Combining Experiments and First-Principles Calculations to Understand and Engineer Metal Exsolution in Perovskites

Exsolution processing has emerged as a leading new route to fabricate highly active and stable ceramic-supported metal catalysts for a wide variety of applications, including solid oxide fuel cells, solid oxide electrolyzers, catalytic converters, and chemical/fuel production. In exsolution, metal cations are exsolved to the surface of a perovskite oxide solid solution under reducing conditions. The result is a perovskite backbone decorated with partially embedded metallic nanoparticles. The stability and anti-coking properties of exsolved nanoparticles have driven growing interest in exsolution materials. However, even after two decades of intense research, key open questions remain regarding exsolution's precise mechanism and, consequently, how to rationally engineer the properties of exsolution nanoparticles. This thesis aims to address these questions through a combination of experimental work and first-principles atomistic modelling with the long-term goal of accelerating the commercialization of exsolution materials. We first investigate the impact of perovskite composition on the properties of Ni nanoparticles exsolved from bulk SrTi₀.₉₄Ni₀.₀₆O₃₋ subscript δ. We adjust the makeup of the Sr site, adding dopants of varying valence and ionic radii as well as vacancies, and measure how these changes modulate the surface density of the exsolved nanoparticles. We then use density functional theory (DFT) calculations to explain the observed trends, finding that the energetics of cation surface segregation and surface reduction control nanoparticle nucleation kinetics. This work provides valuable new insights into the exsolution mechanism, and, for the first time, introduces a quantitative model capable of accurately predicting the experimental exsolution properties of given perovskite composition from first principles. Next, we extend this quantitative model to capture the influence of the exsolution conditions on the properties of Ni nanoparticles, this time focusing solely on Ni exsolution from bulk Sr₀.₈La₀.₁Ca₀.₁Ti₀.₉₄Ni₀.₀₆O₃₋ subscript δ. We first measure the dependence of nanoparticle density on exsolution temperature and oxygen partial pressure. We rationalize the empirical trends using the LaMer theory for nucleation and our model previously developed to predict composition effects. This achievement points towards the first-ever method for first-principles prediction of a generic perovskite composition’s exsolution properties under varying reducing conditions. Thus, we make a major step towards fully in silico design of exsolution materials, greatly increasing their commercial attractiveness. Finally, we develop a novel, highly efficient DFT methodology to predict Raman signatures of point defects and apply this methodology to interpret SrTi₀.₉₄Ni₀.₀₆O₃₋ subscript δ’s complex Raman spectrum. Based on empirical and DFT-derived Raman spectra, we characterize SrTi₀.₉₄Ni₀.₀₆O₃₋ subscript δ’s defect chemistry and local structure. Our findings are a vital first step towards using Raman spectroscopy to study and screen exsolution materials. More broadly, our computational methodology supercharges Raman spectroscopy as a tool to characterize local structure in a wide range of technologically relevant material systems.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Materials Science and Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• O'Leary, Willis

Advisors dc:contributor.advisor

• Rupp, Jennifer L. M.
• Tuller, Harry L.

Statement dc:rights

• Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-nd/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/158270

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/158270