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引用次数: 0
摘要
研究了新型烷氧二氨基膦-金属(ADAP-M, M = Cu, Ag, Au)配合物在[3 + 2]环加成(32CA)反应中的催化潜力,特别是对金属辅助叠氮-炔环加成(MAAC)合成1,2,3-三唑的催化潜力。利用密度泛函理论(DFT)评价了这些配合物的电子和结构性质,以确定它们的催化效率。ADAP配体对于降低活化能和稳定中间体,从而增强催化作用至关重要。该研究比较了单核和双核途径,发现ADAP-Cu配合物,特别是双核形式的配合物,由于铜的协同相互作用,具有最有利的能量分布和显著的势垒降低。相比之下,银和金的ADAP配合物表现出较高的活化能和较低的效率。还考察了溶剂的作用,发现甲苯增加了金属催化反应中的能垒。这些发现强调了铜基ADAP配合物优越的催化效率和溶剂选择对反应动力学的影响,为有机合成中先进的催化体系设计提供了见解。
Assessing the Catalytic Potential of Novel ADAP-M (M = Cu, Ag, Au) Catalysts in [3 + 2] Cycloaddition Reactions
This study investigated the catalytic potential of novel alkoxydiaminophosphine-metal (ADAP-M, M = Cu, Ag, Au) complexes in [3 + 2] cycloaddition (32CA) reactions, specifically for synthesizing 1,2,3-triazoles through metal-assisted azide–alkyne cycloaddition (MAAC). Density functional theory (DFT) was used to evaluate the electronic and structural properties of these complexes to determine their catalytic efficiency. The ADAP ligand is crucial for reducing the activation energy and stabilizing intermediates, thereby enhancing catalysis. The study compared mononuclear and binuclear pathways and revealed that ADAP-Cu complexes, especially in binuclear forms, presented the most favorable energy profiles with significant barrier reductions due to cooperative copper interactions. In contrast, ADAP complexes with silver and gold exhibit higher activation energies and lower efficiency. The role of the solvent was also examined, revealing that toluene increases the energy barriers in metal-catalyzed reactions. These findings emphasize the superior catalytic efficiency of copper-based ADAP complexes and the impact of solvent choice on reaction dynamics, offering insights for advanced catalytic system design in organic synthesis.
期刊介绍:
This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.