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引用次数: 0
摘要
量子化学方法已被广泛应用于研究葡萄糖热解转化为羟甲基糠醛(HMF)和糠醛(FF)的过程。在此,我们收集了近期文献中最相关的机理建议,并将其整理成一个反应网络。我们采用高度精确的 ab initio 方法对所有过渡结构(TSs)和中间产物进行了表征,并根据 TSs 和中间产物相对于 β-吡喃葡萄糖的吉布斯能评估了可能的反应途径,选择了 773 K 的二维理想气体标准状态来代表热解条件。有几种途径可导致 HMF 和 FF 的形成,并通过速率决定 TS,其 ΔG‡ 值约为 49-50 kcal/mol。水助机制和非特异性环境效应对吉布斯能谱的影响较小。我们发现,HMF → FF + CH2O 片段的 ΔrxnG 值较小,且可达到 ΔG‡ 势垒。我们的计算结果与从整块模型中得出的动力学参数、同位素标记实验结果以及报告的 HMF/FF 分子比一致,有助于包括非平衡动力学效应在内的建模研究,从而提供更多有关产物产量和各种途径相关性的信息。
Pyrolytic conversion of glucose into hydroxymethylfurfural and furfural: Benchmark quantum-chemical calculations
Quantum chemical methods have been intensively applied to study the pyrolytic conversion of glucose into hydroxymethylfurfural (HMF) and furfural (FF). Herein, we collect the most relevant mechanistic proposals from the recent literature and organize them into a single reaction network. All the transition structures (TSs) and intermediates are characterized using highly accurate ab initio methods and the possible reaction pathways are assessed in terms of the Gibbs energies of the TSs and intermediates with respect to β-glucopyranose, selecting a 2D ideal-gas standard state at 773 K to represent the pyrolysis conditions. Several pathways can lead to the formation of both HMF and FF passing through rate-determining TSs that have ΔG‡ values of ~49–50 kcal/mol. Both water-assisted mechanisms and nonspecific environmental effects have a minor impact on the Gibbs energy profiles. We find that the HMF → FF + CH2O fragmentation has a small ΔrxnG value and an accessible ΔG‡ barrier. Our computational results, which are in consonance with the kinetic parameters derived from lumped models, the results of isotopic labeling experiments and the reported HMF/FF molecular ratios, could be useful for modeling studies including on nonequilibrium kinetic effects that may render more information about product yields and the relevance of the various pathways.
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.