Layered lithium transition metal oxides represent a major type of cathode materials that are widely used in commercial lithium-ion batteries. Nevertheless, these layered cathode materials suffer structural changes during electrochemical cycling that could adversely affect the battery performance. Clear explanations of the cathode degradation process and its initiation, however, are still under debate and are not yet fully understood. In this thesis, the cycling-induced chemical and structural evolution of LiNi1/3Mn1/3Co1/3O2 (NMC) and high-energy Li1.2Ni0.13Mn0.54Co0.13O2 (HENMC) cathodes are investigated in details using state-of-the-art electron microscopy techniques combined with other bulk measurements to uncover the mechanisms at the source of cell deterioration. / Thesis / Doctor of Philosophy (PhD)

Graphene and its functionalized derivatives, such as nitrogen-doped graphene, have recently become a popular substrate material for the proton exchange membrane fuel cell (PEMFC) due to its enhanced electrical conductivity, electrochemical stability, and increased surface area when compared to the conventional, carbon black. In order to further develop the alternative fuel industry, the Pt catalyst within the PEMFC must also be considered. Single Pt atoms have a higher surface area to volume ratio when compared to nanoparticles, thus offering the potential to create a more affordable and efficient PEMFC. In this thesis, electrode materials comprising single Pt atoms and clusters, produced using atomic layer deposition (ALD) on various C derivatives, including graphene, N-doped graphene, carbon nanotubes (CNTs), and N-doped CNTs (NCNTs) are investigated through the utilization of aberration corrected transmission electron microscopy. Structural and chemical analysis was performed on thermally exfoliated N-doped graphene and CVD-produced graphene that was exposed to N+ ion sources. It was determined that the thermally exfoliated N-doped graphene maintained the short-range order of the graphene lattice; however, local inhomogeneities existed for the total N concentration, and the specific N-dopants within and between graphene sheets. More importantly, Pt atoms and clusters were observed and determined to be primarily stabilized at the edge of the N-doped graphene sheets. The stabilization of the Pt atoms and clusters resulted in a significantly higher mass and specific activity for the hydrogen evolution reaction, when compared to the use of a graphene substrate and Pt nanoparticles on C black. The N+ ion implantation in the CVD graphene showed the incorporation of N-dopants; however, electron energy loss spectroscopy revealed structural damage to thin sheets. NCNTs were also characterized in this thesis as possible gas containers, and as a substrate material to examine the effects of varying ALD conditions. It was determined that the NCNTs were an effective N2 gas conduit, wherein a decreasing pressure was observed with an increase to the inner diameter of the nanotubes. Using similar NCNTs, the effect of dosing time, temperature, and substrate on the Pt size were analyzed using ALD. While no singular condition resulted in the sole production of single Pt atoms, modifying both the substrate and dosing time were shown to provide the greatest potential for producing individual Pt atom catalysts. / Thesis / Doctor of Philosophy (PhD)

Building on the recent advances in computer vision with convolutional neural networks, we have built SpectralNet, a spectroscopy-optimized convolutional neural network architecture capable of classifying spectra despite large temporal (i.e. translational, chemical, calibration) shifts. Present methods of measuring the local chemical environment of atoms at the nano-scale involve manual feature extraction and dimensionality reduction of the original signal such as: using the peak onset, the ratio of peaks, or the full-width half maximum of peaks. Convolutional neural networks like SpectralNet are able to automatically find parts of the spectra (i.e. features) of the spectra which maximally discriminate between the classes without requiring manual feature extraction. The advantage of such a process is to remove bias and qualitative interpretation in spectroscopy analysis which occurs during manual feature extraction. Because of this automated feature extraction process, this method of spectroscopy analysis is also immune to instrument calibration differences since it performs classification based on the shape of the spectra. Convolutional neural networks are an ideal statistical classifier for spectroscopy data (i.e. time-series data) due to its shared weighting scheme in neural network weights which is ideal for identifying local correlations between adjacent dimensions of the time-series data. Over 2000 electron energy loss spectra were collected using a scanning transmission electron microscope of three oxidation states of Mn. SpectralNet was trained to learn the differences between them. We prove generalizability by training SpectralNet on electron energy loss spectroscopy data from one instrument, and test it on a variety of reference spectra found in the literature with perfect accuracy. We also test SpectralNet against a wide variety of high noise samples which a trained human spectroscopist would find incomprehensible. We also compare other neural network architectures used in the literature and determine that SpectralNet, a dense-layer free neural network, is immune to calibration differences whereas other styles of network are not. / Thesis / Master of Applied Science (MASc) / Spectroscopy is the study of the interaction between photons or electrons and a material to determine what that material is made of. One advanced way to make accurate measurements down to the atomic scale is to use high energy electrons in a transmission electron microscope. Using this instrument, a special type of photograph can be taken of the material (a spectrograph or spectrum) which is detailed enough to identify which kinds of atoms are in the material. The spectrographs are very complicated to interpret and the human eye struggles to find patterns in noisy and low resolution data. Depending on which instrument that the spectrographs are taken on, the resulting spectrograph will also change which adds extra difficulty. In this study, advanced algorithms are used to identify which types of atoms can be identified in the noisy signal from the spectrograph regardless of which instrument is used. These algorithms (convolutional neural networks) are also used in self-driving cars for a similar task of identifying objects whereas in this study we use it for identifying atoms.

Human bone tissue has an inherent hierarchical structure, which is integral to its material properties. It is primarily composed of a collagen fiber matrix that is mineralized with hydroxyapatite. A comprehensive understanding of bone and the linkages between structural and cellular organization is imperative to developing fundamental knowledge that can be applied to better our understanding of bone disease manifestations and its interaction with implant devices. Herein, this thesis investigated non-traditional methods for evaluating bone structure across the nano- and meso-length scales. Firstly, due to the inhomogeneous organization of collagen fibrils and mineral platelets of bone ultrastructure, a suitable methodology for the investigation of both phases needed to be generated. In this work, focused ion beam (FIB) microscopy was employed to create site-specific scanning transmission electron microscopy (STEM) lift-outs of human osteonal bone that could be visualized with correlatively with STEM and small angle X-ray scattering (SAXS). Samples were successfully characterized using both techniques, and minimal visual damage was induced during data acquisition. This work is the first to demonstrate the potential for bone to be investigated correlatively using both STEM and SAXS. Secondly, this work is the first to employ a dual-beam plasma FIB (PFIB) equipped with a scanning electron microscope (SEM), to investigate bone tissue across the mesoscale. This equipment enables large volume three-dimensional (3D) imaging at nanoscale resolution across larger mesoscale volumes. This thesis aimed to reduce ion beam-based artifacts, which presents as curtain-like features by adjusting the composition of protective capping layers. Subsequently, large volume tomograms of bone tissue were acquired, demonstrating the effectiveness of the PFIB to reveal mesoscale features including the cellular network of bone tissue. Overall, this thesis has developed methods that allow for the application of advanced microscopy techniques to enhance the understanding of bone tissue across the nanoscale and mesoscale. / Thesis / Master of Applied Science (MASc) / Bone tissue has a unique structure that perplexes both biologists and materials scientists. The hierarchical structure of bone has garnered the interest of materials scientists since the body’s skeletal strength and toughness are governed by the nanoscale (millionth of centimetres) to macroscale (centimeters) organization of bone. In this work, the intricate organization of bone is investigated using advanced electron and ion beam microscopy techniques, which achieve high-resolution imaging of bone structure. Firstly, this work developed a sample preparation workflow to correlate electron and X-ray imaging of the same bone tissue. Secondly, this work was the first to apply serial-sectioning plasma focused ion beam tomography to human bone tissue to investigate its structure at high resolution across micron-sized volumes. Here, previously unexplored methodologies to image bone are demonstrated with the hopes of applying such techniques to investigate healthy and pathological bone tissue in the future.

Electron Ptychography is a technique to retrieve the phase information of the medium through which the electron wave travels in a Transmission Electron Microscope (TEM). Phase calculation is carried out by acquiring an oversampled dataset of diffraction patterns from the sample and execution of a Fourier-based mathematical solution or algorithm using the collected dataset of intensity patterns. The phase of the electron wave contains valuable information about the structure of the material under study. In this contribution, we provide a scientific background necessary for understanding the phase calculation method, examine the capabilities and limitations of the Electron Ptychography in experimental setup and introduce two novel methods to increase the signal to noise ratio by using the same dose budget used in a classic Ptychography experiment. / Thesis / Master of Applied Science (MASc)

Bioindicators of the nanoscale structural quality of bone were investigated using ion milling and transmission electron microscopy of osteoporotic bone from human female donors. / Bone is a complex hierarchical biomaterial constantly undergoing remodeling events initiated by cell signaling and fulfilled by migratory bone cells. In osteoporosis, a multitude of signaling factors cause bone resorption to proceed quicker than bone reformation, resulting in a lower bone mineral density (BMD) and porosity as seen by thinning of the cortex and trabeculae. However, the structural motifs of these altered regions of the skeleton have not been understood on the nanoscale. In this thesis, transmission electron microscopy (TEM) was used with an image analysis technique termed nanomorphometry, developed to enable the measurement of nanoscale structural features in human bone. Several nanoscale bone quality bioindicators relevant to the collagen fibrils and bone mineral (mineral lamellae, ML) components were defined and tested (collagen fibril diameter, interfibrillar spacing, ML thickness & ML stack thickness) among two donor cohorts of post-menopausal osteoporotic female patients and age- and sex-matched controls. In one cohort, the anatomical region investigated was the intertrochanteric crest of the femur, while in the second, the femoral neck was studied. The bone sections were prepared using an ion milling workflow yielding electron-transparent views of the bone ultrastructure. Blinded image analysis of the ultrastructure revealed that in both cohorts, the thickness of the MLs was significantly larger in osteoporotic samples versus their controls. In the former cohort, it was found that anti-resorptive drug use in the treated group did not return the ML thickness back to control levels. In the latter cohort, the ML thickness correlated more closely with the proximal femur bone mineral density (BMD) than the age of the patient. These findings suggest that the morphology of the nanoscale mineral phase is affected by osteoporosis, an effect indirectly observed by other techniques, and warrants further exploration into the implications of this effect on bone quality, fragility and strength. / Thesis / Master of Applied Science (MASc) / Human bone is a biomaterial with many levels of organization from the macroscale down to the nanoscale. The material consists of roughly 30 weight % organic components (collagen, non-collagenous proteins) and 67 weight % inorganic components (calcium phosphate minerals) deposited by bone cells. Osteoporosis is a bone disease commonly associated with increased bone porosity and bone fragility. In this study, the effect of osteoporosis on the nanoscale structure of bone was directly imaged and investigated using transmission electron microscopy (TEM). Two advanced ion milling techniques (broad beam and focused ion beam) were used to thin the bone specimens for TEM. Bioindicators relating to the structure and size of collagen and mineral components in osteoporotic versus control bone were quantified in an unbiased image analysis workflow. Findings indicated an increase in the thickness of poly-crystalline bone mineral lamellae in the nanoscale structure of human osteoporotic bone from two human donor cohorts.

The characterization of the material’s deformation is nowadays common in transmission electron microscopy. The ability to resolve the crystalline lattice enables the strain to be linked with the deformation of the crystal unit cells. Imaging the crystal unit cells imposes the sampling scheme to oversample the resolved crystal periodicities and, thus, limits the field of view (FOV) of the micrograph. Therefore, alternative methods were developed (electron diffraction and holography) to overcome the FOV limitation. The method presented in this thesis is part of the large FOV challenge. Its principle is based on the coherent interference of the sampling grid with the crystalline lattices of the material in scanning transmission electron microscopy (STEM). The interference results to a set of Moiré fringes embedding the structural properties of the material such as a strain field. The STEM Moiré hologram (SMH) formation can be elegantly described using the concept of Moiré sampling in STEM imaging. The STEM Moiré fringes reveals to be undersampling artefacts commonly known as aliasing artefacts. The SMH is, therefore, violating the sampling theorem and is not a proper representation of the crystal unit cells. However, an oversampled representation can be recovered from the SMH using a set of prior knowledge. The SMH becomes suitable to characterize the 2D strain field giving birth to a new dedicated method, called STEM Moiré GPA (SMG), that is using the Geometric Phase Analysis method on the SMH directly. After detailing the theory of SMG, the technique is validated experimentally by comparing it to other strain characterization methods and to Finite Element Method simulations. The characteristics of SMG (resolution, precision and accuracy) and its limits are then detailed. Finally, the SMG method is applied on semiconductor devices to highlight the typical capabilities of the technique. / Thesis / Doctor of Philosophy (PhD)

The acidic, non-oxidative dissolution of galena nanocrystals has been studied using both microscopic and wet-chemical methods. The effects of particle size, shape, aggregation state, and grain proximity on dissolution rates were investigated. Nearly monodisperse galena nanocrystals with an average diameter of 14.4 nm and a truncated cubic shape were synthesized. In the dissolution experiments of dispersed nanocrystals, galena nanocrystals attached on the surface of a TEM grid were exposed to deoxygenated HCl solutions (pH 3) at 25 °C. Capping groups on nanocrystals were removed via a washing process, and chemistry of nanocrystals was examined using X-ray photoelectron spectroscopy (XPS). The evolution of the size and shape of the pre- and post-dissolution nanocrystals were studied using transmission electron microscopy (TEM), and the dissolution rate was calculated directly according to the size shrinking of galena nanocrystals. To assess the size effect, galena microcrystals (~ 3 μm) were synthesized and dissolved under similar conditions to the dispersed nanocrystals. The results showed that the nanocrystals dissolved at a surface area normalized rate of one order of magnitude faster than the microcrystals. In addition, dissolution rate is orientationdependent on a single nanocrystal. High-resolution TEM (HRTEM) images indicated the {111} and {110} faces dissolve faster than {100} faces on galena nanocrystals, rationalized by the average coordination number of ions on each of these faces. To assess the aggregation effect, dissolution experiments of aggregated galena nanocrystals were conducted using a wet-chemical method, and the results were compared with the rates of microcrystals and dispersed nanocrystals. These experiments showed that the rate of aggregated nanocrystals is in the same order of magnitude as the rate of microcrystals, but one order of magnitude smaller than that of dispersed nanocrystals. Finally, the effect of the close proximity between nanocrystals on dissolution was observed by HRTEM. Dissolution was greatly inhibited on nanocrystal surfaces that were closely adjacent (1-2nm, or less) to other nanocrystals, which is probably relevant to the slow dissolution of aggregated nanocrystals. The dissolution phenomena of galena nanocrystals observed in this study is likely important for understanding the environmental fate and behavior of nanoparticles in aquatic systems. / Ph. D.

Magnetic nanoparticles are of considerable interest owing to their potential applications in biotechnology and the magnetic recording industry. Iron oxides have received much attention owing to their oxidative stability and biocompatibility; however, other transition metals and their alloys are also under investigation. Cobalt has one of the largest magnetic susceptibilities of these materials, but it readily oxidizes upon exposure to air resulting in antiferromagnetic oxide. Hence, coating cobalt nanoparticles with an oxygen-impermeable sheath would confer numerous benefits. Cobalt nanoparticles were prepared by the thermolysis of dicobalt octacarbonyl in two block copolymer micellar systems, wherein the copolymers were precursors to graphite or silica. Subsequent heat treatment of the samples at 600-700oC was conducted to condense the polymer coating around the cobalt nanoparticles and form oxygen impervious graphite or silica sheaths. Magnetic and structural characterization of these novel materials afforded pertinent information about their physical properties. Magnetic susceptometry indicated that the graphite coated cobalt nanoparticles resisted oxidation for over one year. The silica coated cobalt nanoparticles had high saturated specific magnetic moments, but the coatings were brittle and grinding the particles resulted in oxidation over time. Transmission electron microscopy (TEM), high-resolution TEM (HRTEM) and energy-filtered TEM (EFTEM) were employed to study particle size and structural differences of the cobalt nanoparticles before and after heat treatment. The mean particle size and size distribution increased for the graphite coated cobalt particles, due to particle sintering at 700oC. In the silica coated cobalt nanoparticle system, the mean particle size increased when the sample was heat-treated at 600oC leading to a bimodal distribution. This bimodal distribution was explained by a fraction of the particles sintering, while others remained discrete. When the silica system was heat treated at 700oC, the particle size and size distribution remained similar to those of the pre-heat-treated sample, indicating that no sintering had taken place. The rapid pyrolysis of the polymer at 700oC may serve to lock the cobalt nanoparticles into a silica matrix, thus preventing them from coming into contact with one another and sintering. Several diffraction techniques (selected area electron diffraction (SAD), nano-beam electron diffraction (NBD) and x-ray diffraction (XRD)) were used to probe the crystal structure of graphite and silica coated cobalt nanoparticles, which was determined to be predominantly face-centered cubic. Anisotropic magnetic nanoparticles (nanorods) have an increased magnetophoretic mobility over spherical magnetic nanoparticles with the same equatorial radius. This property makes them attractive candidates for in vivo biological applications. Anisotropic mixed ferrite nanoparticles were coated with a biocompatible hydrophilic block copolymer to render them dispersible in aqueous media. Polymer coated mixed ferrite particles exhibited magnetic properties similar to that of pure magnetite, as the total level of other transition metals in the nanoparticulate system was less than 5%. Electron energy loss spectroscopy (EELS) and (EFTEM) confirmed that the dominant elements in the mixed ferrite nanoparticles were iron and oxygen. Furthermore, HRTEM, SAD and XRD analyses indicated that the crystal structure for the mixed ferrite nanoparticles was inverse spinel. X-ray diffraction peaks at low angles for the coated mixed ferrite rods corresponded to poly(ethylene oxide) peaks, suggesting that the block copolymer employed as a dispersant was associated with the particles. / Ph. D.

Relationships between trace metals and nanoparticles were investigated using analytical transmission electron microscopy (aTEM) and asymmetric flow field flow fractionation (aFlFFF) coupled to both multi-angle laser light scattering (MALLS) and high resolution-inductively coupled plasma mass spectroscopy (HR-ICPMS). Riverbed sediment samples were taken from the Clark Fork River in Montana, USA where a large-scale dam removal project has released reservoir sediment contaminated with toxic trace metals (namely Pb, Zn, Cu and As) which accumulated from one and a half centuries of mining activities upstream. An aqueous extraction method was used to attempt to separate the nanoparticles from the bulk sediment. After analysis of initial results, it was found that low density clays were being selected for in this process and made up a major portion of the particles within the extracts. However, it was also realized that the metals of interest were associated almost exclusively with nano-sized Fe and Ti oxides. In order to more fully examine these relationships, a density separation method, using sodium polytungstate (2.8g/cm3), was developed to separate these higher density oxides from the lower density clays. The heavy fraction was then subjected to an aqueous extraction routine to extract the nanoparticulate fraction. FFF results indicated a smaller size distribution and more ideal fractionation with this method. The aFlFFF-HR-ICPMS profiles for Fe and Ti also matched strongly with the data for the trace metals. The majority of particles analyzed with the TEM were nano-sized Fe and Ti oxides (most commonly goethite, ferrihydrite and brookite), which typically had trace metals associated with them. In many cases, it was aggregates of these nano oxides that were found hosting trace metals. Nanoparticles and aggregates are known to behave differently than their bulk mineral phases or constituent particles, respectively. Nanoparticles are also capable of extended transport in the environment. For these reasons, it is important that their associations with toxic trace metals be extensively evaluated, as they will affect the bioavailability and toxicity of these metals with implications for any type of contaminant sediment relocation, dam removal or metal contaminated site. / Ph. D.