Date of Completion

5-21-2018

Embargo Period

6-28-2019

Keywords

Density Functional Theory, Perovskite Ferroelectrics, Landau-Devonshire Thermodynamic Potentials, Lead Free, Lone-Pair Active, Multiscale Modeling, Nano-Composites, Finite Element Analysis

Major Advisor

Serge M. Nakhmanson

Associate Advisor

S. Pamir Alpay

Associate Advisor

George A. Rossetti Jr.

Field of Study

Materials Science and Engineering

Degree

Doctor of Philosophy

Open Access

Open Access

Abstract

Ferroelectrics are an important class of materials that exhibit rich functional behavior and are being actively investigated for a variety of technological applications. Multiscale modeling of ferroelectric materials is necessary for accelerating the design and discovery of the next generation of functional materials and nanostructures. In this dissertation, we study the properties of perovskite based ferroelectric systems with the help of first principles calculations, as well as use the results of these calculations to develop coarse-grained descriptions of ferroelectric behavior. In particular we elucidate the electronic underpinnings of functional behavior arising from polarization rotations in classical and layered perovskite oxides containing electron lone-pair active ions, such as Pb2+ and Sn2+. We then devise a general approach for fitting the Landau-Devonshire theory based thermodynamic potentials from first principles for these compounds. The parameterized Landau potential for PbTiO3, that we use as a test case, has the ability to accurately predict dielectric, piezoelectric and thermal properties at finite temperature as compared with the results produced by a popular potentials of the same form fitted from the experimental data. The parametrized potential was also applied to map the phase diagram under simple elastic boundary conditions - giving comparable results with the previous results. In closing, we demonstrate how such coarse-grained thermodynamic energy descriptions can be used to study the properties of ferroelectric nanostructures at mesoscale, e.g., to evaluate the influence of size, shape and morphology on their functional behavior.

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