Multi-scale Atomistic Modeling for Electrocatalytic Applications

Open Access
Akhade, Sneha Anil
Graduate Program:
Chemical Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
August 03, 2016
Committee Members:
  • Michael John Janik, Dissertation Advisor
  • Michael John Janik, Committee Chair
  • Phillip E Savage, Committee Member
  • Scott Thomas Milner, Committee Member
  • Adrianus C Van Duin, Outside Member
  • Janna Kay Maranas, Dissertation Advisor
  • electrocatalysis
  • DFT
  • ReaxFF
  • carbon dioxide electroreduction
  • electrokinetics
With depletion of traditional fossil fuel sources of energy, electrocatalysis is expected to play an important role in the development of alternate energy electrochemical devices, including fuel cells and electrolyzers. The design of effective catalysts is necessary to increase the rate of the electrocatalytic reactions in order to improve the working efficiency of the electrochemical devices. The reactions occur at the electrode/electrolyte interface, with the reaction rates controlled by complex interactions between the redox species and electrolytic ions on the solvated electrode surface that operates under constant applied potentials. These phenomena are difficult to probe experimentally and computational modeling can provide insight on the impact of the electrode potential and electrolyte distribution on the electrocatalytic processes. This dissertation primarily employs Density Functional Theory (DFT) to investigate the effect of the electrode potential on the thermodynamics and kinetics of electrocatalytic reactions. Modeling the electrolyte distribution is not feasible with computationally intensive DFT calculations and as such, classical reactive Molecular Dynamics (MD) simulations are performed to model the structure and dynamics of the electrolyte at longer length and time scales. The electrochemical reduction of CO2 is given special emphasis although the methods and approaches adopted in this dissertation are generally applicable towards investigating any electrocatalytic reaction of interest. CO2 electroreduction (ER) offers the possibility of generating hydrocarbons from renewable energy sources, however, the process is limited by (i) the use of inefficient electrocatalysts that are not selective and active towards hydrocarbon formation, (ii) a poor understanding of the reaction mechanism and the key rate-limiting and selectivity determining steps and, (iii) limited insight on the influence of the electrolyte composition on the selectivity and production rate of key intermediates. In this dissertation, DFT-based calculations are used to probe the electrode potential-dependent activity, reactivity and selectivity of various transition metal electrocatalysts for CO2 ER. A model to estimate the potential-dependent reaction energies and activation barriers is developed and applied to examine elementary kinetics of C-H, O-H and N-H bond breaking and forming steps. The implications of DFT model choices are explored. To address the limitations in the length and time scales of the DFT models, classical reactive MD simulations using ReaxFF are performed to model the electrochemical interface and examine the interfacial distribution and dynamics of the solvent and electrolytic ions under constant applied electrode potentials. The overall objective of this dissertation is to develop computational modeling tools for electrocatalytic reactions and examine the factors that influence the rational design of electrode materials for key electrocatalytic processes.