论文标题
浓度 - 液压探测机制探索，并进行了细胞分析
Concentration-Flux-Steered Mechanism Exploration with an Organocatalysis Application
论文作者
论文摘要
使用自动反应网络探索算法研究反应性化学系统比手动研究更详细地描述了其化学机制。通常，出于可行的原因，探索算法无法详尽地发现反应网络。因此，他们应该在某些外部条件下确定网络的哪一部分在动力学上相关。在这里，我们提出了一种自动化算法，该算法通过通过（不完整的）反应网络对浓度通量的显式建模在自动化的第一原则探索过程中出现的（不完整的）反应网络来识别和探索反应网络的动力学访问区域。自动识别并选择关键化合物以延续探索。例如，我们探索了多组分脯氨酸催化的迈克尔添加丙烯和硝苯的反应网络。我们的算法提供了前所未有的细节，提供了迈克尔添加的机械图。
Investigating a reactive chemical system with automated reaction network exploration algorithms provides a more detailed picture of its chemical mechanism than what would be accessible by manual investigation. In general, exploration algorithms cannot uncover reaction networks exhaustively for feasibility reasons. They should therefore decide which part of a network is kinetically relevant under some external conditions given. Here, we propose an automated algorithm that identifies and explores kinetically accessible regions of a reaction network on the fly by explicit modeling of concentration fluxes through an (incomplete) reaction network that is emerging during automated first-principles exploration. Key compounds are automatically identified and selected for the continuation of the exploration. As an example, we explore the reaction network of the multi-component proline-catalyzed Michael addition of propanal and nitropropene. Our algorithm provides a mechanistic picture of the Michael addition in unprecedented detail.
