(617a) Ab Initio Study of Organometallic Phthalocyanine Catalysts for the Conversion of Methane to Methanol | AIChE

(617a) Ab Initio Study of Organometallic Phthalocyanine Catalysts for the Conversion of Methane to Methanol

Authors 

Ferrone, C. - Presenter, New Mexico Tech
Choudhury, P., University of South Florida
Methane’s low energy density and contribution to the greenhouse gas effect has emphasized the importance of converting methane to methanol. In this work, organometallic, single transition metal active site heterogeneous phthalocyanine catalysts have been designed to activate methane in a single step process. Copper and cobalt phthalocyanines, supported by TiN a substrate, have been studied using ab initio density functional theory (DFT) implemented in the Vienna ab initio software package (VASP). Titanium nitride (TiN) has potential as a substrate due to its metallic-like behavior and favorable optical properties. Catalytic tuning through phthalocyanine and substrate doping have been explored. Results show an inverse relationship between the rate of C-H bond breakage and the metal-oxo species intermediate formation energy. A correlation between rate and formation energy has been further explored in active site metal charge state as a potential descriptor even in the presence of nonidealities, such as substrate vacancies and oxidation. The Nudged Elastic Band method (NEB) was used to further understand the kinetics and transition state energy of methane activation and methanol formation. This work has provided a quick and experimentally accurate method for screening catalytic systems for the conversion of methane to methanol.

Acknowledgments: Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support (or partial support) of this research. The work is supported by ACS-PRF Grant No [58740-UR6]. This work used the Extreme Science and Engineering Discovery Environment (XSEDE) TACC at the stampede2 through allocation [TGDMR140131]. This work utilized resources from the University of Colorado Boulder Research Computing Group, which is supported by the National Science Foundation (awards ACI-1532235 and ACI-1532236), the University of Colorado Boulder, and Colorado. PCC Cluster, NM Consortium, NM.