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17 pages, 2564 KiB  
Article
Comparative Analysis of Amorphous and Biodegradable Copolymers: A Molecular Dynamics Study Using a Multi-Technique Approach
by Alovidin Nazirov, Jacek Klinowski and John Nobleman
Molecules 2025, 30(5), 1175; https://doi.org/10.3390/molecules30051175 (registering DOI) - 6 Mar 2025
Abstract
We investigate the molecular dynamics of glycolide/lactide/caprolactone (Gly/Lac/Cap) copolymers using differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), 1H second-moment, 1H spin-lattice relaxation time (T1) analysis, and 13C solid-state NMR over a temperature range of 100–413 K. [...] Read more.
We investigate the molecular dynamics of glycolide/lactide/caprolactone (Gly/Lac/Cap) copolymers using differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), 1H second-moment, 1H spin-lattice relaxation time (T1) analysis, and 13C solid-state NMR over a temperature range of 100–413 K. Activation energies and correlation times of the biopolymer chains were determined. At low temperatures, relaxation is governed by the anisotropic threefold reorientation of methyl (-CH3) groups in lactide. A notable change in T1 at ~270 K and 294 K suggests a transition in amorphous phase mobility due to translational diffusion, while a second relaxation minimum (222–312 K) is linked to CH2 group dynamics influenced by caprolactone. The activation energy increases from 5.9 kJ/mol (methyl motion) to 22–33 kJ/mol (segmental motion) as the caprolactone content rises, enhancing the molecular mobility. Conversely, lactide restricts motion by limiting rotational freedom, thereby slowing global dynamics. DSC confirms that increasing ε-caprolactone lowers the glass transition temperature, whereas higher glycolide and lactide content raises it. The onset temperature of main-chain molecular motion varies with the composition, with greater ε-caprolactone content enhancing flexibility. These findings highlight the role of composition in tuning relaxation behavior and molecular mobility in copolymers. Full article
Show Figures

Figure 1

Figure 1
<p>DSC thermograms of copolymers 0.5Gly/0.2Lac/0.3Cap and 0.5Gly/0.4Lac/0.1Cap, where heating (1⟶) and cooling (⟵2) are indicated. The dashed vertical lines represent a phase transition temperature (T<sub>g</sub>).</p>
Full article ">Figure 2
<p>Solution-state <sup>13</sup>C NMR spectra (75 MHz) of copolymers 0.5Gly/0.2Lac/0.3Cap and 0.5Gly/0.4Lac/0.1Cap recorded at 313 K. Letters (A–G) indicate the assignment of molecular groups. The samples were dissolved in CDCl<sub>3</sub> (chloroform-d, 77.2 ppm, triplet due to deuterium coupling), with TMS (0 ppm) as the internal reference.</p>
Full article ">Figure 3
<p>Derivatives of <sup>1</sup>H NMR absorption spectra of (<b>a</b>) 0.5Gly/0.2Lac/0.3Cap and (<b>b</b>) 0.5Gly/0.4Lac/0.1Cap at different temperatures. The proton derivative spectra at 273 K are highly sensitive compared to the broad DSC lines (c.f. <a href="#molecules-30-01175-f001" class="html-fig">Figure 1</a>) for both polymers, indicating the early onset of chain molecular dynamics motion in preparation for the phase transition.</p>
Full article ">Figure 4
<p>Second moments of the <sup>1</sup>H NMR lines of 0.5Gly/0.2Lac/0.3Cap and 0.5Gly/0.4Lac/0.1Cap versus temperature. The glass phase transition temperatures, T<sub>g</sub> indicated by the vertical lines (according to DSC, c.f. <a href="#molecules-30-01175-f001" class="html-fig">Figure 1</a>).</p>
Full article ">Figure 5
<p>Arrhenius plots of <sup>1</sup>H spin-lattice relaxation times measurements at 200 MHz and 9 MHz for 0.5Gly/0.2Lac/0.3Cap and 0.5Gly/0.4Lac/0.1Cap. <sup>1</sup>H experimental data fitted using the BPP model as indicated by solid lines. The experiments conducted from the low to high temperatures and the glass phase transition T<sub>g</sub> indicated by the vertical dashed lines (according to DSC, c.f. <a href="#molecules-30-01175-f001" class="html-fig">Figure 1</a>).</p>
Full article ">Figure 6
<p>The resonance frequency of 75.56 MHz <sup>13</sup>C solid-state NMR of copolymers 0.5Gly/0.2Lac/0.3Cap and 0.5Gly/0.4Lac/0.1Cap at different temperatures. The molecular groups are indicated by letters corresponding to the structure of copolymer chains. Solid-state NMR technology is still under development compared to its solution-state counterpart. One of the key technical challenges is the difficulty of spinning amorphous materials at high speeds. Due to their unique behavioral properties, such as superfluid-like elasticity, these materials tend to lose centrifugal axis stability during rotation. The magnitude of <sup>13</sup>C hydrocarbon signals effectively increases with rising temperature, corresponding to an increase in intensity due to fast trans-gauche isomerization and translational diffusion motion.</p>
Full article ">Figure 7
<p>FTIR spectra of copolymers (<b>a</b>) 0.5Gly/0.2Lac/0.3Cap and (<b>b</b>) 0.5Gly/0.4Lac/0.1Cap at different temperatures. The band assignments correspond to hydroxyl end-groups (-OH), carbonyl (C=O), methyl (-CH<sub>3</sub>), methylene (-CH<sub>2</sub>-), and methide (-CH-) vibrational motions. The spectra clearly indicate differences in the vibrational motions of the modulated chains.</p>
Full article ">
19 pages, 3665 KiB  
Article
Harnessing Nitrous Oxide for Sustainable Methane Activation: A Computational Exploration of CNC-Ligated Iron Catalysts
by Bruce M. Prince
Methane 2025, 4(1), 6; https://doi.org/10.3390/methane4010006 - 5 Mar 2025
Abstract
This study employs DFT at the APFD/def2-TZVP level, with SMD solvation in THF, to investigate the catalytic activation of methane by [(κ3-CNC)Fe(N₂O)]2+ cation complexes. The catalytic mechanism encompasses three key steps: oxygen atom transfer (OAT), hydrogen atom abstraction (HAA), and [...] Read more.
This study employs DFT at the APFD/def2-TZVP level, with SMD solvation in THF, to investigate the catalytic activation of methane by [(κ3-CNC)Fe(N₂O)]2+ cation complexes. The catalytic mechanism encompasses three key steps: oxygen atom transfer (OAT), hydrogen atom abstraction (HAA), and oxygen radical rebound (ORR). The computational results identify OAT as the rate-determining step, with activation barriers of −10.2 kcal/mol and 5.0 kcal/mol for κ1-O- and κ1-N-bound intermediates in the gas and solvent phases, respectively. Methane activation proceeds via HAA, with energy barriers of 16.0–25.2 kcal/mol depending on the spin state and solvation, followed by ORR, which occurs efficiently with barriers as low as 6.4 kcal/mol. The triplet (S = 1) and quintet (S = 2) spin states exhibit critical roles in the catalytic pathway, with intersystem crossing facilitating optimal reactivity. Spin density analysis highlights the oxyl radical character of the FeIV=O intermediate as being essential for activating methane’s strong C–H bond. These findings underscore the catalytic potential of CNC-ligated iron complexes for methane functionalization and demonstrate their dual environmental benefits by utilizing methane and reducing nitrous oxide, a potent greenhouse gas. Full article
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Figure 1

Figure 1
<p>Optimized geometries of [(κ<sup>3</sup>-CNC)Fe<sup>II</sup>]<sup>2+</sup> cation complexes in singlet (S = 0), triplet (S = 1), and quintet (S = 2) spin states, respectively. Bond lengths are given in Å, and bond angles in degrees. The quintet state shows longer bond lengths and wider angles, reflecting the influence of spin multiplicity on molecular geometry.</p>
Full article ">Figure 2
<p>Optimized ground-state geometry of the κ<sup>1</sup>-N-bound [(κ<sup>3</sup>-CNC)Fe<sup>II</sup>(N<sub>2</sub>O)]<sup>2+</sup> cation complex in the quintet (S = 2) spin state. Bond lengths are given in Å and bond angles in degrees. The near-linear Fe–N–N bond angle (167.9°) facilitates oxygen atom transfer (OAT). The high-spin density (~3.94 e<sup>−</sup>) on Fe enhances electron donation to N<sub>2</sub>O, promoting N–O bond cleavage and Fe–O bond formation. This step leads to the formation of the Fe<sup>IV</sup>=O species, a key intermediate in methane activation. The contour value of the spin density plot is 0.020.</p>
Full article ">Figure 3
<p>Optimized geometry of the oxygen atom transfer (OAT) transition state in the triplet (S = 1) spin state, denoted by “<sup>‡</sup>” for transition state (TS) geometry. Bond lengths are given in Å. The near-linear Fe–O–N–N bond alignment facilitates efficient oxygen atom transfer and N<sub>2</sub> release.</p>
Full article ">Figure 4
<p>Optimized ground state geometry and spin density distribution of the Fe<sup>IV</sup>=O complex in the quintet (S = 2) spin state. Bond lengths are given in Å, and spin density values (e<sup>−</sup>) are shown on the Fe center and O atom. The oxyl radical character of the oxygen atom (~0.87 e<sup>−</sup>) and the high-spin Fe center (~3.16 e<sup>−</sup>) make this complex a highly reactive intermediate for methane activation. The contour value of the spin density plot is 0.020.</p>
Full article ">Figure 5
<p>Optimized transition state geometry for HAA by the Fe<sup>IV</sup>=O oxo complex in the triplet (S = 1) spin state, denoted by “<sup>‡</sup>” for transition state (TS) geometry. Bond lengths are given in Å, and bond angles in degrees. Red = positive spin density and blue = negative spin density. The contour value of the spin density plot is 0.020.</p>
Full article ">Figure 6
<p>Optimized transition state geometries for ORR by the Fe<sup>III</sup>–OH intermediate in the triplet (S = 1) spin state, denoted by “<sup>‡</sup>” for transition state (TS) geometry. Bond lengths are given in Å, and bond angles in degrees. Red = positive spin density and blue = negative spin density. The contour value of the spin density plot is 0.020.</p>
Full article ">Scheme 1
<p>General reaction cycle for methane C–H activation via [(κ<sup>3</sup>-CNC)Fe(N2O)]<sup>2</sup>⁺ complexes, involving OAT, HAA, and ORR. The oxygen atom of N<sub>2</sub>O is coordinated trans to the pyridine nitrogen atom of the κ<sup>3</sup>-CNC ligand, facilitating C–H activation.</p>
Full article ">Scheme 2
<p>Proposed catalytic pathway for methane functionalization by [(κ<sup>3</sup>-CNC)Fe(N<sub>2</sub>O)]<sup>2</sup>⁺ complexes, including key transition states for OAT, HAA, and ORR. Energetics are calculated for singlet, triplet, and quintet spin states.</p>
Full article ">Scheme 3
<p>Free energy profile for the catalytic cycle of methane activation by the Fe<sup>IV</sup>=O complex in the gas phase. The energy barriers for the OAT, HAA, and ORR steps are shown for the singlet (<b><span style="color:blue">blue</span></b>), triplet (<span style="color:red">red</span>), and quintet (<b><span style="color:#269A26">green</span></b>) spin states. Energies are reported as Gibbs free energies (ΔG) in kcal/mol, with the triplet and quintet spin states exhibiting competitive pathways, while the singlet state remains energetically less favorable. The key transition states and intermediates are highlighted along with the reaction coordinate.</p>
Full article ">Scheme 4
<p>Free energy profile for the catalytic cycle of methane activation by the Fe<sup>IV</sup>=O complex in the solvation (THF) phase. The energy barriers for the OAT, HAA, and ORR steps are shown for the singlet (<b><span style="color:blue">blue</span></b>), triplet (<span style="color:red">red</span>), and quintet (<b><span style="color:#269A26">green</span></b>) spin states. Energies are reported as Gibbs free energies (ΔG) in kcal/mol, with the triplet and quintet spin states exhibiting competitive pathways, while the singlet state remains energetically less favorable. The key transition states and intermediates are highlighted along with the reaction coordinate.</p>
Full article ">
18 pages, 1106 KiB  
Article
Edelstein Effect in Isotropic and Anisotropic Rashba Models
by Irene Gaiardoni, Mattia Trama, Alfonso Maiellaro, Claudio Guarcello, Francesco Romeo and Roberta Citro
Condens. Matter 2025, 10(1), 15; https://doi.org/10.3390/condmat10010015 - 4 Mar 2025
Viewed by 81
Abstract
We investigate spin-to-charge conversion via the Edelstein effect in a 2D Rashba electron gas using the semiclassical Boltzmann approach. We analyze the magnetization arising from the direct Edelstein effect, taking into account an anisotropic Rashba model. We study how this effect depends on [...] Read more.
We investigate spin-to-charge conversion via the Edelstein effect in a 2D Rashba electron gas using the semiclassical Boltzmann approach. We analyze the magnetization arising from the direct Edelstein effect, taking into account an anisotropic Rashba model. We study how this effect depends on the effective masses and Rashba spin–orbit coupling parameters, extracting analytical expressions for the high electronic density regime. Indeed, it is possible to manipulate the anisotropy introduced into the system through these parameters to achieve a boost in the Edelstein response compared to the isotropic Rashba model. We also discuss the theoretical framework to study the inverse Edelstein effect and calculate self-consistently the electric current induced by the proximity of the system to a ferromagnet. These results provide insights into the role of Rashba spin–orbit coupling and anisotropic effects in spin–charge conversion phenomena. Full article
Show Figures

Figure 1

Figure 1
<p>Direct Rashba–Edelstein Effect: Blue and red indicate the branch of the energy dispersion, + or −. (<b>a</b>) In equilibrium, the total spin polarization vanishes. (<b>b</b>) If an external electric field <math display="inline"><semantics> <mrow> <mi mathvariant="bold">E</mi> <mo>=</mo> <msub> <mi>E</mi> <mi>x</mi> </msub> <mover accent="true"> <mi>x</mi> <mo stretchy="false">^</mo> </mover> </mrow> </semantics></math> is applied, the Fermi lines are shifted opposite to the field direction, and a nonvanishing spin polarization perpendicular to <math display="inline"><semantics> <mi mathvariant="bold">E</mi> </semantics></math> results.</p>
Full article ">Figure 2
<p>(<b>Left panel</b>): The figure shows the Edelstein susceptibility <math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mi>x</mi> <mi>y</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>χ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>2.44</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>2</mn> </msup> <mspace width="0.166667em"/> <msub> <mi>μ</mi> <mi>B</mi> </msub> <mspace width="0.166667em"/> <mi mathvariant="sans-serif">Å</mi> <mspace width="0.166667em"/> <msup> <mi mathvariant="normal">V</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>) as a function of the chemical potential <math display="inline"><semantics> <mi>μ</mi> </semantics></math> for <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <mn>52</mn> <mspace width="0.166667em"/> <mi>meV</mi> <mspace width="0.166667em"/> </mrow> </semantics></math>Å. (<b>Right panel</b>): Fermi surface and spin structure for fixed chemical potential <math display="inline"><semantics> <mrow> <mn>0.06</mn> </mrow> </semantics></math> eV in an isotropic Rashba model. <math display="inline"><semantics> <mrow> <mi>ν</mi> <mo>=</mo> <mo>+</mo> <mn>1</mn> </mrow> </semantics></math> indicates the inner circle (the blue one) and <math display="inline"><semantics> <mrow> <mi>ν</mi> <mo>=</mo> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> the outer one (the red one).</p>
Full article ">Figure 3
<p>(<b>Left panel</b>): Edelstein susceptibility <math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mi>x</mi> <mi>y</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>χ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>2.44</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>2</mn> </msup> </mrow> </semantics></math> <math display="inline"><semantics> <msub> <mi>μ</mi> <mi>B</mi> </msub> </semantics></math> Å V<sup>−1</sup>) as a function of the chemical potential <math display="inline"><semantics> <mi>μ</mi> </semantics></math> for different values of <math display="inline"><semantics> <mi>α</mi> </semantics></math>. The dashed gray line indicates the fixed value of <math display="inline"><semantics> <mi>μ</mi> </semantics></math> used for the plot in the right panel. (<b>Right panel</b>): <math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mi>x</mi> <mi>y</mi> <mo>/</mo> </mrow> </msub> <msub> <mi>χ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <mi>α</mi> </semantics></math> at fixed chemical potential <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>3.32</mn> <mo>·</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math> eV.</p>
Full article ">Figure 4
<p>Fermi surface and spin texture for fixed chemical potential in the anisotropic case. <b>Left Panel</b>: <math display="inline"><semantics> <mrow> <msub> <mi>m</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>0.2</mn> <msub> <mi>m</mi> <mi>x</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mi>y</mi> </msub> <mo>=</mo> <msub> <mi>α</mi> <mi>x</mi> </msub> </mrow> </semantics></math>. <b>Right Panel</b>: <math display="inline"><semantics> <mrow> <msub> <mi>m</mi> <mi>y</mi> </msub> <mo>=</mo> <msub> <mi>m</mi> <mi>x</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>2</mn> <msub> <mi>α</mi> <mi>x</mi> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 5
<p>Edelstein susceptibility <math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mi>x</mi> <mi>y</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>χ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>2.44</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>2</mn> </msup> </mrow> </semantics></math> <math display="inline"><semantics> <msub> <mi>μ</mi> <mi>B</mi> </msub> </semantics></math> Å V<sup>−1</sup>) as a function of the chemical potential <math display="inline"><semantics> <mi>μ</mi> </semantics></math> for different values of (<b>Left panel</b>) <math display="inline"><semantics> <msub> <mi>r</mi> <mi>m</mi> </msub> </semantics></math>, at <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mi>x</mi> </msub> <mo>=</mo> <msub> <mi>α</mi> <mi>y</mi> </msub> <mo>=</mo> <mn>52</mn> </mrow> </semantics></math> meV Å, and (<b>Right panel</b>) <math display="inline"><semantics> <msub> <mi>r</mi> <mi>α</mi> </msub> </semantics></math>, at <math display="inline"><semantics> <mrow> <msub> <mi>m</mi> <mi>x</mi> </msub> <mo>=</mo> <msub> <mi>m</mi> <mi>y</mi> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 6
<p>Edelstein susceptibility <math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mrow> <mi>x</mi> <mi>y</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>χ</mi> <mn>0</mn> </msub> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <msub> <mi>χ</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>2.44</mn> <mo>×</mo> <msup> <mn>10</mn> <mn>2</mn> </msup> </mrow> </semantics></math> <math display="inline"><semantics> <msub> <mi>μ</mi> <mi>B</mi> </msub> </semantics></math> Å V<sup>−1</sup>) as a function of <math display="inline"><semantics> <msub> <mi>r</mi> <mi>m</mi> </msub> </semantics></math> (<b>left panel</b>) and <math display="inline"><semantics> <msub> <mi>r</mi> <mi>α</mi> </msub> </semantics></math> (<b>right panel</b>), for a fixed chemical potential <math display="inline"><semantics> <mrow> <mi>μ</mi> <mo>=</mo> <mn>3.32</mn> <mo>·</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math> eV. The points represent the numerical values obtained for the susceptibility, while the solid line represents the analytically derived expression.</p>
Full article ">Figure 7
<p>Schematic view of the setup for observing the IEE. A 2DEG (in ligth-blue) is covered partly by a ferromagnetic metal (in orange). When a magnetization along <math display="inline"><semantics> <mover accent="true"> <mi>y</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> is near the electron gas, a spin bias along <math display="inline"><semantics> <mover accent="true"> <mi>y</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> occurs. Due to the IEE, an electric current is generated along <math display="inline"><semantics> <mover accent="true"> <mi>x</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> in the system.</p>
Full article ">Figure A1
<p>Electric current, normalized by <math display="inline"><semantics> <mrow> <mi>B</mi> <msub> <mi>G</mi> <mn>0</mn> </msub> </mrow> </semantics></math>, as a function of <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>L</mi> <mi>x</mi> </mrow> </semantics></math> at fixed chemical potential 0.17 eV. In particular, <math display="inline"><semantics> <mrow> <msub> <mi>G</mi> <mn>0</mn> </msub> <mo>=</mo> <msub> <mi>N</mi> <mrow> <mi>c</mi> <mi>h</mi> </mrow> </msub> <mrow> <mo>(</mo> <msup> <mi>e</mi> <mn>2</mn> </msup> <mo>/</mo> <mi>h</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> with <math display="inline"><semantics> <mrow> <msub> <mi>N</mi> <mrow> <mi>c</mi> <mi>h</mi> </mrow> </msub> <mo>=</mo> <mn>4</mn> <msub> <mi>k</mi> <mi>F</mi> </msub> <msub> <mi>L</mi> <mi>y</mi> </msub> <mo>/</mo> <mn>2</mn> <mi>π</mi> </mrow> </semantics></math> as the number of conducting channels and <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mi>x</mi> </msub> <mo>≈</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> </mrow> </semantics></math> as the length of the system along the <math display="inline"><semantics> <mover accent="true"> <mi>x</mi> <mo stretchy="false">^</mo> </mover> </semantics></math> direction. The line is a visual guide.</p>
Full article ">
31 pages, 4371 KiB  
Article
Biological, Equilibrium and Photochemical Signatures of C, N and S Isotopes in the Early Earth and Exoplanet Atmospheres
by James R. Lyons
Life 2025, 15(3), 398; https://doi.org/10.3390/life15030398 - 3 Mar 2025
Viewed by 93
Abstract
The unambiguous detection of biosignatures in exoplanet atmospheres is a primary objective for astrobiologists and exoplanet astronomers. The primary methodology is the observation of combinations of gases considered unlikely to coexist in an atmosphere or individual gases considered to be highly biogenic. Earth-like [...] Read more.
The unambiguous detection of biosignatures in exoplanet atmospheres is a primary objective for astrobiologists and exoplanet astronomers. The primary methodology is the observation of combinations of gases considered unlikely to coexist in an atmosphere or individual gases considered to be highly biogenic. Earth-like examples of the former include CH4 and O3, and the latter includes dimethyl sulfide (DMS). To improve the plausibility of the detection of life, I argue that the isotope ratios of key atmospheric species are needed. The C isotope ratios of CO2 and CH4 are especially valuable. On Earth, thermogenesis and volcanism result in a substantial difference in δ13C between atmospheric CH4 and CO2 of ~−25‰. This difference could have changed significantly, perhaps as large as −95‰ after the evolution of hydrogenotrophic methanogens. In contrast, nitrogen fixation by nitrogenase results in a relatively small difference in δ15N between N2 and NH3. Isotopic biosignatures on ancient Earth and rocky exoplanets likely coexist with much larger photochemical signatures. Extreme δ15N enrichment in HCN may be due to photochemical self-shielding in N2, a purely abiotic process. Spin-forbidden photolysis of CO2 produces CO with δ13C < −200‰, as has been observed in the Venus mesosphere. Self-shielding in SO2 may generate detectable 34S enrichment in SO in atmospheres similar to that of WASP-39b. Sufficiently precise isotope ratio measurements of these and related gases in terrestrial-type exoplanet atmospheres will require instruments with significantly higher spectral resolutions and light-collecting areas than those currently available. Full article
(This article belongs to the Special Issue Origin of Life in Chemically Complex Messy Environments: 2nd Edition)
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Figure 1

Figure 1
<p>(<b>a</b>) Beta factors for C isotope exchange for several C-containing molecules relevant to exoplanet and early Earth atmospheres. (<b>b</b>) Beta factors for N isotope exchange for several N-containing molecules relevant to exoplanet and early Earth atmospheres. (<b>c</b>) Beta factors for <sup>34</sup>S–<sup>32</sup>S isotope exchange for several S-containing molecules relevant to exoplanet and early Earth atmospheres.</p>
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<p>(<b>a</b>) Beta factors for C isotope exchange for several C-containing molecules relevant to exoplanet and early Earth atmospheres. (<b>b</b>) Beta factors for N isotope exchange for several N-containing molecules relevant to exoplanet and early Earth atmospheres. (<b>c</b>) Beta factors for <sup>34</sup>S–<sup>32</sup>S isotope exchange for several S-containing molecules relevant to exoplanet and early Earth atmospheres.</p>
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<p>(<b>a</b>) Differences in equilibrium δ<sup>13</sup>C values, defined as Δδ<sup>13</sup>C, for several pairs of C-containing molecules relevant to exoplanet atmospheres. Attaining equilibrium at lower temperatures would require the presence of a catalyst. (<b>b</b>) Differences in equilibrium δ<sup>15</sup>N values, defined as Δδ<sup>15</sup>N, for several pairs of N-containing molecules relevant to exoplanet atmospheres. N<sub>2</sub> is included here as an important reference, but its isotope ratio cannot be determined from infrared observations. (<b>c</b>) Differences in equilibrium δ<sup>34</sup>S values, defined as Δδ<sup>34</sup>S, for several pairs of S-containing molecules relative to H<sub>2</sub>S and relevant to exoplanet atmospheres. S<sub>2</sub> is included here as an important reference, but its isotope ratio cannot be determined from the infrared observations.</p>
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<p>(<b>a</b>) Differences in equilibrium δ<sup>13</sup>C values, defined as Δδ<sup>13</sup>C, for several pairs of C-containing molecules relevant to exoplanet atmospheres. Attaining equilibrium at lower temperatures would require the presence of a catalyst. (<b>b</b>) Differences in equilibrium δ<sup>15</sup>N values, defined as Δδ<sup>15</sup>N, for several pairs of N-containing molecules relevant to exoplanet atmospheres. N<sub>2</sub> is included here as an important reference, but its isotope ratio cannot be determined from infrared observations. (<b>c</b>) Differences in equilibrium δ<sup>34</sup>S values, defined as Δδ<sup>34</sup>S, for several pairs of S-containing molecules relative to H<sub>2</sub>S and relevant to exoplanet atmospheres. S<sub>2</sub> is included here as an important reference, but its isotope ratio cannot be determined from the infrared observations.</p>
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<p>Photodissociation rate coefficients for <sup>28</sup>N<sub>2</sub> and <sup>29</sup>N<sub>2</sub> isotopologues for an Earth atmosphere model for a solar zenith angle (SZA) of 45°. The more abundant <sup>28</sup>N<sub>2</sub> is optically thicker at a given altitude than is <sup>29</sup>N<sub>2</sub>. This defines the self-shielding region to be from ~350 km to 120 km, but it should be noted that the rate coefficient has decreased by two orders of magnitude by 120 km.</p>
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<p>δ<sup>15</sup>N of N atoms due to N<sub>2</sub> self-shielding for several values of the rate constant for N exchange with N<sub>2</sub>. Measurements at 1273 K indicate that this exchange reaction is effectively zero at lower temperatures [<a href="#B45-life-15-00398" class="html-bibr">45</a>], implying that the black curve is the most plausible. Peak enrichment occurs from 150–200 km. The possible recombination of N with NH is not included here.</p>
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<p>δ<sup>15</sup>N of N(<sup>2</sup>D) for several values of the rate constant for N(<sup>2</sup>D) exchange with N<sub>2</sub>. To the best of the author’s knowledge, this rate constant has not been measured.</p>
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<p>Measured UV cross sections of HCN and DCN.</p>
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<p>Computed carbon isotope fractionation due to CO<sub>2</sub> photolysis in the Venus mesosphere using the computed isotopic cross sections at 195 K (black) and 120 K (red) [<a href="#B47-life-15-00398" class="html-bibr">47</a>]. Millimeter wave observations of <sup>12</sup>CO/<sup>13</sup>CO from [<a href="#B52-life-15-00398" class="html-bibr">52</a>] have been converted to δ-values with uncertainties. Additional fractionation processes may be required.</p>
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<p>Composition of the Earth atmosphere over time. These are representative partial pressure curves with large uncertainties for ages &gt;1 Gyr and very large uncertainties beyond 3 Gyr. The N<sub>2</sub>, CO<sub>2</sub>, CH<sub>4,</sub> and O<sub>2</sub> curves are from a review by Catling and Zahnle (2020) [<a href="#B2-life-15-00398" class="html-bibr">2</a>]. HCN is estimated to be 10<sup>−1</sup> times the CH<sub>4</sub> partial pressure prior to the Great Oxidation Event (GOE) at 2.4 Gyr and 10<sup>−4</sup> times CH<sub>4</sub> after the GOE. My focus here is on the detectable species CO<sub>2</sub>, CH<sub>4,</sub> and HCN for ages &gt; 2.5 Gyr.</p>
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<p>C and H isotope ratios for various biogenic and abiogenic CH<sub>4</sub> processes. The fields defined here for microbial, thermogenic, and geothermal CH<sub>4</sub> are from Whiticar (2020). I assume that the earliest Earth (4.4 to 4.0 Gyr) had thermogenic and/or geothermal CH<sub>4</sub> sources and that hydrogenotrophic methanogens were present after 4.0 Gyr. Acetoclastic and methylotrophic methanogens were also important sources of CH<sub>4</sub> prior to the GOE. In general, abiogenic processes occur at higher temperatures than biogenic processes.</p>
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<p>Schematic representation of δ<sup>13</sup>C evolution in the Earth’s atmosphere. In the simplest scenario, CO<sub>2</sub> is derived from volcanism and has δ<sup>13</sup>C ~−6.5‰ as for mantle C. CO<sub>2</sub> undergoes gas exchange with the surface ocean throughout Earth history since 4.4 Gyr ago (black line). More likely, CO<sub>2</sub> tracked the carbonates. The carbonates curve (thick cyan line) is a smoothed version of measurements of δ<sup>13</sup>C for marine carbonates over the past 3.5 Gyr [<a href="#B65-life-15-00398" class="html-bibr">65</a>]. The curve illustrates the approximate range of variation seen in marine carbonates, which would likely be present in atmospheric CO<sub>2</sub>. Atmospheric CO<sub>2</sub> will track carbonates but will be displaced by about −6.5‰ (thick gray curve). The CO curve illustrates the effect of isotope fractionation during CO<sub>2</sub> photolysis in the upper atmosphere. Although δ<sup>13</sup>C for CO is constant over time, the CO mixing ratio decreases by many orders of magnitude from ~10<sup>−3</sup> at 4 Gyr to ~10<sup>−10</sup> today. The CH<sub>4</sub> curve (blue line) illustrates abiogenic sources prior to 4.0 Gyr ago, followed by hydrogenotrophic methanogenesis for the next ~1.5 Gyr, and then CH<sub>4</sub> with modern δ<sup>13</sup>C values after the GOE at 2.4 Gyr ago. The mean δ<sup>13</sup>C for organics recorded from rocks (thick orange line) [<a href="#B62-life-15-00398" class="html-bibr">62</a>] does not exhibit highly negative δ<sup>13</sup>C, indicating that either the rock record does not entirely correlate with atmospheric CH<sub>4</sub> or that methanogenesis was not a major biochemical process (dotted blue line). The δ<sup>13</sup>C difference between CO<sub>2</sub> and abiogenic CH<sub>4</sub> is ~25‰ versus ~95‰ between CO<sub>2</sub> and hydrogenotrophic methanogen CH<sub>4</sub>. This comparison of CO<sub>2</sub> and CH<sub>4</sub> may represent a viable biosignature in a given terrestrial exoplanet atmosphere.</p>
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<p>(<b>a</b>) Normalized line intensities at 296 K for the ν<sub>2</sub> band (bending mode) of <sup>12</sup>CO<sub>2</sub> and <sup>13</sup>CO<sub>2</sub>. The redshift of the <sup>13</sup>CO<sub>2</sub> spectrum is ~19 cm<sup>−1</sup>. (<b>b</b>) For the CO<sub>2</sub> ν<sub>3</sub> band (asymmetric stretch) the redshift is larger at ~70 cm<sup>−1</sup>. For both figures, the <sup>13</sup>CO<sub>2</sub> line intensity has been normalized by the <sup>13</sup>C fraction (0.011057) given in HITRAN. Data were obtained from HITRANonline [<a href="#B66-life-15-00398" class="html-bibr">66</a>].</p>
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<p>(<b>a</b>) Normalized line intensities of <sup>12</sup>CH<sub>4</sub> and <sup>13</sup>CH<sub>4</sub> in the ν<sub>4</sub> band, and (<b>b</b>) in the <b>ν</b><sub>3</sub> band. The ν<sub>3</sub> band has a redshift of ~10 cm<sup>−1</sup> for <sup>13</sup>CH<sub>4</sub>, and the ν<sub>4</sub> band has a redshift of ~8 cm<sup>−1</sup>. For both these figures, the <sup>13</sup>CH<sub>4</sub> line intensity has been normalized by the <sup>13</sup>C fraction (0.011103) given in HITRAN. Data from HITRANonline [<a href="#B66-life-15-00398" class="html-bibr">66</a>].</p>
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<p>(<b>a</b>) Normalized line intensities for the ν<sub>2</sub> band (bending mode) of three isotopologues of HCN. (<b>b</b>) A zoomed-in view of the Q branches illustrating the very small band shift for HC<sup>15</sup>N. Note that the HITRAN data for HC<sup>15</sup>N are incomplete and show only the envelope of the Q-branch. For both figures, the H<sup>13</sup>CN and HC<sup>15</sup>N line intensities are normalized by the <sup>13</sup>C fraction (0.011068) and <sup>15</sup>N fraction (0.003622) given in HITRAN. Data from HITRANonline [<a href="#B66-life-15-00398" class="html-bibr">66</a>].</p>
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<p>(<b>a</b>) Normalized line intensities for the ν<sub>3</sub> band (asymmetric stretch) of <sup>32</sup>SO<sub>2</sub> and <sup>34</sup>SO<sub>2</sub>. (<b>b</b>) Line intensities illustrating the high line density typical of SO<sub>2</sub> over a range of just 2 cm<sup>−1</sup>. For both figures, the <sup>32</sup>SO<sub>2</sub> and <sup>34</sup>SO<sub>2</sub> line intensities are normalized by the <sup>32</sup>S fraction (0.945678) and <sup>34</sup>S fraction (0.041950) given in HITRAN. Data from HITRANonline [<a href="#B66-life-15-00398" class="html-bibr">66</a>].</p>
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25 pages, 8015 KiB  
Review
Metal Complexes of Bispidine Derivatives: Achievements and Prospects for the Future
by Altynay B. Kaldybayeva, Valentina K. Yu, Feyyaz Durap, Murat Aydemir and Khaidar S. Tassibekov
Molecules 2025, 30(5), 1138; https://doi.org/10.3390/molecules30051138 - 3 Mar 2025
Viewed by 171
Abstract
Multidentate bispidine ligands, including tetra-, penta-, hexa-, hepta-, and octadentate variants, exhibit strong coordination tendencies due to their intrinsic rigidity, significant reorganization potential, and ability to efficiently encapsulate metal ions. These structural attributes profoundly influence the thermodynamic stability, metal ion selectivity, redox behavior, [...] Read more.
Multidentate bispidine ligands, including tetra-, penta-, hexa-, hepta-, and octadentate variants, exhibit strong coordination tendencies due to their intrinsic rigidity, significant reorganization potential, and ability to efficiently encapsulate metal ions. These structural attributes profoundly influence the thermodynamic stability, metal ion selectivity, redox behavior, and spin-state configuration of the resulting complexes. Metal ions, in turn, serve as highly suitable candidates for coordination due to their remarkable kinetic inertness, rapid complex formation kinetics, and low redox potential. This review focuses on ligands incorporating the bispidine core (3,7-diazabicyclo[3.3.1]nonane) and provides an overview of advancements in the synthesis of metal complexes involving p-, d-, and f-block elements. Furthermore, the rationale behind the growing interest in bispidine-based complexes for applications in radiopharmaceuticals, medicinal chemistry, and organic synthesis is explored, particularly in the context of their potential for diagnostic and catalytic drug development. Full article
(This article belongs to the Special Issue Organometallic Compounds: Design, Synthesis and Application)
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Figure 1
<p>Bispidine framework and natural alkaloids containing it.</p>
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<p>Possible configuration isomers of bispidine.</p>
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<p>Structural conformations of bispidons. (<b>a</b>) cis-chair–chair, (<b>b</b>) cis-chair–boat, (<b>c</b>) trans-chair–boat, (<b>d</b>) trans-boat–chair.</p>
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<p>Structures of bispidine ligands.</p>
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<p>Structures of bispidine ligands.</p>
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<p>Synthesis methods of 3,7-diazabicyclo[3.3.1]nonanes. (I) Mannich reaction-based synthesis from carbonyl compounds and aliphatic amines [<a href="#B16-molecules-30-01138" class="html-bibr">16</a>]; (II) transformation of 4-piperidones into 3,7-diazabicyclo[3.3.1]nonanes [<a href="#B17-molecules-30-01138" class="html-bibr">17</a>]; (III) acid hydrolysis of carboxylic acid nitrile derivatives, reduction and, in some cases, alkylation (or acylation with subsequent reduction) of the obtained 3,7-diazabicyclo[3.3.1]nonanes [<a href="#B18-molecules-30-01138" class="html-bibr">18</a>]; (IV) cyclization of 3,5-bifunctional piperidine derivatives [<a href="#B13-molecules-30-01138" class="html-bibr">13</a>]; (V) ring-opening of the 1,3-diazaadamantane cycle [<a href="#B19-molecules-30-01138" class="html-bibr">19</a>].</p>
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<p>Synthesis of complex <b>5</b>.</p>
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<p>Synthesis of copper complexes <b>6 a</b>–<b>d</b>.</p>
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<p>Reaction of <b>L 6</b> with copper salt.</p>
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<p>Reaction of bispidine containing ligand <b>L 12</b> with copper salt.</p>
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<p>Synthesis of complex <b>9</b>.</p>
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<p>Synthesis of copper complex <b>11</b>.</p>
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<p>Reaction of <b>L 17</b> with copper salts.</p>
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<p>Synthesis of copper-based complex <b>14</b>.</p>
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<p>Synthesis of complex <b>15 b</b>.</p>
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<p>Synthesis of hexacoordinate Cu complexes <b>16 a</b>, <b>b</b>.</p>
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<p>Reaction tetradentate bispidine ligand <b>L 23</b> with copper salt.</p>
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<p>Synthesis of copper complex <b>18 a</b>.</p>
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<p>Synthesis of complex <b>19 a</b>.</p>
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<p>Reaction of <b>L 31</b>–<b>33</b> with an iron salt.</p>
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<p>Synthesis of heptacoordinate Fe complex <b>21</b>.</p>
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<p>Reaction tetradentate bispidine ligand <b>L 35</b> with an iron salt.</p>
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<p>Synthesis of iron-based complex <b>23a</b>.</p>
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<p>Synthesis of complex <b>24</b>.</p>
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<p>Reaction of <b>L 15</b> with manganese salt.</p>
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<p>Reaction of <b>L 40</b> with a platinum salt.</p>
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<p>Synthesis of tetracoordinate Pt complex <b>27</b>.</p>
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<p>Reaction of <b>L 42</b> with palladium salt.</p>
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<p>Synthesis of nickel complex <b>29</b>.</p>
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<p>Synthesis of complex <b>30</b>.</p>
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<p>Reaction of <b>L 44</b> with various metal salts.</p>
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<p>Reaction of <b>L 46</b> with metal salts.</p>
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<p>Synthesis of mercury complexes <b>35 a</b>, <b>b</b>.</p>
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<p>Synthesis of bismuth-based complex <b>36 a</b>.</p>
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<p>Synthesis of complex <b>37 b</b>.</p>
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<p>Reaction heptadentate bispidine ligand <b>L 54</b> with an indium salt.</p>
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<p>Reaction hexadentate bispidine ligand <b>L 51</b> with a lutetium salt.</p>
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<p>Synthesis of terbium complex <b>42</b>.</p>
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<p>Synthesis of complexes <b>45</b>–<b>47</b>.</p>
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13 pages, 2216 KiB  
Article
Characterization of Gramicidin A in Triblock and Diblock Polymersomes and Hybrid Vesicles via Continuous Wave Electron Paramagnetic Resonance Spectroscopy
by Emma A. Gordon, Indra D. Sahu, Joel R. Fried and Gary A. Lorigan
Biomimetics 2025, 10(3), 154; https://doi.org/10.3390/biomimetics10030154 - 2 Mar 2025
Viewed by 332
Abstract
Studying membrane proteins in a native environment is crucial to understanding their structural and/or functional studies. Often, widely accepted mimetic systems have limitations that prevent the study of some membrane proteins. Micelles, bicelles, and liposomes are common biomimetic systems but have problems with [...] Read more.
Studying membrane proteins in a native environment is crucial to understanding their structural and/or functional studies. Often, widely accepted mimetic systems have limitations that prevent the study of some membrane proteins. Micelles, bicelles, and liposomes are common biomimetic systems but have problems with membrane compatibility, limited lipid composition, and heterogeneity. To overcome these limitations, polymersomes and hybrid vesicles have become popular alternatives. Polymersomes form from amphiphilic triblock or diblock copolymers and are considered more robust than liposomes. Hybrid vesicles are a combination of lipids and block copolymers that form vesicles composed of a mixture of the two. These hybrid vesicles are appealing because they have the native lipid environment of bilayers but also the stability and customizability of polymersomes. Gramicidin A was incorporated into these polymersomes and characterized using continuous wave electron paramagnetic resonance (CW-EPR) and transmission electron microscopy (TEM). EPR spectroscopy is a powerful biophysical technique used to study the structure and dynamic properties of membrane proteins in their native environment. Spectroscopic studies of gramicidin A have been limited to liposomes; in this study, the membrane peptide is studied in both polymersomes and hybrid vesicles using CW-EPR spectroscopy. Lineshape analysis of spin-labeled gramicidin A revealed linewidth broadening, suggesting that the thicker polymersome membranes restrict the motion of the spin label more when compared to liposome membranes. Statement of Significance: Understanding membrane proteins’ structures and functions is critical in the study of many diseases. In order to study them in a native environment, membrane mimetics must be developed that can be suitable for obtaining superior biophysical data quality to characterize structural dynamics while maintaining their native functions and structures. Many currently widely accepted methods have limitations, such as a loss of native structure and function, heterogeneous vesicle formation, restricted lipid types for the vesicle formation for many proteins, and experimental artifacts, which leaves rooms for the development of new biomembrane mimetics. The triblock and diblock polymersomes and hybrid versicles utilized in this study may overcome these limitations and provide the stability and customizability of polymersomes, keeping the biocompatibility and functionality of liposomes for EPR studies of membrane proteins. Full article
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Figure 1
<p>CW-EPR spectra of spin-labeled lipids incorporated into liposomes and polymersomes collected at 298 K. (<b>A</b>) Spectra for liposomes composed of DMPC with incorporated 5-, 12-, 16-doxyl PC spin-labeled lipids. (<b>B</b>) Spectra for polymersomes composed of triblock copolymers with incorporated 5-, 12-, 16-doxyl PC spin-labeled lipids. (<b>C</b>) Spectra for polymersomes composed of diblock copolymers with incorporated 5-, 12-, 16-doxyl PC spin-labeled lipids (<b>D</b>) Inverse central linewidth (ΔH<sup>−1</sup>) of EPR spectra as a function of the spin label lipid incorporated in the vesicles.</p>
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<p>(<b>A</b>) CW-EPR spectra, collected at 298 K, for gramicidin A mutants: A3C and W13C incorporated into DMPC liposomes, DPPC liposomes, triblock polymersomes, and diblock polymersomes. Both mutants are located inside the membrane, as shown by the insets depicting the amino acid sequence and head-to-head dimer formation. The blue dots represent the sites mutated for the addition of a spin label. (<b>B</b>) Inverse central linewidth (ΔH<sup>−1</sup>) of EPR spectra as a function of the vesicle types containing the mutants. The error bars were determined from three repeated measurements.</p>
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<p>(<b>A</b>) CW-EPR spectra, collected at 298 K, for spin-labeled gramicidin A (A3C) incorporated into hybrid vesicles. Hybrid vesicles were composed of a mixture of either triblock or diblock copolymers and either DOPC, POPC, DPPC, or DMPC lipids. (<b>B</b>) Inverse central linewidth (ΔH<sup>−1</sup>) of EPR spectra as a function of the vesicle types containing the mutants. The error bars were determined from three repeated measurements.</p>
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<p>EPR spectral simulation for (<b>A</b>) 16:0 5-doxyl PC spin-labeled lipids in DMPC, triblock, and diblock vesicles; (<b>B</b>) gramicidin A mutant A3C incorporated into DMPC, DPPC, triblock, and diblock vesicles; (<b>C</b>) gramicidin A mutant A3C incorporated into hybrid vesicles composed of DMPC/triblock and DMPC/diblock. Experimental data are in black and the fitted data are in red.</p>
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<p>(<b>A</b>) Schematic of gramicidin A in a lipid bilayer in a head-to-head dimer formation. (<b>B</b>) Schematic of polymersomes and hybrid vesicles. TEM micrographs of (<b>C</b>) liposomes composed of DMPC lipids, (<b>D</b>) liposomes composed of DPPC lipids, (<b>E</b>) polymersomes composed of triblock copolymers, (<b>F</b>) polymersomes composed of diblock copolymers, (<b>G</b>) hybrid vesicles composed of POPC and triblock copolymers, and (<b>H</b>) hybrid vesicles composed of POPC and diblock copolymers.</p>
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13 pages, 6588 KiB  
Article
Direct Synthesis of LiAlH4 from Ti-Doped Active LiAl Alloy
by Yan Chu, Shiwei Fang, Yingjue Chen, Xiaoqi Zhang, Jie Zheng, Zhenglong Li, Wubin Du, Wengang Cui, Jian Miao, Yaxiong Yang, Yongfeng Liu, Mingxia Gao and Hongge Pan
Inorganics 2025, 13(3), 74; https://doi.org/10.3390/inorganics13030074 - 1 Mar 2025
Viewed by 155
Abstract
LiAlH4, characterized by high hydrogen capacity and metastable properties, is regarded as a promising hydrogen source under mild conditions. However, its reversible regeneration from dehydrogenated production is hindered thermodynamically and kinetically. Herein, we demonstrate an active Li–Al–Ti nanocrystalline alloy prepared by [...] Read more.
LiAlH4, characterized by high hydrogen capacity and metastable properties, is regarded as a promising hydrogen source under mild conditions. However, its reversible regeneration from dehydrogenated production is hindered thermodynamically and kinetically. Herein, we demonstrate an active Li–Al–Ti nanocrystalline alloy prepared by melt spinning and cryomilling to enable directly synthesizing nano-LiAlH4. Due to the non-equilibrium preparation methods, the grain/particle size of the alloy was reduced, stress defects were introduced, and the dispersion of the Ti catalyst was promoted. The refined Li–Al–Ti nanocrystalline alloy with abundant defects and uniform catalytic sites demonstrated a high reactivity of the particle surface, thereby enhancing hydrogen absorption and desorption kinetics. Nano-LiAlH4 was directly obtained by ball milling a 5% Ti containing Li–Al–Ti nanocrystalline alloy with a grain size of 17.4 nm and Al3Ti catalytic phase distributed under 20 bar hydrogen pressure for 16 h. The obtained LiAlH4 exhibited room temperature dehydrogenation performance and good reversibility. This finding provides a potential strategy for the non-solvent synthesis and direct hydrogenation of metastable LiAlH4 hydrogen storage materials. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>a</b>) Schematic diagram of the preparation process of active LAT alloys; optical photographs of (<b>b</b>) as-cast alloy by induction smelting, (<b>c</b>) alloy flakes by melt spinning, and (<b>d</b>) alloy powder after cryomilling.</p>
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<p>XRD patterns of LAT–b, LAT–2000, and LAT–4000 alloy flakes.</p>
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<p>SEM of (<b>a</b>) LAT-b, (<b>b</b>) LAT-2000, and (<b>c</b>) LAT-4000; corresponding (<b>d</b>–<b>f</b>) EDX mapping (<b>g</b>–<b>i</b>) corresponding BSE images.</p>
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<p>(<b>a</b>) XRD patterns and (<b>b</b>) corresponding crystallite size and strain of LAT–b–CM, LAT–2000–CM, and LAT–4000–CM; SEM images of (<b>c</b>) LAT–b–CM, (<b>d</b>) LAT–2000–CM, and (<b>e</b>) LAT–4000–CM, respectively; (<b>f</b>) TEM and corresponding EDX mapping of LAT–4000–CM.</p>
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<p>(<b>a</b>) XRD patterns and (<b>b</b>) Non-isothermal dehydrogen curves of LAT–b–CM–H, LAT–2000–CM–H, LAT–4000–CM–H samples; (<b>c</b>) hydrogen mass spectrum of LAT–4000–CM–H sample; (<b>d</b>) survey XPS spectra, and (<b>e</b>) Al 2p XPS spectra of LAT–4000–CM–H and as-received LiAlH<sub>4</sub>.</p>
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<p>(<b>a</b>) XRD patterns of LAT–4000–CM and LA–b alloy, (<b>b</b>) XRD patterns, (<b>c</b>) non-isothermal dehydrogen curves, (<b>d</b>) survey XPS spectra, and (<b>e</b>) Al 2p XPS spectra of LAT–4000–CM–H and LA–b–H samples.</p>
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<p>(<b>a</b>) Non-isothermal dehydrogen curves, (<b>b</b>) survey XPS spectra, (<b>c</b>) Al 2p XPS spectrum, and (<b>d</b>) Li 1s XPS spectrum of rehydrogenated LAT–4000–CM–H.</p>
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10 pages, 5938 KiB  
Article
Improvement of Electrical Transport Performance of BiSbTeSe2 by Elemental Doping
by Peng Zhu, Xin Zhang, Liu Yang, Yuqi Zhang, Deng Hu, Fuhong Chen, Haoyu Qi and Zhiwei Wang
Materials 2025, 18(5), 1110; https://doi.org/10.3390/ma18051110 - 28 Feb 2025
Viewed by 171
Abstract
A topological insulator with large bulk-insulating behavior and high electron mobility of the surface state is needed urgently, not only because it would be a good platform for studying topological surface states but also because it is a prerequisite for potential future applications. [...] Read more.
A topological insulator with large bulk-insulating behavior and high electron mobility of the surface state is needed urgently, not only because it would be a good platform for studying topological surface states but also because it is a prerequisite for potential future applications. In this work, we demonstrated that tin (Sn) or indium (In) dopants could be introduced into a BiSbTeSe2 single crystal. The impacts of the dopants on the bulk-insulating property and electron mobility of the surface state were systematically investigated by electrical transport measurements. The doped single crystals had the same crystal structure as the pristine BiSbTeSe2, no impure phase was observed, and all elements were distributed homogeneously. The electrical transport measurements illustrated that slight Sn doping could improve the performance of BiSbTeSe2 a lot, as the longitudinal resistivity (ρxx), bulk carrier density (nb), and electron mobility of the surface state (μs) reached about 11 Ωcm, 7.40 × 1014 cm−3, and 6930 cm2/(Vs), respectively. By comparison, indium doping could also improve the performance of BiSbTeSe2 with ρxx, nb, and μs up to about 13 Ωcm, 1.29 × 1015 cm−3, and 4500 cm2/(Vs), respectively. Our findings suggest that Sn- or indium-doped BiSbTeSe2 crystals should be good platforms for studying novel topological properties, as well as promising candidates for low-dissipation electron transport, spin electronics, and quantum computing. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>a</b>) Optical images of BiSbTeSe<sub>2</sub>, Sn<span class="html-italic"><sub>x</sub></span>Bi<sub>1-<span class="html-italic">x</span></sub>SbTeSe<sub>2</sub> (<span class="html-italic">x</span> = 0.02), and In<sub>y</sub>Bi<sub>1-<span class="html-italic">y</span></sub>SbTeSe<sub>2</sub> (<span class="html-italic">y</span> = 0.04) single crystals. (<b>b</b>) XRD patterns for all as-grown samples, indicating (00<span class="html-italic">l</span>) planes. (<b>c</b>) Spectrum of EDS for <span class="html-italic">y</span> = 0.05 sample. (<b>d</b>) Elemental mapping of Sn<span class="html-italic"><sub>x</sub></span>Bi<sub>1-<span class="html-italic">x</span></sub>SbTeSe<sub>2</sub> (<span class="html-italic">x</span> = 0.05) and In<span class="html-italic"><sub>y</sub></span>Bi<sub>1-<span class="html-italic">y</span></sub>SbTeSe<sub>2</sub> (<span class="html-italic">y</span> = 0.05) single crystals.</p>
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<p>Electrical transport results of parent BiSbTeSe<sub>2</sub> bulk crystal. (<b>a</b>) Temperature dependence of resistivity of BiSbTeSe<sub>2</sub>. The inset shows the measurement scheme. (<b>b</b>) Arrhenius plots of <span class="html-italic">ρ<sub>xx</sub></span>(<span class="html-italic">T</span>). The cyan dashed line represents the linear fitting. (<b>c</b>) Magnetic field dependence of MR measured at 2 K. (<b>d</b>) Hall resistance measured at 2 K; the yellow dashed curve shows the result of two-band fitting.</p>
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<p>Electrical transport results of Sn<span class="html-italic"><sub>x</sub></span>Bi<sub>1-<span class="html-italic">x</span></sub>SbTeSe<sub>2</sub> crystals: (<b>a</b>) temperature dependence of resistivity of Sn<span class="html-italic"><sub>x</sub></span>Bi<sub>1-<span class="html-italic">x</span></sub>SbTeSe<sub>2</sub>; (<b>b</b>) Arrhenius plots of <span class="html-italic">ρ<sub>xx</sub></span>(<span class="html-italic">T</span>), the cyan dashed line represents the linear fitting; (<b>c</b>) MR at 2 K; and (<b>d</b>) Hall resistance at 2 K, where the yellow curves show the respective two-band fitting.</p>
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<p>Electrical transport results of parent In<sub><span class="html-italic">y</span></sub>Bi<sub>1-<span class="html-italic">y</span></sub>SbTeSe<sub>2</sub> crystals: (<b>a</b>) temperature dependence of resistivity curves <span class="html-italic">ρ</span><sub>xx</sub>(<span class="html-italic">T</span>); (<b>b</b>) Arrhenius plots of <span class="html-italic">ρ<sub>xx</sub></span>(<span class="html-italic">T</span>), the cyan dashed line represents the linear fitting; (<b>c</b>) MR at 2 K; and (<b>d</b>) Hall resistance at 2 K, where the yellow curves show the respective two-band fitting.</p>
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14 pages, 1179 KiB  
Article
Transient Heat Transfer Modeling of SERF Co-Magnetometer Atomic Ensemble Based on the Thermoelectric Analogy Method
by Jiaqi Wu, Feng Liu, Lihong Duan, Shaowei Lv, Xihui Dou and Wei Quan
Photonics 2025, 12(3), 224; https://doi.org/10.3390/photonics12030224 - 28 Feb 2025
Viewed by 185
Abstract
Bias instability is one of the most critical factors in the performance of spin-exchange relaxation-free (SERF) co-magnetometers. Previous studies on SERF co-magnetometers have shown that changes in the atomic ensemble temperature can lead to variations in the alkali metal atom density, which in [...] Read more.
Bias instability is one of the most critical factors in the performance of spin-exchange relaxation-free (SERF) co-magnetometers. Previous studies on SERF co-magnetometers have shown that changes in the atomic ensemble temperature can lead to variations in the alkali metal atom density, which in turn affect the optical rotation angle and light shift, ultimately influencing the system’s stability. Building on this understanding, this paper introduces the thermoelectric analogy method for the first time in the transient heat transfer analysis of SERF co-magnetometer atomic ensembles. Using this method, the primary factors affecting the atomic ensemble temperature in a SERF co-magnetometer were analyzed, and transient heat transfer models were established for the following processes: the interaction between the non-magnetic electric heating system and the atomic ensemble temperature, laser heating of the atomic ensemble by the optical system, and the effect of environmental temperature changes on the non-magnetic electric heating system. These models were experimentally validated through active temperature variation experiments. The experimental results show that the proposed transient heat transfer models accurately describe the related heat transfer processes of the atomic ensemble, with model fitting accuracy exceeding 98%. This lays a solid foundation for the high-precision closed-loop control of the atomic ensemble temperature in SERF co-magnetometers and provides valuable insights for the structural design and engineering applications of SERF co-magnetometers. Full article
(This article belongs to the Special Issue Quantum Enhanced Devices and Instruments for Sensing Applications)
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<p>RC heat transfer network of non-magnetic electric heating and atomic ensemble temperature.</p>
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<p>RC heat transfer network of the laser heating and atomic ensemble temperature.</p>
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<p>RC heat transfer network between environmental temperature and heating film temperature.</p>
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<p>The experimental setup of the SERF co-magnetometer. Oven: non-magnetic electric heating device for heating the vapor cell; Pt: Pt1000 platinum resistance; coils: active magnetic compensation coil; mirror: right angle mirror; PBS: polarization beam splitter; LCVR: a liquid crystal; OPSS: optical power stabilization system; PD: photodetector; PL: beam expander assembly.</p>
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<p>Temperature Variation of Atomic Ensemble and Non-Magnetic Electric Heating System. <math display="inline"><semantics> <msub> <mi>T</mi> <mi>heat</mi> </msub> </semantics></math>: the temperatures of the heating film; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>2</mn> </msub> </semantics></math>: the inner wall temperature of the oven; <math display="inline"><semantics> <msub> <mi>T</mi> <mi>cell</mi> </msub> </semantics></math>: the temperature of atomic ensemble.</p>
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<p>Comparison of 4R2C heat transfer model and measured curve.</p>
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<p>Temperature variation of atomic ensemble and laser heating. <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>p</mi> <mn>1</mn> </mrow> </msub> </semantics></math>: the temperatures at the point where the laser enters the vapor cell; <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>p</mi> <mn>2</mn> </mrow> </msub> </semantics></math>: the temperatures at the point where the laser exits the vapor cell; <math display="inline"><semantics> <msub> <mi>T</mi> <mi>cell</mi> </msub> </semantics></math>: the temperature of the atomic ensemble.</p>
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<p>Comparison of 2R1C heat transfer model and experimental data.</p>
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<p>Temperature variation of different parts of the SERF co-magnetometer with environmental temperature. <math display="inline"><semantics> <msub> <mi>T</mi> <mi>env</mi> </msub> </semantics></math>: the temperature of environment; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>5</mn> </msub> </semantics></math>: the temperature of main structure; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>7</mn> </msub> </semantics></math>: the temperature of first layer permalloy magnetic shield; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>9</mn> </msub> </semantics></math>: the temperature of second layer permalloy magnetic shield; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>11</mn> </msub> </semantics></math>: the temperature of ferrite magnetic shield; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>13</mn> </msub> </semantics></math>: the temperature of active magnetic compensation coil; <math display="inline"><semantics> <msub> <mi>T</mi> <mn>15</mn> </msub> </semantics></math>: the temperature of oven support; and <math display="inline"><semantics> <msub> <mi>T</mi> <mrow> <mi>h</mi> <mi>e</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math>: the temperature of heating film.</p>
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<p>Comparison of the 14R7C heat transfer model with the experimental results.</p>
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<p>Comparison of the 14R7C heat transfer model with the experimental results.</p>
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14 pages, 994 KiB  
Article
Long-Term Timing Analysis of PSR J1741—3016: Efficient Noise Characterization Using PINT
by Yirong Wen, Jingbo Wang, Wenming Yan, Jianping Yuan, Na Wang, Yong Xia and Jing Zou
Symmetry 2025, 17(3), 373; https://doi.org/10.3390/sym17030373 - 28 Feb 2025
Viewed by 179
Abstract
The stable rotation of young pulsars is often interrupted by two non-deterministic phenomena: glitches and red timing noise. Timing noise provides insights into plasma and nuclear physics under extreme conditions. The framework leverages rotational symmetry in pulsar spin-down models and temporal symmetry in [...] Read more.
The stable rotation of young pulsars is often interrupted by two non-deterministic phenomena: glitches and red timing noise. Timing noise provides insights into plasma and nuclear physics under extreme conditions. The framework leverages rotational symmetry in pulsar spin-down models and temporal symmetry in noise processes to achieve computational efficiency, aligning with the journal’s focus on symmetry principles in physical systems. In this paper, we apply a novel frequentist framework developed within the PINT software package (v0.9.8) to analyze single-pulsar noise processes. Using 17.5 years of pulse time-of-arrival (TOA) data for the young pulsar PSR J1741—3016, observed with the Nanshan 26 m radio telescope, we investigate its timing properties. In this study, we employed the Downhill Weighted Least-Squares Fitter to estimate the pulsar’s spin parameters and position. The Akaike Information Criterion (AIC) was used for model parameter selection. The results obtained with PINT were compared to those from ENTERPRISE and TEMPONEST, two Bayesian-based frameworks. We demonstrate that PINT achieves comparable results with significantly reduced computational costs. Additionally, the adequacy of the noise model can be readily verified through visual inspection tools. Future research will utilize this framework to analyze timing noise across a large sample of young pulsars. Full article
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<p>J1741—3016 pre-fit timing residual.</p>
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<p>Variation in the Adjusted Akaike Information Criterion (AIC − AIC<sub>min</sub> + 1) as a function of the number of harmonics used in the model.</p>
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<p>Harmonic parameter estimation results for red noise and power-law fit analysis. The upper panel shows the estimates of the Fourier coefficients derived using the WaveX model with 16 harmonics, as determined by the minimum AIC difference. The vertical dashed line in both panels marks the reference frequency of <math display="inline"><semantics> <mrow> <mn>1</mn> <mspace width="0.166667em"/> <msup> <mi>year</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, and the horizontal dashed line in the upper panel indicates the zero-amplitude baseline. The lower panel presents the best-fit power-law model applied to these coefficients.</p>
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<p>J1741—3016 post-fit timing residuals.</p>
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<p>Comparison of white noise parameter corner plots from two different sampling methods: (<b>a</b>) ENTERPRISE and (<b>b</b>) TEMPONEST. The orange crosshairs indicate the PINT-derived values. The intersection coordinates correspond to the best-fit parameters obtained using the frequentist approach in PINT.</p>
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<p>Comparison of power law spectral parameters using different methods: (<b>a</b>) PINT and ENTERPRISE and (<b>b</b>) PINT and TEMPONEST. The intersecting orange lines mark PINT-derived estimates, providing direct comparison with Bayesian posterior distributions.</p>
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15 pages, 4116 KiB  
Article
Oxidative Stability of Sunflower Oil: Effect of Blending with an Oil Extracted from Myrtle Liqueur By-Product
by Daniele Sanna and Angela Fadda
Antioxidants 2025, 14(3), 300; https://doi.org/10.3390/antiox14030300 - 28 Feb 2025
Viewed by 154
Abstract
Myrtle oil extracted from the spent berries of myrtle liqueur production, using 2-methyltetrahydrofuran, was used to increase the oxidative stability of sunflower oil (SFO). Three blending ratios (5%, 10%, and 15% w/w) and the SFO without any addition were subjected [...] Read more.
Myrtle oil extracted from the spent berries of myrtle liqueur production, using 2-methyltetrahydrofuran, was used to increase the oxidative stability of sunflower oil (SFO). Three blending ratios (5%, 10%, and 15% w/w) and the SFO without any addition were subjected to forced aging conditions at 70 °C for 21 days. The changes in peroxide value (PV), p-anisidine value (AV), total oxidation value (totox), and conjugated dienes and trienes were evaluated during forced aging. The oxidative stability of the blends was also assessed by the spin trapping method coupled with Electron Paramagnetic Resonance spectroscopy. Myrtle oil at 5% provided the best results, increasing the oxidative stability of SFO by reducing the PV and slowing the onset of secondary oxidation products, as measured by the AV and conjugated trienes. The 15% blend, despite its high levels of PV, AV, conjugated dienes, and trienes during storage, protects SFO from oxidation. The blends of SFO with unconventional oils, like myrtle oil, could represent a sustainable approach to increase its oxidative stability during storage. Full article
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<p>Peroxide values (meq. O<sub>2</sub>/kg) measured for SFO and its blends (5, 10, and 15%) with MSO extracted with 2-MeTHF during storage at 70 °C for 21 days. <span class="html-fig-inline" id="antioxidants-14-00300-i001"><img alt="Antioxidants 14 00300 i001" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i001.png"/></span> SFO; <span class="html-fig-inline" id="antioxidants-14-00300-i002"><img alt="Antioxidants 14 00300 i002" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i002.png"/></span> blend 5%; <span class="html-fig-inline" id="antioxidants-14-00300-i003"><img alt="Antioxidants 14 00300 i003" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i003.png"/></span> blend 10%; <span class="html-fig-inline" id="antioxidants-14-00300-i004"><img alt="Antioxidants 14 00300 i004" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i004.png"/></span> blend 15%. In the inset table: capital letters in red deal with the comparison between times inside the same blend; lowercase letters deal with the comparison between blends inside the same storage time. Mean differences were calculated according to Tukey’s test (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>K232 and K268 values measured for SFO and its blends (5, 10, and 15%) with MSO extracted with 2-MeTHF during storage at 70 °C for 21 days. <span class="html-fig-inline" id="antioxidants-14-00300-i001"><img alt="Antioxidants 14 00300 i001" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i001.png"/></span> SFO; <span class="html-fig-inline" id="antioxidants-14-00300-i002"><img alt="Antioxidants 14 00300 i002" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i002.png"/></span> blend 5%; <span class="html-fig-inline" id="antioxidants-14-00300-i003"><img alt="Antioxidants 14 00300 i003" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i003.png"/></span> blend 10%; <span class="html-fig-inline" id="antioxidants-14-00300-i004"><img alt="Antioxidants 14 00300 i004" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i004.png"/></span> blend 15%. In the inset table: capital letters in red deal with the comparison between times inside the same blend; lowercase letters deal with the comparison between blends inside the same storage time. Mean differences were calculated according to Tukey’s test (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>The p-Anisidine values measured for SFO and its blends (5, 10, and 15%) with MSO extracted with 2-MeTHF during storage at 70 °C for 21 days. <span class="html-fig-inline" id="antioxidants-14-00300-i001"><img alt="Antioxidants 14 00300 i001" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i001.png"/></span> SFO; <span class="html-fig-inline" id="antioxidants-14-00300-i002"><img alt="Antioxidants 14 00300 i002" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i002.png"/></span> blend 5%; <span class="html-fig-inline" id="antioxidants-14-00300-i003"><img alt="Antioxidants 14 00300 i003" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i003.png"/></span> blend 10%; <span class="html-fig-inline" id="antioxidants-14-00300-i004"><img alt="Antioxidants 14 00300 i004" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i004.png"/></span> blend 15%. In the inset table: capital letters in red deal with the comparison between times inside the same blend; lowercase letters deal with the comparison between blends inside the same storage time. Mean differences were calculated according to Tukey’s test (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Totox values calculated for SFO and its blends (5, 10 and 15%) with MSO extracted with 2-MeTHF during storage at 70 °C for 21 days. <span class="html-fig-inline" id="antioxidants-14-00300-i001"><img alt="Antioxidants 14 00300 i001" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i001.png"/></span> SFO; <span class="html-fig-inline" id="antioxidants-14-00300-i002"><img alt="Antioxidants 14 00300 i002" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i002.png"/></span> blend 5%; <span class="html-fig-inline" id="antioxidants-14-00300-i003"><img alt="Antioxidants 14 00300 i003" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i003.png"/></span> blend 10%; <span class="html-fig-inline" id="antioxidants-14-00300-i004"><img alt="Antioxidants 14 00300 i004" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i004.png"/></span> blend 15%. In the inset table: capital letters in red deal with the comparison between times inside the same blend; lowercase letters deal with the comparison between blends inside the same storage time. Mean differences were calculated according to Tukey’s test (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Evolution of PBN adduct intensity over time in in SFO (black line) and its blends at 5% (blue line), 10% (green line), and 15% (red line) with MSO extracted with 2-MeTHF during storage at 70 °C for 0 days (<b>A</b>), 2 days (<b>B</b>), 4 days (<b>C</b>), 7 days (<b>D</b>), 14 days (<b>E</b>), and 21 days (<b>F</b>).</p>
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<p>AUC values calculated for sunflower oil and its blends (5, 10, and 15%) with MSO extracted with 2-MeTHF during storage at 70 °C for 21 days. <span class="html-fig-inline" id="antioxidants-14-00300-i001"><img alt="Antioxidants 14 00300 i001" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i001.png"/></span> SFO; <span class="html-fig-inline" id="antioxidants-14-00300-i002"><img alt="Antioxidants 14 00300 i002" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i002.png"/></span> blend 5%; <span class="html-fig-inline" id="antioxidants-14-00300-i003"><img alt="Antioxidants 14 00300 i003" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i003.png"/></span>blend 10%; <span class="html-fig-inline" id="antioxidants-14-00300-i004"><img alt="Antioxidants 14 00300 i004" src="/antioxidants/antioxidants-14-00300/article_deploy/html/images/antioxidants-14-00300-i004.png"/></span> blend 15%. In the inset table: capital letters in red deal with the comparison between times inside the same blend; lowercase letters deal with the comparison between blends inside the same storage time. Mean differences were calculated according to Tukey’s test (<span class="html-italic">p</span> ≤ 0.05).</p>
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9 pages, 2404 KiB  
Article
PLD Growth of Ferrimagnetic Tm3Fe5O12 Thin Film with Perpendicular Magnetic Anisotropy on GGG
by Zezhong Li, Xin Wang, Yinan Xiao, Yuxiao Zou, Donghui Wang, Huaiwen Yang, Hui Zhang, Yunliang Li and Ying Liu
Crystals 2025, 15(3), 234; https://doi.org/10.3390/cryst15030234 - 28 Feb 2025
Viewed by 100
Abstract
Thulium Iron Garnet (TIG), as an emerging hotspot in rare-earth iron garnet systems, possesses a large magnetostriction constant (λ111) and a low damping coefficient. Therefore, it is possible to induce perpendicular magnetic anisotropy (PMA) through stress, which makes it more desirable [...] Read more.
Thulium Iron Garnet (TIG), as an emerging hotspot in rare-earth iron garnet systems, possesses a large magnetostriction constant (λ111) and a low damping coefficient. Therefore, it is possible to induce perpendicular magnetic anisotropy (PMA) through stress, which makes it more desirable for interfacial magnetic proximity or spin–orbit torque effects than Yttrium Iron Garnet (YIG). For achieving a high-quality TIG thin film and regulating its properties accordingly, understanding the effect of growth parameters on the film properties is essential. Using the Pulsed Laser Deposition (PLD) technique, we prepared TIG film on a Gadolinium Gallium Garnet (GGG) substrate. The correlations of its structural properties to the growth conditions are systematically studied, including the oxygen pressure and laser energy. With the annealing, a ferrimagnetic TIG thin film with PMA is successfully obtained. Our work provides a platform for achieving high-quality TIG thin films by experimentally regulating the growth factors. Full article
(This article belongs to the Section Crystalline Metals and Alloys)
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<p>XRD results of the films at different oxygen pressures. (<b>a</b>) 0.05 Torr, (<b>b</b>) 0.07 Torr, (<b>c</b>) 0.10 Torr, (<b>d</b>) 0.15 Torr, (<b>e</b>) 0.20 Torr. And (<b>f</b>) Tm/Fe ratios of the films at different oxygen pressures.</p>
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<p>XRD results of the films at different laser energies.</p>
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<p>MOKE results for samples annealed at different times; (<b>a</b>) 0 min, (<b>b</b>) 10 min, (<b>c</b>) 30 min, (<b>d</b>) 60 min.</p>
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<p>(<b>a</b>) XRD results of TIG films with different annealing times. The dashed line denotes the peak position of the bulk TIG. (<b>b</b>) Tm/Fe ratios of the films with different annealing times. (<b>c</b>) M-H curves of TIG film.</p>
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20 pages, 17376 KiB  
Article
Carbonization of N/P Co-Doped Resin for Metal-Free Catalytic Ozonation of Oxalic Acid
by Yixiong Pang, Yu Pan, Lingjun Kong, Zenghui Diao and Bin Li
Water 2025, 17(5), 710; https://doi.org/10.3390/w17050710 - 28 Feb 2025
Viewed by 151
Abstract
In this study, a millimeter-scale N/P-doped carbonaceous catalyst was synthesized via facile carbonization of the N/P-doped resin at 800 °C (NPCR-800). This work aimed to investigate the performance of the NPCR-800 catalyst in heterogeneous catalytic ozonation and the mechanism of reactive oxygen species [...] Read more.
In this study, a millimeter-scale N/P-doped carbonaceous catalyst was synthesized via facile carbonization of the N/P-doped resin at 800 °C (NPCR-800). This work aimed to investigate the performance of the NPCR-800 catalyst in heterogeneous catalytic ozonation and the mechanism of reactive oxygen species (ROS) generation. The NPCR-800 achieved the highest oxalic acid (OA) degradation efficiency of 91% within 40 min. The first-order kinetics of OA degradation in the NPCR-800/O3 system was approximately twelve and three times higher than that in the O3 and O3/GAC system, respectively. In addition to excellent catalytic ozonation performance, the NPCR catalyst also exhibited good reusability and salt tolerance. The dominant ROS were identified by the electronic spin response and free radical quantitative experiments, being responsible for oxalic acid degradation in NPCR-800/O3 system. The effect of the doped N and P elements on enhancing the catalytic activity was understood, what was ascribed to the efficient reaction of the O3 molecule with the active site of the graphitic N, defect site and carbonyl/carboxyl groups of NPCR to generate the hydroxyl radical and singlet oxygen. A type of metal-free catalytic ozonation strategy was developed in this work, which is promising in the practical treatment of the refractory organic pollutants. Full article
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<p>SEM and EDS mapping images of C, N, O, and P elements (<b>a</b>–<b>e</b>), and EDS spectrum (<b>f</b>) of NPCR-800 (inserted table shows the content analysis of various elements), XRD patterns (<b>g</b>), and Raman spectrum (<b>h</b>) of NPCR catalysts.</p>
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<p>Deconvoluted C 1s XPS spectra of NPCR-600 (<b>a</b>), NPCR-700 (<b>b</b>), NPCR-800 (<b>c</b>); deconvoluted N 1s XPS spectra of NPCR-600 (<b>d</b>), NPCR-700 (<b>e</b>), NPCR-800 (<b>f</b>); deconvoluted P 2p XPS spectra of NPCR-600 (<b>g</b>), NPCR-700 (<b>h</b>), NPCR-800 (<b>i</b>).</p>
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<p>The effect of calcination temperature on OA degradation (<b>a</b>) and <span class="html-italic">k</span><sub>obs</sub> (<b>b</b>) in the NPCR catalytic oxidation system. OA degradation (<b>c</b>) and <span class="html-italic">k</span><sub>obs</sub> (<b>d</b>) for different systems. Conditions: [OA] = 150 mg/L, [catalyst] (if used) = 0.5 g/L, gaseous [O<sub>3</sub>] = 60 mg/L, O<sub>3</sub> flow rate = 100 mL/min, initial pH = 2.8.</p>
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<p>The effect of ozone dosage (<b>a</b>), catalyst dosage (<b>b</b>), initial pH (<b>c</b>), common anions (<b>d</b>) and cycle runs (<b>e</b>) on OA degradation in NPCR-800 catalytic oxidation system. Conditions (unless otherwise noted): [OA] = 150 mg/L, [catalyst] = 0.5 g/L, gaseous [O<sub>3</sub>] = 60 mg/L, O<sub>3</sub> flow rate = 100 mL/min, initial pH (without adjustment) = 2.8.</p>
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<p>EPR spectra of DMPO as a spin trap in DI water (<b>a</b>) and anhydrous methanol (<b>b</b>), EPR spectra of TEMP as a spin trap in DI water (<b>c</b>) and the quantitative detection (<b>d</b>) of •OH and •O<sub>2</sub><sup>−</sup> during catalytic ozonation with NPCR-800. Conditions: [Catalyst] = 0.5 g/L, dissolved [O<sub>3</sub>] ≈ 15 mg/L, initial pH (for ROS quantitative detection test) = 2.8.</p>
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<p>Linear fit between relative amount of surface C=O/COOH groups (<b>a</b>), defects (I<sub>D</sub>/I<sub>G</sub>) (<b>b</b>), graphitic N (<b>c</b>), pyrrolic N (<b>d</b>), pyridinic N (<b>e</b>) and reaction rate constant <span class="html-italic">k</span><sub>obs</sub>.</p>
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<p>Possible pathways of ozone activation by NPCR.</p>
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14 pages, 2076 KiB  
Article
Roles of Water Molecules in the Structures and Magnetic Properties of Coordination Polymers with a Dicarboxylate Ligand
by Dehui Zong, En-Qing Gao and Dawei Zhang
Materials 2025, 18(5), 1089; https://doi.org/10.3390/ma18051089 - 28 Feb 2025
Viewed by 107
Abstract
Three new coordination polymers, {[M(nbpdc)(DMF)(H2O)2]·H2O} (M = Co and Ni) and [Zn(nbpdc)(DMF)(H2O)], were synthesized from 2-nitrobiphenyl-4,4′-dicarboxylate (nbpdc2−). The isomorphous Co(II) and Ni(II) compounds exhibited a two-dimensional coordination network in which [...] Read more.
Three new coordination polymers, {[M(nbpdc)(DMF)(H2O)2]·H2O} (M = Co and Ni) and [Zn(nbpdc)(DMF)(H2O)], were synthesized from 2-nitrobiphenyl-4,4′-dicarboxylate (nbpdc2−). The isomorphous Co(II) and Ni(II) compounds exhibited a two-dimensional coordination network in which the chains with single-water bridges and the chains with single-nbpdc2− bridges intersected each other by sharing the metal ions. The coordination networks were connected with uncoordinated water molecules through hydrogen bonds. The rarely identified single-water-bridged coordination chain was reinforced by water-based intrachain hydrogen bonds. The single-water bridges mediated modest antiferromagnetic superexchange in both Co(II) and Ni(II) compounds and afforded a spin-canting structure for the Co(II) compound at low temperatures. Water molecules played a distinct structural role in the Zn(II) compound, which was a one-dimensional coordination polymer with single-nbpdc2− bridges. Instead of bridging metal ions, each water molecule was coordinated to one metal ion and hydrogen-bonded to the coordination spheres of other two metal ions, resulting to an infinite ladderlike hydrogen-bonding motif. The ladders interlinked the nbpdc-bridged chains into a three-dimensional supramolecular architecture featuring the 5-conneted {44.64} net. Full article
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Figure 1
<p>PXRD profiles of <b>1</b>–<b>3</b> compared with those simulated from the crystal data of <b>1</b> and <b>2</b>.</p>
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<p>Crystal structure of <b>1</b>. (<b>a</b>) A view of the coordination chain formed from Zn(II) and nbpdc<sup>2−</sup> (ellipsoidal probability: 50%). The hydrogen atoms of nbpdc<sup>2−</sup> and DMF have been omitted for clarity. (<b>b</b>) The hydrogen-bonded ladderlike motif. (<b>c</b>) A view showing the stacking of the coordination chains through hydrogen bonds. The non-oxygen atoms of DMF and the nitro groups and hydrogen atoms of nbpdc<sup>2−</sup> have been omitted for clarity. (<b>d</b>) A topologic representation of the 3D structure composed of coordination chains (red) and hydrogen-bonded ladders (blue).</p>
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<p>Crystal structure of <b>2</b>. (<b>a</b>) A view of the coordination modes of Co(II) and nbpdc<sup>2−</sup> (ellipsoidal probability: 50%). The nitro group disordered over two positions is shown in light color and the hydrogen atoms of nbpdc<sup>2−</sup> and DMF have been omitted for clarity. (<b>b</b>) A water-bridged chain assisted with hydrogen bonds. (<b>c</b>) A 2D coordination layer. The non-oxygen atoms of DMF and the nitro groups and hydrogen atoms of nbpdc<sup>2−</sup> have been omitted for clarity. (<b>d</b>) A view of the layer packing showing interlayer hydrogen bonding. The hydrogen atoms of nbpdc<sup>2−</sup> and DMF have been omitted for clarity.</p>
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<p>(<b>a</b>) Temperature dependence of χ and χT of <b>2</b> under 1 kOe. The black and red solid lines both represent the best fit to Equation (1) in the text. (<b>b</b>) Isothermal magnetization of <b>2</b> at 2 K. (<b>c</b>) FC and ZFC susceptibility of <b>2</b> under different field. (<b>d</b>) <span class="html-italic">χ</span>′(<span class="html-italic">T</span>) and <span class="html-italic">χ</span>″(<span class="html-italic">T</span>) plots for <b>2</b> at frequencies 10–1000 Hz with <span class="html-italic">H</span><sub>dc</sub> = 0 and H<sub>ac</sub> = 3.5 Oe.</p>
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<p>Temperature dependence of <span class="html-italic">χ</span> and <span class="html-italic">χT</span> for <b>3</b> under 1 kOe. Both solid lines represent the best fit to Equation (2) in the text.</p>
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21 pages, 3255 KiB  
Article
Assessing the Modulatory Effects of tDCS and Acupuncture on Cerebral Blood Flow in Chronic Low Back Pain Using Arterial Spin Labeling Perfusion Imaging
by Valeria Sacca, Nasim Maleki, Sveta Reddy, Sierra Hodges and Jian Kong
Brain Sci. 2025, 15(3), 261; https://doi.org/10.3390/brainsci15030261 - 28 Feb 2025
Viewed by 164
Abstract
Background: Both transcranial direct current stimulation (tDCS) and acupuncture are promising methods for managing chronic low back pain (cLBP), however, their underlying mechanisms remain unclear. Methods: To explore the neural mechanisms of tDCS and acupuncture on cLBP, we examined how real and sham [...] Read more.
Background: Both transcranial direct current stimulation (tDCS) and acupuncture are promising methods for managing chronic low back pain (cLBP), however, their underlying mechanisms remain unclear. Methods: To explore the neural mechanisms of tDCS and acupuncture on cLBP, we examined how real and sham tDCS applied to the bilateral motor cortex (M1), combined with real or sham acupuncture, influenced cerebral blood flow (CBF) using pulsed continuous arterial spin labeling (pCASL) imaging. tDCS was administered over six sessions, combined with real or sham acupuncture, over one month. Results: Following real tDCS, we observed increased CBF in the bilateral occipital cortex, precuneus, left hippocampus, and parahippocampal gyrus/posterior cingulate cortex. After sham tDCS, CBF decreased in regions including the bilateral superior parietal lobule, precuneus, bilateral precentral and postcentral gyri, and left angular gyrus. Real acupuncture led to reduced CBF in the bilateral occipital cortex and hippocampus, and left posterior cingulate gyrus, and increased CBF in the right postcentral gyrus, superior parietal lobule, and frontal areas. Sham acupuncture was associated with decreased CBF in the bilateral hippocampus and anterior cingulate gyrus. Conclusions: These results suggest both shared and distinct patterns of CBF changes between real and sham tDCS, as well as between real and sham acupuncture, reflecting mode-dependent effects on brain networks involved in pain processing and modulation. Our findings highlight the different neural circuits implicated in the therapeutic mechanisms of tDCS and acupuncture in the management of cLBP. Full article
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<p>(<b>a</b>) Workflow of the experimental procedure. Each participant completed 8 sessions in total. The first and last sessions involved behavioral assessments, where pain intensity was measured using the NRS. Participants underwent two MRI sessions: one before the start of tDCS treatment and another after completing the final treatment session. The treatment phase lasted for 6 sessions over approximately 1 month. (<b>b</b>) High-definition anodal tDCS configuration. Anode electrodes are in orange and return electrodes are in blue. Orange dish line represents the stimulation area.</p>
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<p>Significant CBF clusters found in the statistical analysis of the four different groups. Sham acupuncture and sham tDCS led to a decrease in the left middle frontal gyrus. The real tDCS and sham acupuncture group was associated with decreased CBF in the bilateral occipital cortex. All these brain regions are shown in the circles of the figures.</p>
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<p>CBF changes in real and sham tDCS between pre- and post-treatment. Real tDCS led to decreased CBF after the treatment in the left hippocampus and parahippocampal gyrus, and in the bilateral occipital cortex. In addition, real tDCS was associated with increased CBF after the treatment in the right putamen/caudate/insula. Sham tDCS was associated with decreased CBF in the right precentral/postcentral gyrus, left superior parietal gyrus, left occipital gyrus, and left angular gyrus. All these brain regions are shown in the circles of the figures.</p>
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<p>Comparing pre- and post-treatment differences between the real and sham tDCS groups. The difference highlights regions where the post-treatment minus pre-treatment change in CBF is greater in the real tDCS group compared to the sham group. We found that the real tDCS led to a larger increase in the bilateral anterior cingulate cortex, right putamen/caudate, right insula, right superior parietal lobule, and right occipital cortex. All these brain regions are shown in the circles of the figures.</p>
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<p>Statistical analysis of the CBF changes for the real and sham acupuncture groups. Real acupuncture led to decreased CBF in the bilateral hippocampus and left posterior cingulate cortex (PCC). In addition, increased CBF in the bilateral superior frontal gyrus and right postcentral gyrus were detected. Sham acupuncture was associated with decreased CBF in the bilateral hippocampus, bilateral occipital cortex, bilateral anterior cingulate cortex, and left parietal operculum. All these brain regions are shown in the circles of the figures.</p>
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<p>Comparing pre- and post-treatment differences between the real and sham acupuncture groups. The difference highlights regions where the post-treatment minus pre-treatment change in CBF is greater in the real acupuncture group compared to the sham group. We found that real acupuncture led to a larger increase in the left superior frontal gyrus and bilateral precentral gyrus. All these brain regions are shown in the circles of the figures.</p>
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