Automatic mechanism generation is used to determine mechanisms for the CO₂ hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO₂ catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO₂ methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.

中文翻译：

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量化参数不确定度对 Ni(111) 上 CO2 加氢自动生成机制的影响

自动机理生成用于确定两阶段过程中 Ni(111) 上CO ₂加氢的机理，同时系统地考虑基于 DFT 的能量参数的相关不确定性。在粗略阶段，探索所有可能的化学反应，气相产物低至 ppb 级，而精炼阶段则发现核心甲烷化子机制。产生了五千个独特的机制，其中所有参数都包含微小的扰动。进行全局不确定性评估、全局敏感性分析和速率控制程度分析，以研究这种参数不确定性对微动力学模型预测的影响。模型预测与 Ni/SiO ₂实验数据的比较催化剂在相关的不确定性空间内找到一组可行的微动力学机制，这些机制与测量数据在数量上一致，而不依赖于明确的参数优化。全球不确定性和敏感性分析提供了确定控制参数空间内甲烷化活动的途径和关键因素的工具。总之，这些方法表明，如果不考虑参数不确定性，速率控制方法的程度可能会产生误导。在自动机制生成中考虑不确定性的过程并不是 CO ₂甲烷化所独有的，并且可以很容易地扩展到其他具有挑战性的非均相催化反应。