(2z) Towards an Atomistic Understanding of Microenvironment Effects in (electro)Catalytic Reactions for Energy Conversion

As we are in the midst of a climate crisis, there is an urgent need to transition to the sustainable production of fuels and chemicals. A promising approach in this regard is the electrochemical conversion of atmospherically available gases such as H2O, CO2, O2, and N2 to fuels and chemicals using renewable electricity. Electrocatalysts are central to these electrochemical processes as they increase the reaction rate, efficiency and selectivity towards the desired products. Several research efforts over the past decade have been directed towards the design and discovery of electrocatalytic materials and the optimization of electrochemical cell architectures for high efficiency, stability and sustainability.

Electrode-electrolyte interfaces (EEIs) are at the heart of electrochemical processes, and an atomistic level understanding of the structure and the elementary steps that occur at the interface is paramount to move the field forward towards the design and optimization of next generation materials for energy storage and conversion. However, an atomistic level understanding of EEIs is extremely challenging due to their complexity given the dynamic nature of the electrode surface, strong interfacial electric fields that vary with the applied potential, several components of the electrolyte (solvent, cations, anions) and the interfacial pH gradients under electrochemical reaction conditions. In this regard, first-principles based simulations of EEIs can provide valuable insights at the atomistic level, that is often challenging/inaccessible using in-silico experimental techniques. The overarching goal of my research is to gain an atomistic level understanding of electrochemical processes that occur at the electrode-electrolyte interface using a number of simulation tools including density functional theory based molecular dynamics (DFT-MD), deep learning molecular dynamics incorporating long-range electrostatic interactions (DPLR), advanced sampling methods, DFT based microkinetic simulations coupled to continuum transport models. In particular, we aim to use these techniques to address the following questions:

1. The structure of the electrode-electrolyte interface including the microscopic structure of the electrical double layer under electrochemical conditions using DFT-MD and DPLR simulations
2. The effects of the microenvironment on electrocatalytic processes including the effects of cations, buffering anions and the interfacial pH using DFT-MD, enhanced sampling methods and DPLR
3. Combining electrokinetic experiments and microkinetic models to gain an in-depth understanding of the reaction mechanisms for multi-step electrochemical processes
4. Coupling microkinetic models and transport models to identify key parameters that control the microenvironment, thereby moving towards optimization of electrochemical cell architectures

Related publications:

1. Govindarajan, N., Tiwari, A., Ensing, B., Meijer, E. J., Inorg. Chem., 57, 13063-13066 (2018)
2. Govindarajan, N., Koper, M. T. M., Meijer, E. J., and Calle-Vallejo, F., ACS Catal., 9, 4218-4225 (2019)
3. Govindarajan, N., Beks, H., and Meijer, E. J., ACS Catal, 10, 14665-14781 (2020)
4. Govindarajan, N., Kastlunger, G., Heenen, H. H, and Chan, K., Chem Sci., 13, 14-26 (2022)
5. Kelly, S. R.#, Heenen, H. H.#, Govindarajan, N.#, Chan, K., and Nørskov, J. K., J. Phys. Chem. C., 126, 5521-5528 (2022) # = Equal contribution
6. Govindarajan, N., Xu, A.,and Chan, K., Science, 375, 379-380 (2022)

Teaching interests:

I strongly believe that having good teachers and mentors are essential in both the personal and professional development of an individual. Having benefitted from passionate teachers and mentors myself, it is my responsibility to share my experience and knowledge with the future generation. Given my education and research backgrounds in the areas of chemical engineering and physical chemistry, I’m in a good position to teach core chemical engineering courses including thermodynamics, chemical reaction engineering and transport phenomena. A particular emphasis will be placed on the use of scientific programming libraries (scipy, numpy) to solve exercise problems and assignments in these topics. A couple of specific graduate level courses I would like to develop and teach include (i) Molecular simulations including molecular dynamics, monte-carlo sampling and enhanced sampling methods with hands-on sessions and examples of research problems that I actively work on, and (ii) concepts in heterogeneous catalysis with a particular focus on computational electrocatalysis for sustainable energy conversion. I am excited to use the flipped classroom model for these advanced graduate courses as it encourages student engagement, live problem-solving and focus on the most important concepts and questions.