Muhammad Junaid, Sajid Karam, Muhammad Iqbal, Mehran Anjum
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引用次数: 0
Abstract
Context: The industrial production of ammonia through the Haber-Bosch process is energy intensive and operates under extreme conditions. In contrast, the catalytic reduction of nitrogen (N₂) to ammonia (NH₃) under mild conditions presents a significant challenge with important implications for sustainable chemistry. This work investigates the potential of Mo-doped carbon nitride (C₄₂N₂₄) fullerene as a catalyst for N₂ reduction. The study reveals that Mo@C₄₂N₂₄ exhibits rapid catalytic activity, with a preference for the enzymatic mechanism for N₂ conversion to NH₃. Notably, H₂ evolution is suppressed, making Mo-doped C₄₂N₂₄ a promising candidate for ammonia synthesis under mild conditions.
Methods: Density functional theory (DFT) calculations were performed using the Perdew-Burke-Ernzerhof (PBE) functional within the generalized gradient approximation (GGA) framework. The DNP basis set was employed in all calculations using the DMol3 code. The Mo atom was incorporated into the N₄ cavity of the carbon nitride structure, with a binding energy of - 2.54 eV. The electronic structure was analyzed through molecular electrostatic potential maps, Hirshfeld charge density analysis, and spin density analysis. Three catalytic pathways, alternating, distal, and enzymatic were studied to understand the reaction mechanism. All calculations were carried out using the DMol3 software package.
期刊介绍:
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.