The research employs advanced computational methods, primarily Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations, to understand and design novel catalytic materials and processes. The research spans several critical areas: CO2 conversion (hydrogenation and electroreduction), water splitting for hydrogen production, and methanol electro-oxidation.

A recurring theme across these studies is the exploration of metal-support interactions (MSI), bimetallic catalysts, and the influence of dopants or support materials on the electronic structure and reactivity of active sites. The work consistently emphasizes the importance of surface effects, demonstrating how seemingly minor structural or compositional changes at interfaces can significantly alter reaction pathways, activation energies, and overall catalytic efficiency. An important part is developing novel parameterization methods for reactive force fields.

Overarching conclusions:

  • Surface effects are paramount: The research consistently demonstrates that surface geometry, termination, and composition, along with the immediate chemical environment of active sites, are critical determinants of catalytic activity and selectivity. Bulk properties alone are insufficient for accurate predictions.
  • Metal-support interactions are key: The studies highlight how support materials, even when not directly participating in bond formation with reactants, can profoundly influence catalytic performance through electronic effects and charge redistribution at the interface. This includes tunable properties of perovskites and the role of ZnO in Cu/ZnO catalysts.
  • Doping as a promoter: Doping, particularly with transition metals like Co, can act as a promoter by altering the electronic properties of neighboring active sites, leading to improved catalytic efficiency (e.g., lower overpotential) even if the dopant itself is not the primary active site.
  • Importance of computational modeling: DFT and MD simulations are indispensable tools for gaining atomistic insights into complex catalytic mechanisms and designing novel materials where experimental characterization is challenging. The development of robust parameterization methods, like the force-matching technique, further enhances the predictive power of these simulations.
  • Complex reaction pathways: Catalytic reactions, especially multi-electron processes like CO2 reduction and methanol oxidation, involve intricate networks of intermediates. Identifying the most thermodynamically and kinetically favorable pathways, along with limiting steps, is crucial for optimizing catalyst design.

Related publications:

https://pubs.acs.org/doi/full/10.1021/acs.cgd.3c01466

https://www.mdpi.com/2673-4141/4/3/37

https://www.mdpi.com/1996-1944/16/14/5138

https://link.springer.com/article/10.1007/s00894-021-04989-6

https://www.sciencedirect.com/science/article/pii/S0169433221009600

https://pubs.acs.org/doi/full/10.1021/acs.jpclett.0c00900

https://pubs.acs.org/doi/full/10.1021/acs.jpcc.8b10872