First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design

As the demand for clean and renewable energy sources continues to grow, much attention has been given to solid oxide fuel cells (SOFCs) due to their efficiency and low operating temperature. However, the components of SOFCs must still be improved before commercialization can be reached. Of particula...

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Main Author: Ismail, Arif
Language:en
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10393/20198
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-OOU.-en#10393-201982013-01-11T13:33:11ZFirst Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte DesignIsmail, Arifcomputational chemistrymaterials sciencesolid electrolytesionic conductivitydiffusionsolid oxide fuel cellsdensity functional theorysimulationenergyAs the demand for clean and renewable energy sources continues to grow, much attention has been given to solid oxide fuel cells (SOFCs) due to their efficiency and low operating temperature. However, the components of SOFCs must still be improved before commercialization can be reached. Of particular interest is the solid electrolyte, which conducts oxygen ions from the cathode to the anode. Samarium-doped ceria (SDC) is the electrolyte of choice in most SOFCs today, due mostly to its high ionic conductivity at low temperatures. However, the underlying principles that contribute to high ionic conductivity in doped ceria remain unknown, and so it is difficult to improve upon the design of SOFCs. This thesis focuses on identifying the atomistic interactions in SDC which contribute to its favourable performance in the fuel cell. Unfortunately, information as basic as the structure of SDC has not yet been found due to the difficulty in experimentally characterizing and computationally modelling the system. For instance, to evaluate 10.3% SDC, which is close to the 11.1% concentration used in fuel cells, one must investigate 194 trillion configurations, due to the numerous ways of arranging the Sm ions and oxygen vacancies in the simulation cell. As an exhaustive search method is clearly unfeasible, we develop a genetic algorithm (GA) to search the vast potential energy surface for the low-energy configurations, which will be most prevalent in the real material. With the GA, we investigate the structure of SDC for the first time at the DFT+U level of theory. Importantly, we find key differences in our results from prior calculations of this system which used less accurate methods, which demonstrate the importance of accurately modelling the system. Overall, our simulation results of the structure of SDCagree with experimental measurements. We identify the structural significance of defects in the doped ceria lattice which contribute to oxygen ion conductivity. Thus, the structure of SDC found in this work provides a basis for developing better solid electrolytes, which is of significant scientific and technological interest. Following the structure search, we perform an investigation of the electronic properties of SDC, to understand more about the material. Notably, we compare our calculated density of states plot to XPS measurements of pure and reduced SDC. This allows us to parameterize the Hubbard (U) term for Sm, which had not yet been done. Importantly, the DFT+U treatment of the Sm ions also allowed us to observe in our simulations the magnetization of SDC, which was found by experiment. Finally, we also study the SDC surface, with an emphasis on its structural similarities to the bulk. Knowledge of the surface structure is important to be able to understand how fuel oxidation occurs in the fuel cell, as many reaction mechanisms occur on the surface of this porous material. The groundwork for such mechanistic studies is provided in this thesis.2011-09-07T18:53:29Z2011-09-07T18:53:29Z20112011-09-07Thèse / Thesishttp://hdl.handle.net/10393/20198en
collection NDLTD
language en
sources NDLTD
topic computational chemistry
materials science
solid electrolytes
ionic conductivity
diffusion
solid oxide fuel cells
density functional theory
simulation
energy
spellingShingle computational chemistry
materials science
solid electrolytes
ionic conductivity
diffusion
solid oxide fuel cells
density functional theory
simulation
energy
Ismail, Arif
First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
description As the demand for clean and renewable energy sources continues to grow, much attention has been given to solid oxide fuel cells (SOFCs) due to their efficiency and low operating temperature. However, the components of SOFCs must still be improved before commercialization can be reached. Of particular interest is the solid electrolyte, which conducts oxygen ions from the cathode to the anode. Samarium-doped ceria (SDC) is the electrolyte of choice in most SOFCs today, due mostly to its high ionic conductivity at low temperatures. However, the underlying principles that contribute to high ionic conductivity in doped ceria remain unknown, and so it is difficult to improve upon the design of SOFCs. This thesis focuses on identifying the atomistic interactions in SDC which contribute to its favourable performance in the fuel cell. Unfortunately, information as basic as the structure of SDC has not yet been found due to the difficulty in experimentally characterizing and computationally modelling the system. For instance, to evaluate 10.3% SDC, which is close to the 11.1% concentration used in fuel cells, one must investigate 194 trillion configurations, due to the numerous ways of arranging the Sm ions and oxygen vacancies in the simulation cell. As an exhaustive search method is clearly unfeasible, we develop a genetic algorithm (GA) to search the vast potential energy surface for the low-energy configurations, which will be most prevalent in the real material. With the GA, we investigate the structure of SDC for the first time at the DFT+U level of theory. Importantly, we find key differences in our results from prior calculations of this system which used less accurate methods, which demonstrate the importance of accurately modelling the system. Overall, our simulation results of the structure of SDCagree with experimental measurements. We identify the structural significance of defects in the doped ceria lattice which contribute to oxygen ion conductivity. Thus, the structure of SDC found in this work provides a basis for developing better solid electrolytes, which is of significant scientific and technological interest. Following the structure search, we perform an investigation of the electronic properties of SDC, to understand more about the material. Notably, we compare our calculated density of states plot to XPS measurements of pure and reduced SDC. This allows us to parameterize the Hubbard (U) term for Sm, which had not yet been done. Importantly, the DFT+U treatment of the Sm ions also allowed us to observe in our simulations the magnetization of SDC, which was found by experiment. Finally, we also study the SDC surface, with an emphasis on its structural similarities to the bulk. Knowledge of the surface structure is important to be able to understand how fuel oxidation occurs in the fuel cell, as many reaction mechanisms occur on the surface of this porous material. The groundwork for such mechanistic studies is provided in this thesis.
author Ismail, Arif
author_facet Ismail, Arif
author_sort Ismail, Arif
title First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
title_short First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
title_full First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
title_fullStr First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
title_full_unstemmed First Principles and Genetic Algorithm Studies of Lanthanide Metal Oxides for Optimal Fuel Cell Electrolyte Design
title_sort first principles and genetic algorithm studies of lanthanide metal oxides for optimal fuel cell electrolyte design
publishDate 2011
url http://hdl.handle.net/10393/20198
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