Ammonia (NH3) is a promising carbon-free energy carrier due to its high hydrogen content and ease of liquefaction, enabling efficient storage and transportation. However, conventional ammonia production via the Haber-Bosch process is energy intensive, requires high temperature and pressure, and results in significant CO2 emissions. Electrochemical nitrogen reduction reaction (NRR) offers a sustainable alternative for ammonia synthesis under ambient conditions, but its performance in aqueous systems is fundamentally limited by high overpotentials and poor selectivity caused by competing interfacial reactions. This project will use first-principles simulations and machine learning-assisted modeling to investigate and engineer aqueous electrode-electrolyte interfaces for selective ammonia synthesis. Density functional theory (DFT), explicit-solvent ab initio molecular dynamics (AIMD), and enhanced sampling techniques will be employed to resolve intrinsic reaction mechanisms governing nitrogen activation, proton transfer, and competing hydrogen evolution at electrified interfaces. Particular emphasis will be placed on understanding how electrolyte composition, interfacial solvation structure, and local electric fields modulate reaction energetics and selectivity. Mechanistic insights derived from these simulations will be used to establish theory-driven interface design principles for improving NH3 yield, Faradaic efficiency, and energy efficiency in aqueous NRR under mild conditions.
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Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees