Reece Christian, Luneau Mathilde, Friend Cynthia M, Madix Robert J
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138, USA.
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA.
Angew Chem Int Ed Engl. 2020 Jun 26;59(27):10864-10867. doi: 10.1002/anie.202001576. Epub 2020 Apr 28.
Controlling the selectivity of catalytic reactions is a critical aspect of improving energy efficiency in the chemical industry; thus, predictive models are of key importance. Herein the performance of a heterogeneous, nanoporous Au catalyst is predicted for the complex catalytic self-coupling of the series of C -C alkyl alcohols, based solely on the known kinetics of the elementary steps of the catalytic cycle for methanol coupling, using scaling methods augmented by density functional theory. Notably, a sharp decrease in selectivity for ester formation with increasing molecular weight to favor the aldehyde due to van der Waals interactions of reaction intermediates with the surface was predicted and subsequently verified quantitatively by experiment. Further, the agreement between theory and experiment clearly demonstrates the efficacy of this approach for building a predictive model of catalytic behavior for a homologous set of reactants using a small set of experimental information.
控制催化反应的选择性是提高化学工业能源效率的关键方面;因此,预测模型至关重要。在此,仅基于甲醇偶联催化循环基本步骤的已知动力学,使用密度泛函理论增强的标度方法,预测了一种非均相纳米多孔金催化剂对一系列碳 - 碳烷基醇复杂催化自偶联反应的性能。值得注意的是,预测随着分子量增加酯形成选择性急剧下降,有利于醛的生成,这是由于反应中间体与表面的范德华相互作用所致,随后通过实验进行了定量验证。此外,理论与实验之间的一致性清楚地证明了这种方法利用少量实验信息构建一组同源反应物催化行为预测模型的有效性。