Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

Shaping surface acoustic waves for cardiac tissue engineering

The heart is a non-regenerating organ that gradually suffers a loss of cardiac cells and functionality. Given the scarcity of organ donors and complications in existing medical implantation solutions, it is desired to engineer a three-dimensional architecture to successfully control the cardiac cells in vitro and yield true myocardial structures similar to native heart. This thesis investigates the synthesis of a biocompatible gelatin methacrylate hydrogel to promote growth of cardiac cells using biotechnology methodology: surface acoustic waves, to create cell sheets. Firstly, the synthesis of a photo-crosslinkable gelatin methacrylate (GelMA) hydrogel was investigated with different degree of methacrylation concentration. The porous matrix of the hydrogel should be biocompatible, allow cell-cell interaction and promote cell adhesion for growth through the porous network of matrix. The rheological properties, such as polymer concentration, ultraviolet exposure time, viscosity, elasticity and swelling characteristics of the hydrogel were investigated. In tissue engineering hydrogels have been used for embedding cells to mimic native microenvironments while controlling the mechanical properties. Gelatin methacrylate hydrogels have the advantage of allowing such control of mechanical properties in addition to easy compatibility with Lab-on-a-chip methodologies. Secondly in this thesis, standing surface acoustic waves were used to control the degree of movement of cells in the hydrogel and produce three-dimensional engineered scaffolds to investigate in-vitro studies of cardiac muscle electrophysiology and cardiac tissue engineering therapies for myocardial infarction. The acoustic waves were characterized on a piezoelectric substrate, lithium niobate that was micro-fabricated with slanted-finger interdigitated transducers for to generate waves at multiple wavelengths. This characterization successfully created three-dimensional micro-patterning of cells in the constructs through means of one- and two-dimensional non-invasive forces. The micro-patterning was controlled by tuning different input frequencies that allowed manipulation of the cells spatially without any pre- treatment of cells, hydrogel or substrate. This resulted in a synchronous heartbeat being produced in the hydrogel construct. To complement these mechanical forces, work in dielectrophoresis was conducted centred on a method to pattern micro-particles. Although manipulation of particles were shown, difficulties were encountered concerning the close proximity of particles and hydrogel to the microfabricated electrode arrays, dependence on conductivity of hydrogel and difficult manoeuvrability of scaffold from the surface of electrodes precluded measurements on cardiac cells. In addition, COMSOL Multiphysics software was used to investigate the mechanical and electrical forces theoretically acting on the cells. Thirdly, in this thesis the cardiac electrophysiology was investigated using immunostaining techniques to visualize the growth of sarcomeres and gap junctions that promote cell-cell interaction and excitation-contraction of heart muscles. The physiological response of beating of co-cultured cardiomyocytes and cardiac fibroblasts was observed in a synchronous and simultaneous manner closely mimicking the native cardiac impulses. Further investigations were carried out by mechanically stimulating the cells in the three-dimensional hydrogel using standing surface acoustic waves and comparing with traditional two-dimensional flat surface coated with fibronectin. The electrophysiological responses of the cells under the effect of the mechanical stimulations yielded a higher magnitude of contractility, action potential and calcium transient.