Hydrodechlorination of 1,2-Dichloroethane on Platinum Catalysts: Insights from Reaction Kinetics Experiments, Density Functional Theory, and Microkinetic Modeling

Catalytic hydrodechlorination is a promising strategy for treating industrial 1,2-dichloroethane wastes, for which Pt and Pt-based alloy catalysts are widely used. Here, we performed a detailed mechanistic study for 1,2-dichloroethane hydrodechlorination on Pt using a synergistic approach combining density functional theory (DFT) calculations, reaction kinetics experiments, and microkinetic modeling. Using planewave DFT calculations, we evaluated the reaction energy and activation energy barrier of each elementary step involved in the reaction network on Pt(111). The calculated energetics were then incorporated into a comprehensive mean-field microkinetic model accounting for a total of 65 elementary steps. The model-predicted reaction rates were compared with the results from our reaction kinetics experiments on SiO2-supported Pt catalysts. Our results indicated that the hydrodechlorination of 1,2-dichloroethane on Pt(111) starts with a H-removal step; then, it proceeds through a sequence of alternating dechlorination and dehydrogenation steps until vinylidene (CH2C*) is formed; finally, CH2C* is hydrogenated to the final product, ethane, sequentially via vinyl (CH2CH*), ethylene, and ethyl (CH3CH2*) intermediates. After model parameter adjustments, we achieved good agreement between our theoretical model and experimental results; the adjustments to the calculated parameters are consistent with the typically anticipated coverage effects. Our study offers valuable mechanistic insights, which are useful for improving catalysts for this chemistry.

Automated summary

Catalytic hydrodechlorination of 1,2-dichloroethane using Pt catalysts was studied through a synergistic approach of DFT calculations, reaction kinetics experiments, and microkinetic modeling. The reaction on Pt(111) involves multiple steps leading to the formation of ethane. Adjustments to model parameters were made to achieve good agreement between theoretical predictions and experimental results, highlighting the importance of coverage effects in catalytic reactions. Overall, the study provides valuable mechanistic insights for improving catalysts in this chemistry.