Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, United States.
SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States.
J Phys Chem Lett. 2021 Mar 25;12(11):2954-2962. doi: 10.1021/acs.jpclett.1c00195. Epub 2021 Mar 17.
In heterogeneous catalysis, free energy profiles of reactions govern the mechanisms, rates, and equilibria. Energetics are conventionally computed using the harmonic approximation (HA), which requires determination of critical states Here, we use neural networks to efficiently sample and directly calculate the free energy surface (FES) of a prototypical heterogeneous catalysis reaction-the dissociation of molecular nitrogen on ruthenium-at density-functional-theory-level accuracy. We find that the vibrational entropy of surface atoms, often neglected in HA for transition metal catalysts, contributes significantly to the reaction barrier. The minimum free energy path for dissociation reveals an "on-top" adsorbed molecular state prior to the transition state. While a previously reported flat-lying molecular metastable state can be identified in the potential energy surface, it is absent in the FES at relevant reaction temperatures. These findings demonstrate the importance of identifying critical points self-consistently on the FES for reactions that involve considerable entropic effects.
在多相催化中，反应的自由能曲线决定了反应的机理、速率和平衡。通常使用谐波近似（HA）来计算自由能，这需要确定关键状态。在这里，我们使用神经网络来有效地采样并直接计算一个典型的多相催化反应——氮气在钌上的解离——的自由能面（FES），其达到了密度泛函理论的精度。我们发现，表面原子的振动熵通常在 HA 中被忽略，对于过渡金属催化剂来说，它对反应势垒有显著贡献。解离的最小自由能路径揭示了在过渡态之前存在一个“顶位”吸附的分子态。尽管在势能表面上可以识别到先前报道的平面分子亚稳态，但在相关反应温度下，它在 FES 中不存在。这些发现表明，对于涉及到相当大的熵效应的反应，在 FES 上一致地确定关键点是很重要的。
