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基于自动化反应发现方法的γ-酮氢过氧化物的单分子反应途径。

Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods.

机构信息

Department of Chemical Engineering, Massachusetts Institute of Technology , 77 Massachusetts Ave., Cambridge, Massachusetts 02139, United States.

Combustion Research Facility, Sandia National Laboratories , 7011 East Ave., Livermore, California 94551, United States.

出版信息

J Am Chem Soc. 2018 Jan 24;140(3):1035-1048. doi: 10.1021/jacs.7b11009. Epub 2018 Jan 8.

DOI:10.1021/jacs.7b11009
PMID:29271202
Abstract

Ketohydroperoxides are important in liquid-phase autoxidation and in gas-phase partial oxidation and pre-ignition chemistry, but because of their low concentration, instability, and various analytical chemistry limitations, it has been challenging to experimentally determine their reactivity, and only a few pathways are known. In the present work, 75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of density functional theory with several automated transition-state search algorithms: the Berny algorithm coupled with the freezing string method, single- and double-ended growing string methods, the heuristic KinBot algorithm, and the single-component artificial force induced reaction method (SC-AFIR). The present joint approach significantly outperforms previous manual and automated transition-state searches - 68 of the reactions of γ-ketohydroperoxide discovered here were previously unknown and completely unexpected. All of the methods found the lowest-energy transition state, which corresponds to the first step of the Korcek mechanism, but each algorithm except for SC-AFIR detected several reactions not found by any of the other methods. We show that the low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. Our study highlights the complexity of chemical space exploration and the advantage of combined application of several approaches. Overall, the present work demonstrates both the power and the weaknesses of existing fully automated approaches for reaction discovery which suggest possible directions for further method development and assessment in order to enable reliable discovery of all important reactions of any specified reactant(s).

摘要

酮过氧化物在液相自动氧化和气相部分氧化及预点火化学中很重要,但由于其浓度低、不稳定性以及各种分析化学的局限性,使得实验确定其反应性具有挑战性,目前仅知道少数几种途径。在本工作中,通过密度泛函理论与几种自动过渡态搜索算法(Berny 算法与冻结字符串法、单端和双端增长字符串法、启发式 KinBot 算法以及单组分人工力诱导反应法(SC-AFIR))的结合,发现了最简单的γ-酮过氧化物 3-过氧丙醛的 75 个基元单分子反应。本联合方法明显优于以前的手动和自动过渡态搜索-这里发现的 68 种γ-酮过氧化物反应以前是未知的,完全出乎意料。所有方法都找到了最低能量过渡态,对应于 Korcek 机制的第一步,但除了 SC-AFIR 之外的每种算法都检测到了其他方法都没有发现的几种反应。我们表明,低势垒化学反应涉及有前途的新化学,可能与大气和燃烧系统有关。我们的研究强调了化学空间探索的复杂性和几种方法联合应用的优势。总的来说,本工作展示了现有完全自动化反应发现方法的强大功能和弱点,为进一步开发和评估方法以可靠发现任何指定反应物的所有重要反应提供了可能的方向。

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