75 elementary-step unimolecular reactions of the simplest γ-ketohydroperoxide, 3-hydroperoxypropanal, were discovered by a combination of several automated reaction discovery methodologies based on density functional theory calculations. This molecule is used as a test case for automated reaction discovery because 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 order to further explore their chemical space, 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 (AFIR) are used to automatically identify viable reaction pathways. 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 AFIR detected several reactions not found by any of the other methods. Many of the detected low-barrier chemical reactions involve promising new chemistry that may be relevant in atmospheric and combustion systems. This 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).

Discovering unimolecular reaction pathways using an ensemble of automated reaction discovery methods

256th National Meeting (2018)

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