Due to their spontaneous polarization, ferroelectric materials have a variety of applications in electronic, optical, and electromechanical devices. In addition, recent advances in atomic-level control of thin film growth techniques, including molecular beam epitaxy and pulsed laser deposition, have made it possible to grow ferroelectric thin films with low-dimensional features leading to the discovery of many new phenomena and functional properties stemming from the coupling between the ferroelectricity and the low-dimensional features. However, since the features are usually in nano- or atomic- size, conventional characterization techniques have low spatial resolutions cannot accurately resolve these tiny features. Herein, I reported a comprehensive atomic-scale characterization method to study the low-dimensional features in ferroelectric materials using advanced transmission electron microscopy (TEM) techniques, including in situ TEM, scanning TEM (STEM), 4-dimensional STEM (4D STEM), energy dispersive X-ray spectroscopy (EDS) and electron energy loss spectroscopy (EELS). This opens new opportunities for studying both the mechanisms for how macroscopic properties can emerge from atomic-scale phenomena and the fundamental physics of ferroelectricity.First, we systematically study the spontaneous polarization induced positive/negative charge accumulation at ferroelectric-insulator interface. Second, we show dislocation-assisted BiMnOx nanochannels embedded in SrTiO3/La0.67Sr0.33MnO3 thin films having diode-like behavior. Finally, we demonstrate superelasticity and domain switching of freestanding BiFeO3 films using in situ straining and biasing TEM, respectively. During the in situ straining experiment, the film shows an unprecedented tremendous lattice strain up to 34.4%, which is two orders of magnitude higher than their bulk counterparts and comparable to ductile metals.

Due to their intrinsic polarization, ferroelectric materials have a variety of applications in electronic, optical, and electromechanical devices. In addition, modern thin film growth techniques such as molecular beam epitaxy and pulsed laser deposition have made it possible to grow heterostructures with atomically sharp interfaces leading to the discovery of many new phenomena and functional properties stemming from the coupling between the ferroelectric and the substrate material. In the study of these thin films, transmission electron microscopy has been a powerful technique for high resolution structural and chemical characterization of these heterostructures. With the development of fast pixelated detectors, four-dimensional scanning transmission electron microscopy (4D STEM) has led to the emergence of new techniques for directly interrogating the electronic properties of ferroelectrics with atomic resolution. This opens new opportunities for studying both the mechanisms for how macroscopic properties can emerge from atomic scale electronic phenomena and the fundamental physics of ferroelectricity. In this work, new analysis techniques based on 4D STEM electric field and charge density imaging are developed and applied to reveal the electronic properties of ferroelectric heterostructures.

First, we systematically study the effect of sample thickness and electron probe defocus on the electric field measured in 4D STEM and demonstrate that the technique can be extended to samples up to 20 nm thickness. Next, new quantitative analysis techniques for 4D STEM charge density images are developed. These techniques are applied to a BiFeO3-SrTiO3 (ferroelectric-insulator) heterostructure, which reveals the local electronic properties of the interface. Through a combination of methods, we showed that there is charge accumulation at the interface due to an asynchronous change in the structural polarization and the charge distribution across the interface. Applying 4D STEM electric field imaging to PbTiO3-SrTiO3 superlattice, we found that asymmetric features in atomic scale images originate from the charge distribution in perovskite ferroelectrics and while nanometer-resolution images reveal the total electric field of the material system. Finally, an in-depth study of how Bader charge analysis, adapted for use with 4D STEM charge density images, can be leveraged to understand the bonding properties of PbTiO3. These results demonstrate the potential of 4D STEM for investigating the electronic properties of materials and provide new insights into the behavior of ferroelectric heterostructures.

Catalysis remains an important field of research that drives economical approaches for various energy conversion applications from natural resources. Industrial catalyzed reactions occur at the surface of heterogeneous catalysts where many different active sites exist. Any atom not at the surface is not directly used to drive chemical reactions. To improve efficiency, catalytic nanomaterials have shrunk to the nano and atomic scale, increasing the surface area/volume ratio. Traditional characterization methods for nanomaterials provide a large scale picture of overall changes but do not exhibit a high degree of spatial information. To that end, transmission electron microscopy (TEM) may be used to probe materials down to the scale of individual atoms through both imaging and spectroscopy. Specialty holders allow for replication of benchtop reactions with which to investigate changes to nanomaterials in situ. Here, in situ TEM was used to gain insights into a variety of chemical processes including bond cleavage and surface reduction of different nanomaterials.First, we used in situ TEM to observe the contraction of the inter-metal center distances upon heating of a Zr based metal-organic framework before tracking the chemical bond changes with vibrational electron energy loss spectroscopy (EELS). The in situ results were corroborate with ex situ samples to validate the results. Then, in situ TEM and EELS was used to spatially map the Ce3+ aggregation on the surface of Pt loaded ceria nanoparticles. The localization of the Ce3+ had remained an unanswered question prior. The surface reduction was seen to proceed in an irreversible fashion which was attributed to orientated attachment, a precursor step to sintering. Finally, in situ TEM was performed in a liquid environment analyzing the growth of nanobubbles and the dissolution of octahedral core-shell nanoparticles. Both nanomaterials exhibited stages of structural changes that correspond to size stability and atom migration, respectively. As seen with the variety of nanomaterials observed, in situ TEM gives insight to the various chemical processes that occur when replicating benchtop reactions.

In this master thesis research project, we synthesized the Pt:TiO2-B thin films as the anode material for lithium-ion batteries using the pulsed laser deposition (PLD) method, which is a totally waterless process. Considering the poor electronic conductivity of TiO2-B, we aim to upgrade the electrochemical performance of TiO2-B by integrating Pt into its matrix to improve its electronic and ionic conductivity. By varying the oxygen partial pressure during the PLD synthesis, we obtained the Pt:TiO2-B thin film with different Pt content of 1.5%, 6% and 12% revealed by Rutherford backscattering spectrometry (RBS) analysis. Materials characterization techniques, including XRD and TEM, were used to verify thin films’ composition and structure. The as-prepared Pt:TiO2-B thin films were then used to assemble full cells of lithium-ion batteries (LIBs) and examined by chronopotentiometry and cyclic voltammetry tests. The result indicates that Pt:TiO2-B thin films present excellent electrochemical performance with high rate capacity and cycling stability, which reveals its promising application as anode materials for LIBs, and Pt dopant plays an important role in upgrading the TiO2-B electrochemical performance. This project suggests using PLD to synthesize TiO2 based materials doped with conductive substances to improve its electrochemical conductivity is an effective and simple way to obtain high-performance anode materials for lithium-ion batteries.

Oxide solid electrolytes (OSEs) have the potential to achieve improved safety and energy density for lithium-ion batteries, but their high grain-boundary (GB) resistivity generally is a bottleneck. In the well-studied perovskite oxide solid electrolyte, Li3xLa2/3-xTiO3 (LLTO), the ionic conductivity of grain boundaries is about three orders of magnitude lower than that of the bulk. In contrast, the related Li0.375Sr0.4375Ta0.75Zr0.25O3 (LSTZ) perovskite exhibits low grain boundary resistivity for reasons yet unknown. Here, we use aberration-corrected scanning transmission electron microscopy and spectroscopy, along with an active learning moment tensor potential, to reveal the atomic scale structure and composition of LSTZ grain boundaries. Vibrational electron energy loss spectroscopy is applied for the first time to reveal atomically resolved vibrations at grain boundaries of LSTZ and to characterize the otherwise unmeasurable Li distribution therein. We find that Li depletion, which is a major reason for the low grain boundary ionic conductivity of LLTO, is absent for the grain boundaries of LSTZ. Instead, the low grain boundary resistivity of LSTZ is attributed to the formation of a nanoscale defective cubic perovskite interfacial structure that contained abundant vacancies. Our study provides new insights into the atomic scale mechanisms of low grain boundary resistivity.

To further improve the total ionic conductivity of LSTZ, we explore the wide compositional space of compositionally complex ceramics (CCCs). Herein, we propose and demonstrate strategies for tailoring CCCs via a combination of non-equimolar compositional designs and control of grain boundaries and microstructures. A class of compositionally complex perovskite oxides (CCPOs) with improved lithium ionic conductivities beyond the limit of conventional doping was discovered. For example, we demonstrate that the ionic conductivity can be improved by >60% in (Li0.375Sr0.4375)(Ta0.375Nb0.375Zr0.125Hf0.125)O3-d compared with the (Li0.375Sr0.4375)(Ta0.75Zr0.25)O3-d baseline that is synthesized using the same conditions. Furthermore, the ionic conductivity can be improved by another >70% via air quenching, achieving >270% of the LSTZ. Notably, we demonstrate GB enabled conductivity improvements via both promoting grain growth and altering GB structures through compositional designs and processing. In a broader perspective, this work suggests new routes for discovering and tailoring CCCs for energy storage and many other applications. In comparison with the ionic conductivities of the other compositions we have studied, i.e., (Li0.375Sr0.4375)(Ta0.75Zr0.125Hf0.125)O3, (Li0.375Sr0.4375)(Ta0.375Nb0.375Hf0.25)O3, (Li0.375Sr0.4375)(Ta0.375Nb0.375Zr0.25)O3, (Li0.375Sr0.4375)(Ta0.375Nb0.375Zr0.125Hf0.125)O3, and (Li0.375Sr0.4375)(Ta0.75Zr0.25)O3, the ionic conductivity of (Li0.375Sr0.4375)(Nb0.75Zr0.125Hf0.125)O3 (LSNZH) is at least one order of magnitude lower. This abnormally low total ionic conductivity intrigued us to investigate its microstructure. In depth investigation of periodic lattice and none-periodic features is crucial for understanding Li-ion transport in crystalline solid electrolytes. Identifying the crystal lattices of new Li-ion conductors has been a standard practice in physical science and is valuable for both pure and applied science. In comparison, the atomistic mechanisms that control the Li-ion migration of many non-periodic features are not as well studied. Herein, we discover a new atypical, ordered structure and a new self-interstitial point defect in solid electrolyte (Li0.375Sr0.4375)(Nb0.75Zr0.125Hf0.125)O3, and the names “Lee-Ko phase” and “defected Lee-Ko phase” are coined to describe them. The Lee-Ko phase degrades bulk ionic conductivity by its ordered structure. It also reduces the grain boundary ionic conductivity by creating a gradual change in composition at around the phase boundaries. In conclusion, both the Lee-Ko phase and defected Lee-Ko phase hinder Li-ion transport and are key factors contributing to the low total ionic conductivity of LSNZH perovskite solid electrolyte. Our discoveries highlight the importance of thoroughly investigating crystal lattices and none-periodic features and motivates similar studies for other solid electrolytes.

Encapsulating a permeable layer of oxide support on metal catalysts, as a type of strong metal-support interaction (SMSI), is often adapted to design heterogeneous catalysts with enhanced reactivity and catalytic activity. The success of such a design highly relies on the thickness of the encapsulation layer, often only one or two atomic layers, and its chemical composition and structure, which is highly delicate given its thickness and complex chemical environment. Precisely detecting such a trace layer and determining its chemistry however, is challenging. Scanning transmission electron microscopy (STEM), the most commonly used technique for such analysis, also suffers from a low signal strength due to the thickness and the electron beam sensitivity of the surface encapsulation layer. This can lead to the potential misinterpretation or overlooking of the encapsulation signal. Here, using Pd-TiO2 as a prototype system, we develop and demonstrate an unsupervised machine learning method that allows us to reveal the presence and chemical information of the SMSI encapsulation layer that is otherwise hidden in STEM-electron energy loss spectroscopy (EELS) datasets. This method not only provides a robust tool for the analysis of trace SMSI in catalysts, but is generally applicable to any materials and spectroscopy datasets of any material systems where revealing a trace signal is critical.

Thermal properties in nanostructured materials are dominated by atomic scale and nanoscale inhomogeneities in crystal lattices. However, tools for studying nanoscale thermal properties have relied on theoretical frameworks and optical measurements of defect aggregates. Vibrational spectroscopy in a transmission electron microscope offers unprecedented access into nanoscale phonon physics. We have studied a SiGe quantum dot (QD) superlattice which is a strong candidate for high temperature thermoelectrics. These dome shaped, SiGe alloy QDs are bounded by a sharp and gradual interface due to its nonuniform alloy distribution. With a 6mev (~50 cm-1) energy resolution via a monochromated beam, we map Si optical phonons in a single SiGe QD. We find a composition-induced strain in the alloy matrix in the QD nanostructure that manifests as a redshift in the phonon energy that is exactly consistent with the nonuniform composition distribution. More notably, we find an accumulation of non-equilibrium phonons below the sharp interface. To investigate the dynamics of this further, I developed a new technique called differential momentum mapping (DPM) that allows for the mapping of propagating phonon modes. With this, we mapped phonon group velocity vectors showing unequivocally a drastically larger reflection of phonons from the sharp interface than the gradual one. For the first time, dynamical thermal processes at the nanoscale have been imaged.

This vibrational EELS capability is then applied to a ferroelectric-insulator system: BiFeO3/TbScO3 (BFO/TSO). Our goal for this study was to identify relationships between the phonon structure and ferroelectricity in BFO. Ferroelectric domain walls (DW) and the emergence of free charge gases at the interface offered us an excellent opportunity to also investigate nanoscale electron-phonon dynamics. We discovered that DW-localized shear strain due to alternating polarization, causes phonons to propagate anisotropically by utilizing the DPM technique developed in the previous work. Furthermore, the free charge gasses at the interface also break phonon symmetry but due to accumulated net charge rather than structural distortions. This work provides a nanoscale angle-resolved picture for the decrease in cross-DW and cross-interface thermal conductivity. Uncovering this physics is fundamental to the well-informed fabrication of ferroelectric-based materials and proper design of ferroelectric memories.

To enable trustable data analysis of EELS data, a data workflow stack has been developed with the following key aspects in mind: accuracy, efficiency, transparency, and useability. With the advent of advanced detectors and electron spectroscopy techniques, demand for intelligent, high throughput, processing has sky-rocketed, but the lack of programming and data analysis expertise has been a high barrier to entry. The developed modules serve to mitigate this problem by taking advantage of relatively low-level APIs that interface with data and provide scientific analysis tools and wrapping them in high-level modules designed for user-specific workflows. An example workflow for vibrational EELS includes aligning of the zero-loss peak (ZLP), background subtracting the vibrational signal, using PCA to reconstruct the data in a lower dimensional representation, fitting prominent peaks, and finally visualizing the data in the form of line plots or contour maps. This framework also includes tools for analyzing the fine structure of core-loss edges, bandgap measurements, and a general set of tools including deconvolution, clustering, and filtering. Because entire blocks in the workflow are condensed into single lines of code, these high-level modules can aid non-coders to process their data using innovative data analysis techniques

Ammonia (NH3) is a critically important molecule, necessary to produce fertilizers and is also used in a variety of household chemical and as a precursor in pharmaceuticals. Additionally, NH3 has a relatively large energy density and can be liquified at mild conditions, making it appealing as not only a chemical feedstock but also as an energy storage vector. Unfortunately, the now century old Haber Bosch (HB) process remains the only way to produce NH3 on a large scale. The HB process is one of the most energy intensive and carbon dioxide emitting processes and is therefore essential to decarbonize as we transition into a greener future. The electrochemical transformation of reactive nitrogen-species is a promising, carbon neutral pathway for NH3 synthesis. Typical approaches utilize di-nitrogen (N2) as a reactant; however, the success of these systems remains unproven. Utilizing a more oxidized form of nitrogen, nitrate (NO3-), presents several advantages such as increased solubility in aqueous electrolytes and favorable adsorption energies, helping to increase the NO3- to NH3 selectivity. The electrochemical nitrate reduction reaction (NO3RR) is a complex 8e- transfer reaction, where the reaction pathway and participation of reaction intermediates is largely unknown. This dissertation addresses these issues by fundamental studies partitioning the reaction pathway over distinct catalytic sites in a bi-metallic system. Then moving to develop a series of physically relevant NO3/NO2RR activity descriptors. Finally, the knowledge gained from the fundamental studies is applied to create an active particle-active support catalyst system, achieving the NO3RR to NH3 at industrial current densities. Specifically, the studies are outlined below. i) Highly durable and selective Fe-and Mo-based atomically dispersed electrocatalysts for nitrate reduction to ammonia via distinct and synergized NO2–pathways An atomically dispersed bi-metallic FeMo-N-C catalyst was developed and was shown computationally and experimentally that the Fe-Nx sites favor NO2- to NH3 conversion, while the Mo-Nx sites favor NO3- to NO2- conversion. These sites were synergized to achieve a NO3- to NH3 efficiency of 94%. Additionally, DFT uniquely demonstrated that over highly oxyphilic sites, such as Mo-Nx the real active site during the reaction is *O-Mo-Nx and can simultaneously adsorb multiple intermediates.

ii) Elucidating electrochemical nitrate and nitrite reduction over atomically dispersed transition metal sitesA library of 3d, 4d, 5d and f-metal atomically dispersed Metal-Nitrogen-Carbon catalysts were synthesized and extensively characterized for their atomically dispersed nature and M-Nx coordination. Electrochemical NO3RR and NO2RR were performed to obtain experimental activity descriptors. DFT was used to generate a series of computational activity descriptors. The experimental and computational activity descriptors were correlated to develop a set of physically relevant computational descriptors, such that the NO3/NO2RR activity of M-N-C catalysts could be accurately predicted with a simple descriptor. Additionally, isotopic doping experiments revealed the complex NO2- production consumption mechanism over the M-N-C catalysts, confirming the 2e- + 6e- transfer pathway rather than the commonly assumed direct 8e- pathway.

iii) Synergizing γ-Fe2O3 nanoparticles on single atom Fe-N-C for nitrate reduction to ammonia at industrial current densities An active particle-active support catalyst system was synthesized by reducing γ-Fe2O3 nanoparticles onto an atomically dispersed Fe-N-C support. The catalyst system was characterized electrochemically to demonstrate the increase in NO3RR performance of the γ-Fe2O3/Fe-N-C system over a γ-Fe2O3/XC72 system. Uniquely, the γ-Fe2O3/Fe-N-C system showed potential independent behavior on the FENH3, allowing for a reductive potential up to -1.2 V vs. RHE, while maintaining a 100% FENH3 and a high YieldNH3 over 9 mmol hr-1 cm-2. An economic analysis invesitagting the levelized cost of NH3 revealed it is more beneficial to reduce the levelized cost of NH3 to operate at a higher over potential of -1.0V at a lower energy efficiency, with a very high NH3 partial current density (1.3 A/cm2). Post-mortem XPS revealed that during the pre-reduction activation step, a surface layer of Fe2+/Fe0 is formed, resulting in the ultra-high NO3RR activity observed.