Development of novel EELS methods to unveil nanoparticle properties

[eng] The aim of this thesis has been two-fold. First, to develop new processing and analysis tools and strategies for extracting information from EELS data, and second, to apply the methods to different nanoparticle systems to shed light to relevant phenomena related to their synthesis and properties. In this regard, chapter 1 presented and overview of the EELS fundamentals and of the state of the art of the technique. Chapter 2 was focused on the advanced computational methods related to EELS data analysis. Moreover, the application of cluster analysis to EELS was introduced, showing its possibilities as an image segmenting and phase identification tool. The following chapters were devoted to the investigation of different material science problems related to NPs that take advantage of the capabilities of quantitative EELS. The results were grouped by increasing complexity of the performed analysis, with chapter 3 devoted to characterizations that were mainly carried out using EELS elemental mapping, chapter 4 being related to ELNES analysis and chapter 5 to EELS tomography. In chapter 2, the adaptation of data clustering algorithms to the analysis of EELS data, developed within the scope of the present thesis, has been undertaken. In chapter 3.1 the organic synthesis of FeOx@SiO2 NPs was assessed. Several findings were obtained through the HRTEM, STEM-HAADF and EELS characterization of the FeOx@SiO2 NPs at different stages of its synthesis. In chapter 3.2, concerning Au-Ag-Se and the Au-Ag-S system cation exchange reactions several findings were made. Chapter 4 was devoted to the characterization of different NPs with an emphasis on the direct observation the oxidation state of its constituents through EELS. In chapter 4.1, the synthesis of MnOx/Fe3O4 core/shell NPs was assessed. In chapter 4.2, the measurement of oxidation state at atomic resolution in spinel crystals was proposed as a method to assess cation inversion in the crystal. The necessary methods were developed and applied to iron oxide/manganese oxide core/shell NPs. Chapter 5 was devoted to the combination of EELS and tomography. In chapter 5.1 the synthesis of cobalt oxide/cobalt ferrite (CoO@CFO) core/shell NPs and cobalt oxide/manganese ferrite (CoO@MFO) NPs was investigated. Chapter 5.2 was focused on the achievement of an oxidation state-sensitive tomographic reconstruction.[cat] L’adveniment de la nanotecnologia està portant amb ell l’aparició d’una gran quantitat de nous materials, compostos i aplicacions. En el seu desenvolupament, sovint té lloc fenomenologia sorprenent, o encara no ben entesa. Per omplir aquest forats en el nostre coneixement i poder desenvolupar noves aplicacions és de vital importància esbrinar la configuració estructural i química a nivell subnanomètric d’aquests components. Per la seva gran resolució espacial, la microscòpia electrònica de transmissió ha esdevingut una eina indispensable en aquest context. A més, en un microscopi electrònic es poden combinar una gran varietat de tècniques que poden donar una quantitat d’informació enorme. Una d’aquestes tècniques és l’espectroscòpia de pèrdua d’energia dels electrons (EELS). Aquesta tècnica ha permès en els últims anys el mapejat d’elements químics i ions columna atòmica per columna atòmica, arribant a uns dels nivells més íntims als que es pot conèixer la matèria en estat sòlid. L’objectiu d’aquesta tesi ha estat fer ús de l’EELS i d’altres tècniques emprades en microscòpia electrònica per entendre els processos químics que tenen lloc en diferents síntesis de nanopartícules. En aquest procés s’han desenvolupat també una sèrie d’eines enfocades al processat de les dades d’EELS ja sigui per a facilitar la seva interpretació, limitar problemes derivats de la seva adquisició (i. e. soroll) o calcular propietats concretes del material estudiat. A més aquesta tècnica s’ha combinat amb mètodes de reconstrucció 3D per obtenir una informació completa dels sistemes estudiats

Conformational states of macromolecular assemblies explored by integrative structure calculation

A detailed description of macromolecular assemblies in multiple conformational states can be very valuable for understanding cellular processes. At present, structural determination of most assemblies in different biologically relevant conformations cannot be achieved by a single technique and thus requires an integrative approach that combines information from multiple sources. Different techniques require different computational methods to allow efficient and accurate data processing and analysis. Here, we summarize the latest advances and future challenges in computational methods that help the interpretation of data from two techniques—mass spectrometry and three-dimensional cryo-electron microscopy (with focus on alignment and classification of heterogeneous subtomograms from cryo-electron tomography). We evaluate how new developments in these two broad fields will lead to further integration with atomic structures to broaden our picture of the dynamic behavior of assemblies in their native environment

Real-space imaging of polar and elastic nano-textures in thin films via inversion of diffraction data

Exploiting the emerging nanoscale periodicities in epitaxial, single-crystal thin films is an exciting direction in quantum materials science: confinement and periodic distortions induce novel properties. The structural motifs of interest are ferroelastic, ferroelectric, multiferroic, and, more recently, topologically protected magnetization and polarization textures. A critical step towards heterostructure engineering is understanding their nanoscale structure, best achieved through real-space imaging. X-ray Bragg coherent diffractive imaging visualizes sub-picometer crystalline displacements with tens of nanometers spatial resolution. Yet, it is limited to objects spatially confined in all three dimensions and requires highly coherent, laser-like x-rays. Here we lift the confinement restriction by developing real-space imaging of periodic lattice distortions: we combine an iterative phase retrieval algorithm with unsupervised machine learning to invert the diffuse scattering in conventional x-ray reciprocal-space mapping into real-space images of polar and elastic textures in thin epitaxial films. We first demonstrate our imaging in PbTiO3/SrTiO3 superlattices to be consistent with published phase-field model calculations. We then visualize strain-induced ferroelastic domains emerging during the metal-insulator transition in Ca2RuO4 thin films. Instead of homogeneously transforming into a low-temperature structure (like in bulk), the strained Mott insulator splits into nanodomains with alternating lattice constants, as confirmed by cryogenic scanning transmission electron microscopy. Our study reveals the type, size, orientation, and crystal displacement field of the nano-textures. The non-destructive imaging of textures promises to improve models for their dynamics and enable advances in quantum materials and microelectronics

Validação de heterogeneidade estrutural em dados de Crio-ME por comitês de agrupadores

Orientadores: Fernando José Von Zuben, Rodrigo Villares PortugalDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Análise de Partículas Isoladas é uma técnica que permite o estudo da estrutura tridimensional de proteínas e outros complexos macromoleculares de interesse biológico. Seus dados primários consistem em imagens de microscopia eletrônica de transmissão de múltiplas cópias da molécula em orientações aleatórias. Tais imagens são bastante ruidosas devido à baixa dose de elétrons utilizada. Reconstruções 3D podem ser obtidas combinando-se muitas imagens de partículas em orientações similares e estimando seus ângulos relativos. Entretanto, estados conformacionais heterogêneos frequentemente coexistem na amostra, porque os complexos moleculares podem ser flexíveis e também interagir com outras partículas. Heterogeneidade representa um desafio na reconstrução de modelos 3D confiáveis e degrada a resolução dos mesmos. Entre os algoritmos mais populares usados para classificação estrutural estão o agrupamento por k-médias, agrupamento hierárquico, mapas autoorganizáveis e estimadores de máxima verossimilhança. Tais abordagens estão geralmente entrelaçadas à reconstrução dos modelos 3D. No entanto, trabalhos recentes indicam ser possível inferir informações a respeito da estrutura das moléculas diretamente do conjunto de projeções 2D. Dentre estas descobertas, está a relação entre a variabilidade estrutural e manifolds em um espaço de atributos multidimensional. Esta dissertação investiga se um comitê de algoritmos de não-supervisionados é capaz de separar tais "manifolds conformacionais". Métodos de "consenso" tendem a fornecer classificação mais precisa e podem alcançar performance satisfatória em uma ampla gama de conjuntos de dados, se comparados a algoritmos individuais. Nós investigamos o comportamento de seis algoritmos de agrupamento, tanto individualmente quanto combinados em comitês, para a tarefa de classificação de heterogeneidade conformacional. A abordagem proposta foi testada em conjuntos sintéticos e reais contendo misturas de imagens de projeção da proteína Mm-cpn nos estados "aberto" e "fechado". Demonstra-se que comitês de agrupadores podem fornecer informações úteis na validação de particionamentos estruturais independetemente de algoritmos de reconstrução 3DAbstract: Single Particle Analysis is a technique that allows the study of the three-dimensional structure of proteins and other macromolecular assemblies of biological interest. Its primary data consists of transmission electron microscopy images from multiple copies of the molecule in random orientations. Such images are very noisy due to the low electron dose employed. Reconstruction of the macromolecule can be obtained by averaging many images of particles in similar orientations and estimating their relative angles. However, heterogeneous conformational states often co-exist in the sample, because the molecular complexes can be flexible and may also interact with other particles. Heterogeneity poses a challenge to the reconstruction of reliable 3D models and degrades their resolution. Among the most popular algorithms used for structural classification are k-means clustering, hierarchical clustering, self-organizing maps and maximum-likelihood estimators. Such approaches are usually interlaced with the reconstructions of the 3D models. Nevertheless, recent works indicate that it is possible to infer information about the structure of the molecules directly from the dataset of 2D projections. Among these findings is the relationship between structural variability and manifolds in a multidimensional feature space. This dissertation investigates whether an ensemble of unsupervised classification algorithms is able to separate these "conformational manifolds". Ensemble or "consensus" methods tend to provide more accurate classification and may achieve satisfactory performance across a wide range of datasets, when compared with individual algorithms. We investigate the behavior of six clustering algorithms both individually and combined in ensembles for the task of structural heterogeneity classification. The approach was tested on synthetic and real datasets containing a mixture of images from the Mm-cpn chaperonin in the "open" and "closed" states. It is shown that cluster ensembles can provide useful information in validating the structural partitionings independently of 3D reconstruction methodsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

Optical imaging methods for the study of disease models from the nano to the mesoscale

The visualisation of disease phenotypes allows scientists to study fundamental mechanisms of disease. Optical imaging methods are useful not only to observe anatomical features of biological samples, but also to infer interactions between molecular species using fluorescence labelling. This thesis presents the development of imaging and analysis tools to study biological questions in three models of disease, with samples ranging from the sub-cellular to the organ scale. First, the role of the alpha-synuclein (a-syn) protein, whose dysfunction is a hallmark of Parkinson’s Disease, was studied with respect to vesicle trafficking at the synapse. Synaptic vesicles are ∼40 nm in diameter; imaging vesicles therefore requires methods with resolution below the diffraction limit. Single-molecule localisation microscopy (SMLM), which circumvents the diffraction limit by separating fluorophore emission in time to localise individual molecules in space with ∼20 nm precision, was thus implemented to study a-syn in purified synaptic boutons. A software package was developed to analyse the colocalisation of a-syn with internalised vesicles, and the clustering of a-syn under differing synaptic calcium levels. The colocalisation of a-syn and internalised vesicles was found to be temperature independent, suggesting that a-syn is involved in non-canonical trafficking mechanisms. Ground truth simulations from a synaptosome model were used to benchmark two cluster analysis methods. Both methods applied on the experimental data showed that a-syn becomes less clustered at low synaptic calcium levels. Second, the spatiotemporal association of ESCRT-II, a protein complex whose role in the budding of the human immunodeficiency virus (HIV) was previously considered dispensable, and the HIV polyprotein Gag was studied during viral egress using novel image analysis tools. A nearest-neighbour analysis showed the ESCRT-II protein EAP45 colocalises with Gag similarly to ALIX, a protein well known to be involved in HIV budding. However, upon deletion of EAP45’s N-terminus, its colocalisation with Gag was significantly impaired, highlighting the importance of this EAP45 domain in linking to Gag. Single particle tracking was used to trace the trajectories of EAP45 and Gag in live cells, and an algorithm was developed to visualise the simultaneous motion of two particles; these analyses revealed three types of potential dynamic interaction between EAP45 and Gag. Finally, an open-source instrument to visualise phenotypes from large organs in 3D was developed for the study of chronic obstructive pulmonary disease (COPD) models. The instrument implements Optical Projection Tomography, a technique which can reconstruct cross-sectional slices of a transparent object from its orthographic projections, using off-the- shelf components and novel ImageJ plugins for artefact correction and volume reconstructions. Excised and cleared mouse lungs were imaged in which high order airways can be discerned with 50 μm resolution. The raw lung data, instructions for building the instrument, the free ImageJ plugins, and a detailed software manual are available in an online repository to encourage the widespread use of OPT for imaging large samples.Gates Cambridg

Computer Vision Approaches to Liquid-Phase Transmission Electron Microscopy

Electron microscopy (EM) is a technique that exploits the interaction between electron and matter to produce high resolution images down to atomic level. In order to avoid undesired scattering in the electron path, EM samples are conventionally imaged in solid state under vacuum conditions. Recently, this limit has been overcome by the realization of liquid-phase electron microscopy (LP EM), a technique that enables the analysis of samples in their liquid native state. LP EM paired with a high frame rate acquisition direct detection camera allows tracking the motion of particles in liquids, as well as their temporal dynamic processes. In this research work, LP EM is adopted to image the dynamics of particles undergoing Brownian motion, exploiting their natural rotation to access all the particle views, in order to reconstruct their 3D structure via tomographic techniques. However, specific computer vision-based tools were designed around the limitations of LP EM in order to elaborate the results of the imaging process. Consequently, different deblurring and denoising approaches were adopted to improve the quality of the images. Therefore, the processed LP EM images were adopted to reconstruct the 3D model of the imaged samples. This task was performed by developing two different methods: Brownian tomography (BT) and Brownian particle analysis (BPA). The former tracks in time a single particle, capturing its dynamics evolution over time. The latter is an extension in time of the single particle analysis (SPA) technique. Conventionally it is paired to cryo-EM to reconstruct 3D density maps starting from thousands of EM images by capturing hundreds of particles of the same species frozen on a grid. On the contrary, BPA has the ability to process image sequences that may not contain thousands of particles, but instead monitors individual particle views across consecutive frames, rather than across a single frame