Towards first-principles prediction of electrocatalytic activity of ABO₃ perovskites
Author(s)Rong, Xi, Ph. D. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Mechanical Engineering.
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The design of efficient, stable, and inexpensive catalysts such as ABO 3 perovskites for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR) is crucial for the development of electrochemical energy conversion devices such as water electrolysis, fuel cells, and metal-air batteries. In order to enable high-throughput computation and screening for optimal catalysts, a deeper understanding of composition-structure-activity relationships is required. Currently, this endeavor is hindered by the complexity of the oxide surface structure and challenges in atomic-scale experimental characterization under in operando conditions. In this thesis, we address these issues by employing density functional theory and classical methods, including electrochemical principles and micro-kinetics, for prediction of catalyst surface structure, stability, and reaction mechanism as a function of environment. We have performed investigations focused on the following thrusts: 1) Predicting the active surface phase under the operation conditions; 2) elucidating possible OER reaction mechanisms and correlating the preferred mechanism to ABO 3 stability; 3) identifying electronic structure correlations to surface reactivity; and 4) demonstrating the high efficiency of Ruddlesden-Popper (RP) perovskties. To this end, we have derived a general formalism for incorporating pH- and U-dependent ion exchange at the catalyst surface-solvent interface, and used this approach to determine the surface structure/composition phase diagram of various perovkites, demonstrating that the surface structure of perovskites is highly sensitive to the environment, which in turn alters electrocatalytic activity. These effects are dramatically important for those highly efficient ABO 3 compounds, for which we showed that the lattice oxygen becomes an active participant in the OER mechanism. Combining this new mechanism (the lattice oxygen mediated mechanism or LOM) with the conventional adsorbate evolution mechanism (AEM), we developed a new overall activity volcano, and showed that LOM is fundamentally more thermodynamically favorable and thus governs the activity of the most efficient catalysts. Furthermore, we have identified a fundamental descriptor for the binding energy of oxygen surface reaction intermediates based on the shape of the transition metal cation d-projected density of states, as described by its 1s-4th mathematical moments, and provided a strong physical grounding for this descriptor from a tight-binding analysis and use of the moments theorem. This work has led to an essential extension of the widely used d-band theory for metal catalysts to the realm of oxides. With the insights gained from the ABO 3 perovskite, we finally extended our study to understand the origin of the high efficiency and stability of some novel types of perovskite. Together, these efforts have contributed crucial insights into the complete composition-structure-activity relationship, and provided important steps towards the objective of using first-principles computations to predict ABO 3 activity for OER and ORR These insights are transferrable to many other catalytic reactions, in which oxideliquid interfaces play a critical role, and have potential to critically impact our understanding of surface chemistry, corrosion, energy conversion, and electrochemical science. Keywords Perovskite-based electrocatalysts; oxygen evolution and reduction reactions; density functional theory; surface structure; machine learning.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018."Feb 2018." Cataloged from PDF version of thesis.Includes bibliographical references (pages 159-172).
DepartmentMassachusetts Institute of Technology. Department of Mechanical Engineering.; Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology