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Theoretical calculations provide mechanistic insights and an energetic rationale for the pronounced differences in switchability observed. The energetics of linker bending and linker-linker dispersion interactions govern the phase transitions in investigated MOFs.A thin layer of gold nanoparticles (Au NPs) sputtered on cadmium sulfide quantum dots (CdS QDs) decorated anodic titanium dioxide nanotubes (TNTs) (Au/CdS QDs/TNTs) was fabricated and explored for the nonenzymatic detection of cholesterol and hydrogen peroxide (H2O2). Morphological studies of the sensor revealed the formation of uniform nanotubes decorated with a homogeneously dispersed CdS QDs and Au NPs layer. The electrochemical measurements showed an enhanced electrocatalytic performance with a fast electron transfer (∼2 s) between the redox centers of each analyte and electrode surface. The hybrid nanostructure (Au/CdS QDs/TNTs) electrode exhibited about a 6-fold increase in sensitivity for both cholesterol (10,790 μA mM-1 cm-2) and H2O2 (78,833 μA mM-1 cm-2) in analyses compared to the pristine samples. The hybrid electrode utilized different operational potentials for both analytes, which may lead to a voltage-switchable dual-analyte biosensor with a higher selectivity. The biosensor also demonstrated a good reproducibility, thermal stability, and increased shelf life. In addition, the clinical significance of the biosensor was tested for cholesterol and H2O2 in real blood samples, which showed maximum relative standard deviations of 1.8 and 2.3%, respectively. These results indicate that a Au/CdS QDs/TNTs-based hybrid nanostructure is a promising choice for an enzyme-free biosensor due to its suitable band gap alignment and higher electrocatalytic activities.Ethylene production from C2 hydrocarbon mixtures through one separation step is desirable but challenging because of the similar size and physical properties of acetylene, ethylene, and ethane. Herein, we report three new isostructural porous coordination networks (NPU-1, NPU-2, NPU-3; NPU represents Northwestern Polytechnical University) that are sustained by 9-connected nodes based upon a hexanuclear metal cluster of composition [Mn6(μ3-O)2(CH3COO)3]6+. NPU-1/2/3 exhibit a dual cage structure that was systematically fine-tuned in terms of cage size to realize selective adsorption of C2H2 and C2H6 over C2H4. find more Dynamic breakthrough experiments demonstrated that NPU-1 produces ethylene in >99.9% purity from a three-component gas mixture (111 C2H2/C2H4/C2H6). Molecular modeling studies revealed that the dual adsorption preference for C2H2 and C2H6 over C2H4 originates from (a) strong hydrogen-bonding interactions between electronegative carboxylate O atoms and C2H2 molecules in one cage and (b) multiple non-covalent interactions between the organic linkers of the host network and C2H6 molecules in the second cage.Neuroinflammatory cytokines are promising therapeutic targets for the treatment of Alzheimer’s disease. Herein, we described our efforts toward the investigation of cinnamic acid derivatives as antineuroinflammatory agents. Intensive structural modifications led to the identification of compound 4f as the most effective antineuroinflammatory agent in vitro. The oral administration of compound 4f could reverse lipopolysaccharide (LPS)-induced memory disturbance and normalize glucose uptake and metabolism in the brains of mice. Further biological studies in vivo revealed that compound 4f was directly bound to the mitogen-activated protein kinase (MAPK) signaling pathway, resulting in suppression of its downstream signaling pathway by blocking neuroinflammatory progression. Docking studies showed that compound 4f could be inserted into the active pocket of interleukin-1β (IL-1β). Furthermore, it was confirmed that compound 4f formed hydrogen bonds with SER84 to enhance the binding affinity. Taken together, these results are of great importance in the development of cinnamic acid derivatives for the treatment of Alzheimer’s disease.Selective removal or enrichment of targeted solutes including micropollutants, valuable elements, and mineral scalants from complex aqueous matrices is both challenging and pivotal to the success of water purification and resource recovery from unconventional water resources. Membrane separation with precision at the subnanometer or even subangstrom scale is of paramount importance to address those challenges via enabling “fit-for-purpose” water and wastewater treatment. So far, researchers have attempted to develop novel membrane materials with precise and tailored selectivity by tuning membrane structure and chemistry. In this critical review, we first present the environmental challenges and opportunities that necessitate improved solute-solute selectivity in membrane separation. We then discuss the mechanisms and desired membrane properties required for better membrane selectivity. On the basis of the most recent progress reported in the literature, we examine the key principles of material design and fabrication, which create membranes with enhanced and more targeted selectivity. We highlight the important roles of surface engineering, nanotechnology, and molecular-level design in improving membrane selectivity. Finally, we discuss the challenges and prospects of highly selective NF membranes for practical environmental applications, identifying knowledge gaps that will guide future research to promote environmental sustainability through more precise and tunable membrane separation.The development of nanoporous single-layer graphene membranes for gas separation has prompted increasing theoretical investigations of gas transport through graphene nanopores. However, computer simulations and theories that predict gas permeances through individual graphene nanopores are not suitable to describe experimental results, because a realistic graphene membrane contains a large number of nanopores of diverse sizes and shapes. With this need in mind, here, we generate nanopore ensembles in silico by etching carbon atoms away from pristine graphene with different etching times, using a kinetic Monte Carlo algorithm developed by our group for the isomer cataloging problem of graphene nanopores. The permeances of H2, CO2, and CH4 through each nanopore in the ensembles are predicted using transition state theory based on classical all-atomistic force fields. Our findings show that the total gas permeance through a nanopore ensemble is dominated by a small fraction of large nanopores with low energy barriers of pore crossing.