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Thermodynamic analysis of the effect of palm stearin on fully hydrogenated soybean oil coatings in granular micronutrient premixes.
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February 2025
Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada.
This study examined the phase behaviour and temperature-dependent viscosity of palm stearin and fully hydrogenated soybean oil (FHSBO) mixtures to understand the stability of FHSBO coatings on micronutrient premixes. The Hildebrand equation showed that palm stearin/FHSBO mixtures form liquid solutions, while DSC data indicated partial immiscibility in the solid phase. The melting temperatures and enthalpies of fusion are composition dependent, ranging from 67 °C and 138 J/g for 100 % FHSBO to 13 °C and 71 J/g for 100 % palm stearin.
View Article and Find Full Text PDFAuCu bimetallic nanocluster-modified titania nanotubes for photoelectrochemical water splitting: composition-dependent atomic arrangement and activity.
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Quantum Solid-State Physics, Department of Physics and Astronomy, KU Leuven, Belgium.
The photoelectrochemical (PEC) water splitting reaction of bimetallic AuCu ( = 1, 0.75, 0.5, 0.
View Article and Find Full Text PDFActive Site Customizing of Metal-Organic Materials for Highly Efficient Oxygen Evolution.
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Key Laboratory of Inorganic Molecule-Based Chemistry of Liaoning Province, Shenyang University of Chemical Technology, Shenyang, 110142, China.
Elucidating the correlation of active sites and catalytic activity in multi-component metal-organic frameworks (MOFs) is key to understanding the mechanism of oxygen evolution reaction (OER), yet it remains nebulous. Herein, a direct pathway combining theoretical prediction with anchoring high-valence metals is proposed on MOFs to reveal the mechanism of the OER reaction. Density functional theory (DFT) predicts that the co-modulation by Mo and Co atoms can enhance the conductance of CoMOF and optimize the adsorption-free energies of the OER intermediates.
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Process Systems Engineering (AVT.SVT), RWTH Aachen University Forckenbeckstraße 51 52074 Aachen Germany
We propose excess Gibbs free energy graph neural networks (GE-GNNs) for predicting composition-dependent activity coefficients of binary mixtures. The GE-GNN architecture ensures thermodynamic consistency by predicting the molar excess Gibbs free energy and using thermodynamic relations to obtain activity coefficients. As these are differential, automatic differentiation is applied to learn the activity coefficients in an end-to-end manner.
View Article and Find Full Text PDFSemi-quantitative chemometric models for characterization of mixtures of sugars using infrared spectral data.
Spectrochim Acta A Mol Biomol Spectrosc
February 2025
CQC-IMS, Department of Chemistry, University of Coimbra, 3004-535 Coimbra, Portugal; Faculty of Sciences and Letters, Department of Physics, Istanbul Kultur University, Ataköy Campus, Bakirköy 34156, Istanbul, Turkey.
Sugars (saccharides) are sweet-tasting carbohydrates that are abundant in foods and play very important roles in living organisms, particularly as sources and stores of energy, and as structural elements in cellular membranes. They are desirable therapeutic targets, as they participate in multiple metabolic processes as fundamental elements. However, the physicochemical characterization of sugars is a challenging task, mostly due to the structural similarity shared by the large diversity of compounds of this family.
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