The solvent-composition dependence of quenching triplet states of benzophenone (BP) by anisole in acetonitrile-water (ACN-HO) mixtures was investigated by laser flash photolysis over the water mole fraction () increasing from 0 to 0.92. Single exponential decay of BP was observed over the whole composition range. The quenching rate constant consistently increased with the water content but increased far more rapidly with > 0.7. The water-triggered electron-transfer (ET) mechanism was confirmed by a steeply growing quantum yield of the benzophenone ketyl radical anion, escaping back-ET when the partial water volume exceeded the acetonitrile one. The water-content influence on the BP quenching rate was described by a kinetic model accounting for the microheterogeneous structure of the ACN-HO mixtures and the very different solubility of the reactants in the solvent components. According to the model, the ET mechanism occurs at a rate constant of 1.46 × 10 M s and is presumably assisted by the ACN-HO hydrogen-bonding interaction.
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http://dx.doi.org/10.1021/acs.jpcb.0c02635 | DOI Listing |
Vaccines (Basel)
December 2024
Center for Vaccines and Immunology, University of Georgia, Athens, GA 30605, USA.
Standard-of-care influenza vaccines contain antigens that are typically derived from components of wild type (WT) influenza viruses. Often, these antigens elicit strain-specific immune responses and are susceptible to mismatch in seasons where antigenic drift is prevalent. Thanks to advances in viral surveillance and sequencing, influenza vaccine antigens can now be optimized using computationally derived methodologies and algorithms to enhance their immunogenicity.
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November 2024
Institute of Experimental Medicine, Saint Petersburg 197022, Russia.
Background/objectives: Influenza viruses and SARS-CoV-2 are currently cocirculating with similar seasonality, and both pathogens are characterized by a high mutational rate which results in reduced vaccine effectiveness and thus requires regular updating of vaccine compositions. Vaccine formulations combining seasonal influenza and SARS-CoV-2 strains can be considered promising and cost-effective tools for protection against both infections.
Methods: We used a licensed seasonal trivalent live attenuated influenza vaccine (3×LAIV) as a basis for the development of a modified 3×LAIV/CoV-2 vaccine, where H1N1 and H3N2 LAIV strains encoded an immunogenic cassette enriched with conserved T-cell epitopes of SARS-CoV-2, whereas a B/Victoria lineage LAIV strain was unmodified.
Sensors (Basel)
December 2024
Faculty of Engineering Science, University of Bayreuth, 95440 Bayreuth, Germany.
Molding sand mixtures in the foundry industry are typically composed of fresh and reclaimed sands, water, and additives such as bentonite. Optimizing the control of these mixtures and the recycling of used sand after casting requires an efficient in-line monitoring method, which is currently unavailable. This study explores the potential of an AI-enhanced electrical impedance spectroscopy (EIS) system as a solution.
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December 2024
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
(1) Background: Ultra-high dose rate (UHDR) radiation therapy needs a reliable dosimetry solution and scintillation detectors are promising candidates. In this study, we characterized an inorganic powder-based scintillation detector under a 9 MeV UHDR electron beam. (2) Methods: A mixture of ZnS:Ag powder and optic glue was coupled to an 8 m Eska GH-4001-P polymethyl methacrylate (PMMA) optical fiber.
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December 2024
The State Key Laboratory for the Safety, Long-Life, Health Operation and Maintenance of Long-Span Bridges, Jiangsu Provincial Institute of Traffic Science (JSTI Group), Nanjing 210098, China.
The strain data acquired from structural health monitoring (SHM) systems of large-span bridges are often contaminated by a mixture of temperature-induced and vehicle-induced strain components, thereby complicating the assessment of bridge health. Existing approaches for isolating temperature-induced strains predominantly rely on statistical temperature-strain models, which can be significantly influenced by arbitrarily chosen parameters, thereby undermining the accuracy of the results. Additionally, signal processing techniques, including empirical mode decomposition (EMD) and others, frequently yield unstable outcomes when confronted with nonlinear strain signals.
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