Efficient Screening of Metal Promoters of Pt Catalysts for C-H Bond Activation in Propane Dehydrogenation from a Combined First-Principles Calculations and Machine-Learning Study.

Platinum-based materials are the most widely used catalysts in propane direct dehydrogenation, which could achieve a balanced activity between both propane conversion and propene formation. One of the core issues of Pt catalysts is how to efficiently activate the strong C-H bond. It has been suggested that adding second metal promoters could greatly solve this problem. In the current work, first-principles calculations combined with machine learning are performed in order to obtain the most promising metal promoters and identify key descriptors for control performance. The combination of three different modes of adding metal promoters and two ratios between promoters and platinum sufficiently describes the system under investigation. The activity of propane activation and the formation of propene are reflected by the increase or decrease of the adsorption energy and C-H bond activation of propane and propene after the addition of promoters. The data of adsorption energy and kinetic barriers from first-principles calculations are streamed into five machine-learning methods including gradient boosting regressor (GBR), K neighbors regressor (KNR), random forest regressor (RFR), and AdaBoost regressor (ABR) together with the sure independence screening and sparsifying operator (SISSO). The metrics (RMSE and R2) from different methods indicated that GBR and SISSO have the most optimal performance. Furthermore, it is found that some descriptors derived from the intrinsic properties of metal promoters can determine their properties. In the end, Pt3Mo is identified as the most active catalyst. The present work not only provides a solid foundation for optimizing Pt catalysts but also provides a clear roadmap to screen metal alloy catalysts.

Engineering the catalytic properties of CeO2 catalyst in HCl-assisted propane dehydrogenation by effective doping: A first-principles-based microkinetic simulation.

HCl-assisted propane dehydrogenation (PDH) is an attractive route for propene production with good selectivity. In this study, the doping of CeO2 with different transition metals, including V, Mn, Fe, Co, Ni, Pd, Pt, and Cu, in the presence of HCl was investigated for PDH. The dopants have a pronounced effect on the electronic structure of pristine ceria that significantly alters the catalytic capabilities. The calculations indicate the spontaneous dissociation of HCl on all surfaces with a facile abstraction of the first hydrogen atom except on V- and Mn-doped surfaces. The lowest energy barrier of 0.50 and 0.51eV was found for Pd- and Ni-doped CeO2 surfaces. The surface oxygen is responsible for hydrogen abstraction, and its activity is described by the p-band center. Microkinetics simulation is performed on all doped surfaces. The increase in the turnover frequency (TOF) is directly linked with the partial pressure of propane. The adsorption energy of reactants aligned with the observed performance. The reaction follows first-order kinetics to C3H8. Furthermore, on all surfaces, the formation of C3H7 is found as the rate-determining step confirmed by the degree of rate control (DRC) analysis. This study provides a decisive description of catalyst modification for HCl-assisted PDH.