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Two-dimensional (2D) materials have properties that are often different from their three-dimensional (3D) bulk form. Many of these materials are stable at ambient conditions, which allows them to be integrated with other 2D- or 3D-materials to form heterostructures. Integration of various dimensional materials attains unique electrical and optical properties that aid in developing novel electronic devices. The interface of the heterogeneous integration of these films can exhibit a weak van der Waals-like bonding. In this thesis, an advanced characterization (from atomic to millimeter resolution) of various dimensional materials with weakly bonded interfaces is developed and employed to understand their behavior at scale. First, a large-area single-crystal cadmium telluride thin film is grown incommensurately and strain-free to a sapphire substrate despite a significant 3.7% lattice mismatch. The film remarkably delaminates as a bulk single crystal film due to an atomically thin tellurium that spontaneously forms at the interface. Aberration-corrected electron microscopy and spectroscopy reveal both the van der Waals-like structure and bonding at the film/substrate interface. Second, a large-area atomically thin gallium is intercalated at the interface of epitaxial graphene. Correlative microscopy workflows are applied to understand the thickness uniformity and area coverage of the 2D–gallium over few millimeters of the sample. Utilizing multiple correlative methods, SEM image contrast is found to be directly related to the presence of the intercalated gallium. The origin of the SEM contrast is investigated as a function of the surface potential. Then, the heterostructure characterization is scaled up over a few square millimeter areas by segmenting SEM images, each acquired with nanometer-scale resolution. Additionally, transmission electron microscopy is applied to investigate the interface of gallium–SiC, the gallium air–stability, and the role of the substrate on the heteroepitaxial growth of 2D–gallium, which charts a path for further development of these materials. / 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.

The geometry of a plasmonic nanostructure determines the charge-current distributions of its localized surface plasmon resonances (LSPR), thereby determining the device’s interactions with external electromagnetic fields. To target specific applications, we manipulate the nanostructure geometry to create different electromagnetic multipole moments, from basic electric and magnetic dipoles to more exotic higher order and toroidal multipoles. The nanoscale nature of the resonance phenomena makes electron beam spectromicroscopy techniques uniquely suited to probe LSPRs over a wide spectral range, with nanoscale spatial resolution. We use electron energy loss spectroscopy (EELS) in a monochromated scanning transmission electron microscope and cathodoluminescence spectroscopy (CL) in a scanning electron microscope to probe the near-field and far-field properties of LSPR. Electric dipoles within triangular prisms and apertures in Sierpiński fractals couple as the generation number is advanced, creating predictable spectral bands from hybridized dipole modes of parent generations with hierarchical patterns of high field intensity, as visualized in EELS. A magnetic dipole moment is engineered using a vertical split ring resonator (VSRR), pushing the limits of nanofabrication techniques. On this nanostructure we demonstrate the calculation of spatially resolved Stokes parameters on the emission of the magnetic dipole mode and a series of coupled rim modes. Coupling of the magnetic dipole mode of four VSRRs in a circular array creates an LSPR mode supporting the lesser-known toroidal dipole moment. We further probe the near-field configuration of this 3D array through tilting under the electron beam in EELS, and the far-field emission through CL of higher order rim modes. We also propose further configurations of five and six VSRRs to strengthen the toroidal dipole moment. All of the data presented herein was analyzed using custom Python code, which provides a unique graphical interface to 3D spectromicroscopy datasets, and a parallelized implementation of the Richardson-Lucy deconvolution algorithm. / Thesis / Doctor of Philosophy (PhD) / Certain types of metallic particles are capable of trapping light on a scale far below that which we can see; their light-trapping properties depend on their material and on their geometry. Using these tiny particles, we can manipulate the behaviour of light with greater freedom than is otherwise possible. In this thesis, we study how we can engineer the geometry of these particles to give predictable responses that can then be targeted towards specific applications. We study a fractal structure with predictable self-similar responses useful for high sensitivity detection of disease or hormone biomarkers; a resonating structure emulating a magnetic response which can be used in the design of unique new materials capable of bending light backwards and cloaking objects from sight; and a combination of these resonators in an array to demonstrate exotic electromagnetic behaviour still on the limit of our understanding.

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During this study, the correlation between the evolution of the prior austenitic grain size and of the precipitation state during thermal treatment performed on steels is presented. To do this, the precipitation state has been finely characterized. Precipitate volume fractions were measured by plasma spectroscopy. Transmission Electron Microscopy (TEM) was used to determine the precipitate size distributions (HAADF images) and the precipitate chemical composition (EDX, EELS for carbon and nitrogen). In order to treat ELLS spectra obtained on complex carbonitrides (V,Nb,Ti)(C,N), a routine based on the Least Mean square Fitting have been developed. Results obtained with this method are in gopd agreement with those obtained by EDX analysis for metallic elements (Nb, V, Ti, ...). Then, grain size distributions were determined using a special etching called "Bechet-Beaujard", which reveals the prior austenite grain boundaries. Two alloys have been characterized in this study. (i) A model alloy, the FeVNbCN, which presents two precipitate types, NbC and VCN. This alloy was chosen to study the role of nitrogen on the precipitation state during reversion treatments. A model predicting the precipitation kinetics, coupled with a model for grain growth, give a good agreement with experimental results on grain sizes, precipitate sizes and on precipitate volume fraction. (ii) An industrial steel, the 16MnCr5+Nb was also studied. This alloy exhibits the presence of AlN and NbC precipitates. The correlation obtained between the Prior Austenite Grain Size and the evolution of the precipitation state shows that a large volume fraction of small precipitates allows a great pinning of grain boundaries. Finally, during thermo-mechanical treatments performed in the industry, some large grains may grow faster than smaller grains, leading to the so-called abnormal grain growth. This kind of growth can lead to undesirable mechanical instabilities. We have developed a criterium for abnormal grain growth which predicts the risk of such growth for a given precipitation state. This model presents a good agreement with all experimental results for both studied alloys.

Organic materials with fascinating/intriguing electronic properties have been the driving force for many research activities in the past, and in particular for important progress in materials science covering both new functional materials as well as theoretical developments. In addition, charge transfer, i. e., the addition or removal of charges to or from molecules in organic solids is one route to modify and control their electronic properties. Recently, the discovery of superconductivity in several alkali metal intercalated hydrocarbon systems (picene, phenanthrene, coronene and 1,2;8,9-dibenzopentacene) with rather high transition temperatures has opened a new chapter in organic material science as well as solid-state physics. The search for a microscopic understanding of the mechanism that drives materials superconducting always has initiated a large number of scientific activities, and there are numerous examples where these activities have provided major advancement. A basic foundation of this understanding is the knowledge of the electronic properties of the material under investigation. In this context, this thesis reports first, very detailed insight into the electronic structure of both undoped as well as potassium doped picene, coronene and 1,2;8,9-dibenzopentacene using electron energy-loss spectroscopy (EELS) as main experimental method. Additionally, also photoemission spectroscopy experiments have been performed to investigate the occupied electronic density of states close to the chemical potential. In order to learn more about the electronic structure we have compared the results we obtained from EELS and photoemission spectroscopy with theoretical calculations based on Density functional theory (DFT) using the local-density approximation (LDA). We identify the peculiar case of very close lying conduction bands that upon doping harbour the electrons that form the Cooper-pairs in the superconducting state. Moreover, the presented data display substantial changes in the electronic excitation spectrum upon doping, whereas in the doped case the appearance of one new peak (for picene) and several new peaks (for coronene and 1,2;8,9-dibenzopentacene) in the former optical gap is reported. By using a Kramers–Kronig analysis (KKA) it is possible to gain information about the nature of this doping introduced excitations. In particular, in case of picene, the new low energy feature can be assigned to a charge carrier plasmon. Interestingly, this plasmon disperses negatively upon increasing momentum transfer, which deviates significantly from the traditional picture of metals based on the homogeneous electron gas. The comparison with calculations of the loss function of potassium intercalated picene shows how this finding is the result of the competition between metallicity and electronic localization on the molecular units. Furthermore, core level excitation measurements show the reduction of the lowest lying C 1s excitation feature, which clearly demonstrates that potassium intercalation leads to a filling of the conduction bands with electrons. Additionally, the measurements of potassium intercalated 1,2;8,9-dibenzopentacene clearly indicate the formation of particular doped phases with compositions K_xdibenzopentacene (x = 1, 2, 3), whereas the data suggest that K_1dibenzopentacene has an insulating ground state with an energy gap of about 0.9 eV, while K_2dibenzopentacene and K_3dibenzopentacene might well be metallic, because of the absent of an energy gap in the electronic excitation spectra. Interestingly, a comparison of the photoemission as well as EELS spectra of undoped 1,2;8,9-dibenzopentacene and pentacene reveal that the electronic states close to the Fermi level and the electronic excitation spectra of the two materials are extremely similar, which is due to the fact, that the additional two benzene rings in 1,2;8,9-dibenzopentacene virtually do not contribute to the delocalized pi molecular orbitals close to the Fermi level. This close electronic similarity is in contrast to the behavior upon potassium doping, where evidence for a Mott state has been reported in the case of pentacene. A comparison of the low energy excitation spectra of chrysene with picene (phenacenes) as well as tetracene with pentacene (acenes) crystals reveal a significant difference between the former and the latter two materials. While for the phenacenes (zigzag arrangement) the excitation onset is characterized by up to five weak excitation features with only small anisotropy and without visible Davydov splitting within the a*, b*-planes, the acene (linear arrangement) spectra are dominated by a large excitation close to the onset and a sizable Davydov splitting. The presented data show further that the spectral shape of the pentacene excitation spectrum provides clear evidence for a large admixture of molecular Frenkel-type excitons with charge-transfer excitations resulting in excited states with a significantly mixed character. This conclusion is in good agreement with recent advanced calculations which predicted a charge-transfer admixture to the lowest singlet excitation which is significantly dependent upon the length of the acene molecules. Moreover, also for picene and chrysene we observe differences which point towards an increased charge-transfer contribution to the singlet excitation spectrum in the former. Finally, investigations of the electronic properties of undoped and potassium doped chrysene, a close relative of picene, show that the doping introduced changes are in a similar range such as observed in case of picene. Interestingly, due to the analogy between the observed changes in the electronic structure upon potassium doping between chrysene and picene and further similarity in the crystal structure we speculate that chrysene is a promising candidate for another aromatic hydrocabon superconductor.

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abstract: In-situ environmental transmission electron microscopy (ETEM) is a powerful tool for following the evolution of supported metal nanoparticles under different reacting gas conditions at elevated temperatures. The ability to observe the events in real time under reacting gas conditions can provide significant information on the fundamental processes taking place in catalytic materials, from which the performance of the catalyst can be understood. The first part of this dissertation presents the application of in-situ ETEM studies in developing structure-activity relationship in supported metal nanoparticles. In-situ ETEM studies on nanostructures in parallel with ex-situ reactor studies of conversions and selectivities were performed for partial oxidation of methane (POM) to syngas (CO+H2) on Ni/SiO2, Ru/SiO2 and NiRu/SiO2 catalysts. During POM, the gas composition varies along the catalyst bed with increasing temperature. It is important to consider these variations in gas composition in order to design experiments for in-situ ETEM. In-situ ETEM experiments were performed under three different reacting gas conditions. First in the presence of H2, this represents the state of the fresh catalyst for the catalytic reaction. Later in the presence of CH4 and O2 in 2:1 ratio, this is the composition of the reacting gases for the POM reaction and this composition acts as an oxidizing environment. Finally in the presence of CH4, this is the reducing gas. Oxidation and reduction behavior of Ni, Ru and NiRu nanoparticles were followed in an in-situ ETEM under reacting gas conditions and the observations were correlated with the performance of the catalyst for POM. The later part of the dissertation presents a technique for determining the gas compositional analysis inside the in-situ ETEM using electron energy-loss spectroscopy. Techniques were developed to identify the gas composition using both inner-shell and low-loss spectroscopy of EELS. Using EELS, an "operando TEM" technique was successfully developed for detecting the gas phase catalysis inside the ETEM. Overall this research demonstrates the importance of in-situ ETEM studies in understanding the structure-activity relationship in supported-metal catalysts for heterogeneous catalysis application. / Dissertation/Thesis / Ph.D. Materials Science and Engineering 2011