A theoretical approach toward sustainable ammonia synthesis
- Ammonia is one of the most significant industrially produced chemicals for its role as fertilizer in feeding the world's growing population. The Haber-Bosch process for the reduction of atmospheric nitrogen to ammonia using fossil-derived hydrogen is also one of the most scientifically important reactions in heterogeneous catalysis, as many of the fundamental concepts in the field such as the significance of defect sites and the existence of rate-determining steps were developed by researchers studying this reaction. Despite enormous effort, two major drawbacks of the industrial process are (A) the expensive and wasteful centralized infrastructure for fertilizer production and distribution necessitated by the harsh conditions required to activate the N-N triple bond while maintaining a strong thermodynamic driving force, and (B) the environmental impact associated with the dependence on unsustainable fossil fuel resources for energy and hydrogen. The development of an alternative route to ammonia that operates in a distributed fashion under ambient conditions, based on renewable energy sources such as solar and wind, could be both economically and environmentally beneficial. In this work, we use electronic structure calculations based on density functional theory in conjunction with microkinetic modeling to develop three strategies toward sustainable ammonia synthesis: (1) designing improved catalysts for a low-temperature, low-pressure version of the thermochemical Haber-Bosch process, (2) establishing a set of guidelines for an active and selective electrochemical ammonia synthesis process, and (3) designing a hybrid approach that leverages the beneficial elements of both the thermochemical and electrochemical processes. Finally, we improve the efficiency of our computational methods by developing two machine learning approaches that reduce the number of density functional theory calculations required for the construction of surface phase diagrams and the prediction of activation barriers.
|Type of resource
|electronic resource; remote; computer; online resource
|1 online resource.
|Singh, Aayush Ranjan
|Degree committee member
|Stanford University, Department of Chemical Engineering.
|Statement of responsibility
|Aayush Ranjan Singh.
|Submitted to the Department of Chemical Engineering.
|Thesis Ph.D. Stanford University 2019.
- © 2019 by Aayush Ranjan Singh
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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