(128b) Predictor of Fischer Tropsch Catalyst Performance for 55-Atom Metal Clusters | AIChE

(128b) Predictor of Fischer Tropsch Catalyst Performance for 55-Atom Metal Clusters

Authors 

Godara, S. - Presenter, Louisiana Tech university
Mainardi, D. S., Louisiana Tech University
All Fischer-Tropsch mechanisms known to date begin with the adsorption of carbon monoxide followed by its dissociation on a given catalysts surface. 13-atom Cluster models of Co, Fe, Ni, Pd, Pt, and Ru have been explored using Density Functional Theory. Carbon monoxide adsorption energies were calculated for adsorption on all possible catalytic sites, and the most preferred CO adsorption sites were found in each case. An initial predictor that can be used to anticipate potentially effective catalysts was identified as a percentage difference, using CO adsorption energy results in combination with CO dissociation energies from the previously found sites. A greater catalysts performance is expected when that percentage difference is maximized. On pure clusters, the predictor indicates that ruthenium is expected to be the best catalyst followed by cobalt, in very good agreement with the current knowledge in this field.

CO adsorption and dissociation on 55-atom metallic clusters is under study. The main idea of this work is to apply the same predictor; which worked well on 13 atoms pure clusters, on clusters containing 55 atoms. Structural and thermal stability of these metallic clusters will be first investigated using a python code that combines classical Monte Carlo and Molecular Dynamics. The chemistry of these clusters will be then explored by investigating the adsorption and desorption of CO and further Fischer-Tropsch reaction steps. Thus, this work presents a mechanism to quickly explore the natural potential of a catalyst material as a Fischer-Tropsch catalyst.

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