Screened d‐p Orbital Hybridization in Turing Structure of Confined Nickel for Sulfion Oxidation Accelerated Hydrogen Production
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The sulfion oxidation reaction (SOR) could offer an energy‐efficient and tech‐economically favorable alternative to the oxygen evolution reaction (OER) for H2 production. Transition metal (TM) based catalysts have been considered promising candidates for SOR but suffer from limited activity due to the excessive bond strength from TM‐S2‐ d‐p orbit coupling. Herein, we propose a feasible strategy of screening direct d‐p orbit hybridization between TM and S2‐ by constructing the Turing structure composed of lamellar stacking carbon‐confined nickel nanosheets. The optimized p‐p orbit coupling between electron‐injected carbon and S2‐ enables exceptional catalytic activity and stability for sulfion degradation and energy‐efficient yet value‐added H2 production. Specifically, it achieves a current density of 500 mA cm‐2 at an ultralow potential of 0.67 V vs. RHE for alkaline SOR. Theoretical calculations indicate that the electron transfer from Ni imparts metallicity and a higher p‐band center to carbon shells, thereby contributing to optimized p‐p orbit hybridization and a thermodynamically favorable stepwise sulfion degradation. Practically, a two‐electrode flow cell achieves an industrial current density of 1 Acm‐2 at an unprecedented low voltage of 0.91 V while maintaining stability for over 300 hours, and exhibits high productivities of 3.83 and 0.32 kgh‐1m‐2 for sulfur and H2, respectively.Keywords:
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The stacking of layers forming three-dimensional periodic structures is explored in the general case, where neither the layers nor the stacking need to be close-packed, and the connectivity number for the system may be either two or four. Procedures are described whereby all possible stacking variants can be systematically derived for a given number of layers, and for a given number of possible stacking positions. The latter depends on the structure of the layer and on the stacking vector.
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As an extension of Table 7.1.5B of International Tables for X-ray Crystallography [(1967), Vol. II. Birmingham: Kynoch Press], the possible stacking variants up to ten layers are arranged according to the percentage of hexagonal stacking. A method is given which allows one to calculate the number of possible stacking variants for any number of layers.
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Abstract Martensitic and massive phases containing fine lamellae of two different close‐packed structures have been studied by transmission electron microscopy. The stacking sequences involved in the lamellar mixtures are ABCBCACAB and ABC, or AB and ABC, or ABC and CBA. The fine lamellae produce fringe patterns which are similar to fringe patterns due to single stacking faults. However, by tilting the foil images can be obtained that are incompatible with single stacking faults.
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Predicting the strength of stacking interactions involving heterocycles is vital for several fields, including structure-based drug design. While quantum chemical computations can provide accurate stacking interaction energies, these come at a steep computational cost. To address this challenge, we recently developed quantitative predictive models of stacking interactions between drug-like heterocycles and the aromatic amino acids Phe, Tyr, and Trp (DOI: 10.26434/chemrxiv.7628939.v4). These models depend on heterocycle descriptors derived from electrostatic potentials (ESPs) computed using density functional theory and provide accurate stacking interactions without the need for expensive computations on stacked dimers. Herein, we show that these ESP-based descriptors can be reliably evaluated directly from the atom connectivity of the heterocycle, providing a means of predicting both the descriptors and the potential for a given heterocycle to engage in stacking interactions without resorting to any quantum chemical computations. This enables the conversion of simple molecular representations ( e.g . SMILES) directly into accurate stacking interaction energies using a freely-available online tool, thereby providing a way to rapidly rank the stacking abilities of large sets of heterocycles.
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It is important to control the lamellar spacing of fully la mellar TiAl alloy for improving its mechanical properties. The factors affecting the lamellar spacing of fully lamellar TiAl alloy and the dependence of the lam ellar spacing on the factors were investigated by means of OM and TEM. The resul ts show that the lamellar spacing depends on cooling rate and Al content. The la mellar spacing is inversely proportional to cooling rate and increases with the increase of Al content. At the same time, a theoretical expression of the lamell ar spacing of fully lamellar TiAl alloy during continuous cooling has been deriv ed on the basis of the ledge mechanism of lamellae growth. The theoretical resul ts are in agreement with the experimental findings.
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Stacking vs thickness: Stacking between the metal–organic layers (MOLs) of MOFs determines their thickness: the higher the stacking, the higher the thickness. This thickness plays an important role in controlling the function of the material, hence, regulating the stacking in 2D nano-MOFs might be very important. We tuned the stacking by modulating the chemical structure of the organic linkers in a series of isostructural MOFs. AFM, XRPD, FESEM, etc. showed the chemical functionality of the linkers to play a pivotal role in modulating stacking efficiency. Such an approach might open a new avenue in controlling the thickness of 2D materials. More information can be found in the Research Article by B. Manna, S. Ida et al. (DOI: 10.1002/chem.202201665).
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<p>Predicting the strength of stacking interactions involving heterocycles is vital for several fields, including structure-based drug design. While quantum chemical computations can provide accurate stacking interaction energies, these come at a steep computational cost. To address this challenge, we recently developed quantitative predictive models of stacking interactions between drug-like heterocycles and the aromatic amino acids Phe, Tyr, and Trp (DOI: 10.26434/chemrxiv.7628939.v4). These models depend on heterocycle descriptors derived from electrostatic potentials (ESPs) computed using density functional theory and provide accurate stacking interactions without the need for expensive computations on stacked dimers. Herein, we show that these ESP-based descriptors can be reliably evaluated directly from the atom connectivity of the heterocycle, providing a means of predicting both the descriptors and the potential for a given heterocycle to engage in stacking interactions without resorting to any quantum chemical computations. This enables the conversion of simple molecular representations (<i>e.g</i>. SMILES) directly into accurate<i> </i>stacking interaction energies using a freely-available online tool, thereby providing a way to rapidly rank the stacking abilities of large sets of heterocycles.</p> <p> </p>
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Stacking vs thickness: Stacking between the metal–organic layers (MOLs) of MOFs determines their thickness: the higher the stacking, the higher the thickness. This thickness plays an important role in controlling the function of the material, hence, regulating the stacking in 2D nano-MOFs might be very important. We tuned the stacking by modulating the chemical structure of the organic linkers in a series of isostructural MOFs. AFM, XRPD, FESEM, etc. showed the chemical functionality of the linkers to play a pivotal role in modulating stacking efficiency. Such an approach might open a new avenue in controlling the thickness of 2D materials. More information can be found in the Research Article by B. Manna, S. Ida et al. (DOI: 10.1002/chem.202201665).
Isostructural
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As an extension of Table 7.1.5B of International Tables for X-ray Crystallography [(1967), Vol. II. Birmingham: Kynoch Press], the possible stacking variants up to ten layers are arranged according to the percentage of hexagonal stacking. A method is given which allows one to calculate the number of possible stacking variants for any number of layers.
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