Computational Study for Selective Ethane Dehydrogenation Using Metal Phosphide Catalysts

Metal phosphides (MP) are a potential new class of ethane dehydrogenation (EDH) catalysts. MP structural and compositional diversity brings an opportunity for tuning catalytic properties over a wide range, but it also presents a difficulty in computer simulation. In this dissertation, density functional theory (DFT) calculations were employed to describe how I dealt with that diversity and investigated EDH performance on metal phosphides.

A comparison of the trend in adsorbate-binding and elementary reactions of EDH on model Ni and Ni2P surfaces elucidates the role of P atom in improving EDH performance. Mechanistics underlying microkinetic models at the experimental conditions rationalize the enhanced EDH performance of Ni2P.

A simple isostructural metal phosphide model was selected to reduce the structural diversity, and they were utilized to perform a screening of selective EDH catalyst over metal phosphide series via the adsorbate-binding characteristics which observed in the above Ni2P studies.

Lastly, a systematical strategy is introduced to show how I handle the compositional diversity of metal phosphides through combined theoretical and experimental inference, and thermodynamic evaluation of their structures. This approach demonstrates influences of P content on EDH performance, and importance of the size of metallic ensemble in the phosphide surface chemistry.