van Schendel Robin K A, Yang Wenjun, Uslamin Evgeny A, Pidko Evgeny A
Inorganic Systems Engineering Department of Chemical Engineering Delft University of Technology Van der Maasweg 9 2629 HZ Delft (The Netherlands.
ChemCatChem. 2021 Dec 7;13(23):4886-4896. doi: 10.1002/cctc.202101140. Epub 2021 Sep 14.
Homogeneous hydrogenation catalysts based on metal complexes provide a diverse and highly tunable tool for the fine chemical industry. To fully unleash their potential, fast and effective methods for the evaluation of catalytic properties are needed. In turn, this requires changes in the experimental approaches to test and evaluate the performance of the catalytic processes. Design of experiment combined with statistical analysis can enable time- and resource-efficient experimentation. In this work, we employ a set of different statistical models to obtain the detailed kinetic description of a highly active homogeneous Mn (I) ketone hydrogenation catalyst as a representative model system. The reaction kinetics were analyzed using a full second order polynomial regression model, two models with eliminated parameters and finally a model which implements "chemical logic". The coefficients obtained are compared with the corresponding high-quality kinetic parameters acquired using conventional kinetic experiments. We demonstrate that various kinetic effects can be well captured using different statistical models, providing important insights into the reaction kinetics and mechanism of a complex catalytic reaction.
基于金属配合物的均相氢化催化剂为精细化工行业提供了一种多样且高度可调的工具。为了充分发挥其潜力,需要快速有效的催化性能评估方法。反过来,这就要求改变测试和评估催化过程性能的实验方法。实验设计与统计分析相结合能够实现高效省时的实验。在这项工作中,我们采用了一组不同的统计模型来获得一种高活性均相锰(I)酮氢化催化剂作为代表性模型体系的详细动力学描述。使用全二阶多项式回归模型、两个消除参数的模型以及最终一个实施“化学逻辑”的模型对反应动力学进行了分析。将所得系数与使用传统动力学实验获得的相应高质量动力学参数进行了比较。我们证明,使用不同的统计模型可以很好地捕捉各种动力学效应,为复杂催化反应的反应动力学和机理提供重要见解。