Computational modeling is increasingly relevant in chemical research, especially in electrocatalysis, where interactions can be potential-dependent. Our Computational Modeling team focuses on performing calculations that can motivate and validate experimental work, in perfect concert with the Reactor Engineering team and the Operando Electrochemical Characterization team. Techniques that the team implements into their research include:
Quantum Mechanical models, such as Joint Density Functional Theory (JDFT) can rapidly expedite the discovery of new, more stable electrocatalysts. Of particular interest is the use of JDFT to screen Metal-Nitrogen-Carbon catalysts, where a graphene sheet is doped with functional metals to promote catalysis.
Molecular Dynamics (MD) is a powerful class of computation, allowing our researchers to assess molecular interactions based on interaction energies. This approach is being used to model the chemical microenvironment of the electrocatalyst, including electrolyte and ionomer interactions with the surface.
Continuum Modeling is relevant to understanding the effects due to scaling electrochemical reactors that are observed by the Reactor Design team. Reactions, diffusion, and convection behaviors are all captured by the mesoscale technique.
Hussain and Paige lead the efforts of catalyst discovery using JDFT, and Paige also has interests in using MD simulations to better understand electrochemical systems. Recep performs continuum models to understand both local effects in the porous electrodes and bulk effects in the electrolyzers.