Design of metal nanoclusters as catalyst for Fischer-Tropsch Reaction

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Design of metal nanoclusters as catalyst for Fischer-Tropsch Reaction Sumegha Godara Dr. Daniela Mainardi Louisiana Tech University June, 2017 3

Introduction: Metal nanocluster Models Black box of Catalysts Long-chained hydrocarbons CO + H2 nCO + (2n+1)H2  CnH2n+2 + nH2O 55 atom nanoclusters (D ~ 1 nm): With DFT implemented in VASP Ru Pt Pd Co Ni Fe 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.

Increased cluster model size Selection Process of Catalyst Model Energy Barrier CO dissociation CO adsorption D ~ 0.5 nm (13 atoms) D ~ 1.5 nm (55 atoms) D ~ 0.9 nm (38 atoms) D ~ 2.0 nm (309 atoms) Increased cluster model size Our Approach is to study the CO adsorption and dissociation on bigger metal cluster to have more realistic results as we only have studied this on the smallest stable cluster of 13 atoms. And also apply that % difference on bimetallic clusters to see how they behave. Best metallic catalyst ?? Can this be used to predict binary systems’ behavior?

Scaling of # of cores in VASP On QueenBee2 LONI : 1 node:20 cores Not all elements are good for everything, there are metals that produce hydrocarbons, others produce oxygenate species, and Rh produces ethanol As I mentioned before the metals that exhibit FT catalytic activity are placed in order here, but for practical purposes, iron and cobalt are the best. If you take a look at their cost, you will see… An idea to reduce cost is to use core-shell nanocatalysts That is possible if the elements segregate In any other case, it will be a mixture/ alloy

Future work (Parallelization with MPI) Initial (random) configuration Final (most probable) configuration found Molecular Dynamics simulation NVE ensemble (to relax the structure) A Python code was written Random atomic initial configuration A Monte Carlo allows to find the most probable arrangement of atoms A system thermalization (heat treatment) is performed via Molecular Dynamics. Kinetic energy is given to the system according to a Maxwell-Boltzmann distribution at T0 and the system evolves to a relaxed structure. We optimized the 55 atom clusters and the CO adsorption and diss studies are in process. A python code was written to see the thermal stability of the clusters in which a random ….

Acknowledgements The Mainardi Research Group at Louisiana Tech University Financial/Computational Support provided by US National Science Foundation, NSF-CREST, Grant HRD-1242152 NSF LA-SiGMA, EPS-1003897 NSF CAREER, Grant CTS-0449046 NSF IMR, Grant DMR-0414903 Louisiana Board of Regents, Contract LEQSF(2007-08)-ENH-TR-46 The Louisiana Optical Network Initiative (LONI) PhD Students Suraj Gyawali Shawn Cole Sumegha Godara Dr. Purnima Kharidehal Dr. Fernando Soto MS Students Sajin Killa King-Ki Fung, MS Visiting Researchers Alaina Fox – REU Summer’15 Mary Beth McCoy– RET Summer 2015 – Sterlington Middle and Ouachita Junior High School, LA

Questions?