Notes

Epidemic involving osteoporosis and also osteopenia examined by densitometry within Western puerperal females.
Electroreduction of carbon dioxide (CO2RR) has been regarded as a promising approach to realize the production of useful fuels and to decrease greenhouse gas levels simultaneously, where high-efficiency catalysts are required. Herein, we report La2CuO4 nanobamboo (La2CuO4 NBs) perovskite with rich twin boundaries showing a high Faraday efficiency (FE) of 60% toward ethylene (C2H4), whereas bulk La2CuO4 exhibits a FECO of 91%. X-ray absorption spectroscopy (XAS) reveals that the Cu in La2CuO4 NBs is in the Cu2+ state, and no obvious change can be observed during the catalytic process, as monitored by in situ XAS. Density functional theory calculations reveal that the superior FEC2H4 of La2CuO4 NBs originates from the active (113) surfaces with intrinsic strain. selleck products The formation of gap states annihilates the electron transfer barrier of C-C coupling, resulting in the high FEC2H4. This work provides a new perspective for developing efficient perovskite catalysts via grain boundary engineering.We report a facile approach to directly chlorinate graphene from an aqueous sodium chloride solution under ambient conditions. By applying a moderate anodic voltage to substrate-supported monolayer graphene, the resultant chlorine radicals generated at the graphene surface enable efficient chlorination X-ray photoelectron spectrum confirms the formation of C-Cl bonds, and reaction voltage-tunable ClC atomic ratios of up to 17% are achieved. In comparison, we find the corresponding electrochemical graphene bromination and iodination reactions much less viable. Electrical and Raman characterizations show substantial p-doping for the chlorinated graphene, yet good basal-plane integrity and electrical properties are maintained. Interference reflection microscopy and pH-dependent experiments next help elucidate the competition between the radical-mediated electrochemical chlorination and oxidation in the process, and rationalize acidic conditions for optimal chlorination. Reaction in a mixed NaCl-NaN3 solution shows the electrochemical chlorination to be fully suppressed by azidation, yet a sequential, two-step chlorination-azidation approach permits facile bifunctionalization.Although strain engineering is effective in boosting the activities of noble metal catalysts, it remains desirable to construct fully strained catalysts to push the activity to even higher levels. Herein, we report a novel route to strong lattice strains of a Pd-based catalyst by radial growth of a Pd-rich phase on Au-Ag alloy nanowires that are no thicker than 1.5 nm. It creates not only tensile strains in the Pd-rich sheath due to the core-sheath lattice mismatch but also distortion and twinning of the lattice, producing nonhomogeneous local strains as hotspots for the catalysis. Toward the electrochemical oxidation of biomass-derived alcohols including ethanol, ethylene glycol, and glycerol, the highly strained nanowires outperformed their less strained counterparts and reached up to 13.6, 18.2, and 11.1 A mgPd-1, respectively. This strain engineering strategy may open new avenues to highly efficient catalysts for direct alcohol fuel cells and many other applications.Ultrasmall ferrite nanoparticles (UFNPs) have emerged as powerful magnetic resonance imaging (MRI) T1 nanoprobe for noninvasive visualization of biological events. However, the structure-relaxivity relationship and regulatory mechanism of UFNPs remain elusive. Herein, we developed chemically engineered 3.8 nm ZnxFe3-xO4@ZnxMnyFe3-x-yO4 (denoted as ZnxF@ZnxMnyF) nanoparticles with precise dopants control in both crystalline core and disordered shell as a model system to assess the impact of dopants on the relaxometric properties of UFNPs. It is determined that the core-shell dopant architecture allows the optimal tuning of r1 relaxivity for [email protected] up to 20.22 mM-1 s-1, which is 5.2-fold and 6.5-fold larger than that of the original UFNPs and the clinically used Gd-DTPA. Moreover, the high-performing UFNPs nanoprobe, when conjugated with a targeting moiety AMD3100, enables the in vivo MRI detection of small lung metastasis with greatly enhanced sensitivity. Our results pave the way toward the chemical design of ultrasensitive T1 nanoprobe for advanced molecular imaging.In this work, we describe the radiolytic environment experienced by a polymer in water during liquid-cell transmission electron microscopy (LCTEM). We examined the radiolytic environment of aqueous solutions of poly(ethylene glycol) (PEG, 2400 g/mol) in the presence of sensitizing gold nanoparticles (GNPs, 100 nm) or radical scavenging isopropanol (IPA). To quantify polymer damage, we employed post-mortem analysis via matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS). This approach confirms IPA (1-10% w/v) can significantly mitigate radiolysis-induced damage to polymers in water, while GNPs significantly enhance damage. We couple LCTEM experiments with simulations to provide a generalizable strategy for assessing radiolysis mitigation or enhancement. This study highlights the caution required for LCTEM experiments on inorganic nanoparticles where solution phase properties of surrounding organic materials or the solvent itself are under investigation. Furthermore, we anticipate an increased use of scavengers for LCTEM studies of all kinds.Adsorption of gas mixtures is central to adsorption-based gas separations, and the number of adsorbate mixture/adsorbent systems that exist is staggering. Because examples of machine learning (ML) models predicting single-component adsorption of arbitrary molecules in large libraries of crystalline adsorbents have been developed, it is interesting to determine whether these models can accurately predict mixture adsorption. Here, we use molecular simulations to generate mixture adsorption data with a set of 12 near-azeotropic molecules in a diverse set of MOFs. These data provide a challenging example for any method to rapidly predict mixture adsorption in MOFs. We combine a previous ML single-component isotherm model with ideal adsorbed solution theory (IAST) to make predictions that can be compared directly with molecular simulation data for these adsorbed mixtures. This combination of ML and IAST illustrates the scope that is available with these methods, but the accuracy of the resulting predictions is disappointing.
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