isotherm models for Cd<sup>2+</sup> adsorption. FBM represents fishbone; B<sub>200</sub>, B<sub>400</sub>, B<sub>600</sub>, and B<sub>800</sub> represent fishbone biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C, respectively.</p>
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<p>The adsorption capacity of Cd<sup>2+</sup> by fishbone-derived biochar under different initial pH values. FBM represents fishbone; B<sub>200</sub>, B<sub>400</sub>, B<sub>600</sub>, and B<sub>800</sub> represent fishbone biochar prepared at 200 °C, 400 °C, 600 °C, and 800 °C, respectively.</p>
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<p>SEM–EDS spectra of (<b>a</b>) FBM-Cd, (<b>b</b>) B<sub>200</sub>-Cd, (<b>c</b>) B<sub>400</sub>-Cd, (<b>d</b>) B<sub>600</sub>-Cd, and (<b>e</b>) B<sub>800</sub>-Cd. FBM-Cd represents Cd-absorbed fishbone; B<sub>200</sub>-Cd, B<sub>400</sub>-Cd, B<sub>600</sub>-Cd, and B<sub>800</sub>-Cd represent Cd-absorbed fishbone biochar that was prepared at 200 °C, 400 °C, 600 °C, and 800 °C, respectively.</p>
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