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Metal-organic framework (MOF) in biomass valorization is a promising technology developed in recent decades. By tailoring both the metal nodes and organic ligands, MOFs exhibit multiple functionalities, which not only extend their applicability in biomass conversion but also increase the complexity of material designs. To address this issue, quantum mechanical simulations have been used to provide mechanistic insights into the catalysis of biomass-derived molecules, which could potentially facilitate the development of novel MOF-based materials for biomass valorization. The aim of this review is to survey recent quantum mechanical simulations on biomass reactions occurring in MOF catalysts, with the emphasis on the studies of the catalytic activity of active sites and the effects of organic ligand and porous structures on the kinetics. Moreover, different model systems and computational methods used for MOF simulations are also surveyed and discussed in this review.
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http://dx.doi.org/10.1002/asia.202001371 | DOI Listing |
Anal Chem
September 2025
Institute of Biological Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria.
The discovery of solute precursors of crystalline materials, such as biominerals, recently challenged the classical nucleation theory (CNT). One emerging method for investigating these early-stage intermediates in solution is dissolution dynamic nuclear polarization (dDNP)-enhanced nuclear magnetic resonance (NMR) spectroscopy. Recent applications of dDNP to calcium carbonate (CaC) and calcium phosphate (CaP) mineralization have demonstrated the feasibility of identifying and tracing very early-stage prenucleation clusters (PNCs).
View Article and Find Full Text PDFNano Lett
September 2025
Institute of Energy Materials Science, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.
Ampere-level electrocatalytic nitrate reduction to ammonia (eNRA) offers a carbon-neutral alternative to the Haber-Bosch process. However, its energy efficiency is critically hampered by the inherent conflict between the reaction and diffusion. Herein, we propose a reaction-diffusion-coupled strategy implemented on a well-tailored CuCoNiRuPt high-entropy alloy aerogel (HEAA) to simultaneously realize energy barrier homogenization and accelerate mass transport, endowing ampere-level eNRA with a high energy efficiency.
View Article and Find Full Text PDFAcc Chem Res
September 2025
Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Ave. Ferrocarril San Rafael Atlixco 186, Col. Leyes de Reforma 1A sección, Alcaldía Iztapalapa, 09310 Mexico City, Mexico.
ConspectusWhat does the word antioxidant mean? Antioxidants are supposed to be nontoxic, versatile molecules capable of counteracting the damaging effects of oxidative stress (OS). Thus, when evaluating a candidate molecule as an antioxidant, several aspects should be considered. Antioxidants are more than free radical scavengers.
View Article and Find Full Text PDFBiosystems
September 2025
Department of Physics, Razi University, Kermanshah, Iran.
From a physics perspective, DNA and RNA molecules are characterized as dynamic biological structures that exhibit vibrations across a range of time scales. To conduct a more accurate investigation of their dynamic properties, it is essential to consider the environmental conditions surrounding these molecules. A harmonic Hamiltonian that incorporates damping, along with the Green's function method, has been utilized to analyze the vibrational responses of viscous DNA and RNA strands.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
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