论文标题
面向化学反应的设计：反应物空间中竞争机制的机器学习障碍
Towards the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space
论文作者
论文摘要
尽管用于研究平衡状态的复杂数值方法具有很好的先进，但动力学行为的定量预测仍然具有挑战性。我们引入了一个反应物到屏障（R2B）机器学习模型，该模型可以快速，准确地渗透到整个化学复合空间中的激活能和过渡状态几何形状。随着训练集的增长，R2B享有提高的准确性，并且需要作为反应物的输入仅分子图信息。我们提供了R2B对有机合成相关的两个相互竞争的教科书反应E2和SN2的适用性的数值证据，对文献中化学多样的量子数据进行了培训和测试。在1K至1.8K示例进行训练后，R2B在毫秒内平均在耦合群集单打双打（CCSD）参考方面平均预测激活能量。内核矩阵的主要成分分析揭示了化学空间中反应性的多个量表的层次结构：亲核者和离开基团，取代基和成对取代基组合对应于系统降低特征值。对先前无证件反应物的气相中基于R2B的预测对〜11.5K E2和SN2屏障的分析表明，在所有情况的75％中，E2平均受到青睐，并且SN2可能对与氯的亲核激素/离开组可能成为对应于氯的，并且对于由氢或电子或绘画组组成的替代物。得益于R2B，实现了第一原理的实验反应设计，这是通过决策树的构建证明的。基于数值R2b的基于原子间距离的结果和反应物和过渡状态几何形状的角度表明Hammond的假设适用于SN2，但不适用于E2。
While sophisticated numerical methods for studying equilibrium states have well advanced, quantitative predictions of kinetic behaviour remain challenging. We introduce a reactant-to-barrier (R2B) machine learning model that rapidly and accurately infers activation energies and transition state geometries throughout chemical compound space. R2B enjoys improving accuracy as training sets grow, and requires as input solely molecular graph information of the reactant. We provide numerical evidence for the applicability of R2B for two competing text-book reactions relevant to organic synthesis, E2 and SN2, trained and tested on chemically diverse quantum data from literature. After training on 1k to 1.8k examples, R2B predicts activation energies on average within less than 2.5 kcal/mol with respect to Coupled-Cluster Singles Doubles (CCSD) reference within milliseconds. Principal component analysis of kernel matrices reveals the hierarchy of the multiple scales underpinning reactivity in chemical space: Nucleophiles and leaving groups, substituents, and pairwise substituent combinations correspond to systematic lowering of eigenvalues. Analysis of R2B based predictions of ~11.5k E2 and SN2 barriers in gas-phase for previously undocumented reactants indicates that on average E2 is favored in 75% of all cases and that SN2 becomes likely for nucleophile/leaving group corresponding to chlorine, and for substituents consisting of hydrogen or electron-withdrawing groups. Experimental reaction design from first principles is enabled thanks to R2B, which is demonstrated by the construction of decision trees. Numerical R2B based results for interatomic distances and angles of reactant and transition state geometries suggest that Hammond's postulate is applicable to SN2, but not to E2.
