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The synthesis of functional nanoparticles is an important step in the hierarchical construction of hybrid materials for nanotechnological applications. A useful path to build these components is to use colloidal nanocrystals that can spontaneously agglomerate into ordered structures under confinement. The focus of this thesis is to explore the diversity of superstructures that can be self-assembled using binary dispersions where the dispersed colloids have spherical or quasi-spherical shapes and interact through simple potentials with repulsive cores and short-range attractions. Using computer simulations we demonstrate that agglomeration experiments with heterogeneous binary mixtures of nanoparticles can be exploited for the synthesis of structured clusters which are proposed as potential intermediate building blocks in hierarchical self-assembly of colloidal molecules and crystals. To describe the structural properties of aggregates resulting from confined mixtures of particles with heterogeneous attractions we analyse the structure diagrams of binary Lennard-Jones clusters by means of a basin-hopping global optimisation approach for a broad range of cluster sizes, compositions and interaction energies and present a large database of minimal energy structures. We identify a variety of structures such as core-shell clusters, Janus clusters and clusters in which the minority species is located at the vertices of icosahedra. For a binary mixture with heterogeneous particle diameters we use molecular dynamics simulations to demonstrate that pressure-dependent inter-particle potentials affect the self-assembly route of the confined particles. This is in agreement with experiments where crystalline superlattices, Janus particles, and core-shell particle arrangements form in the same dispersions for moderate changes in the working pressure or the surfactant that sets the Laplace pressure inside the droplets. Comparison of experimental analysis and simulations confirms th

The synthesis of functional nanoparticles is an important step in the hierarchical construction of hybrid materials for nanotechnological applications. A useful path to build these components is to use colloidal nanocrystals that can spontaneously agglomerate into ordered structures under confinement. The focus of this thesis is to explore the diversity of superstructures that can be self-assembled using binary dispersions where the dispersed colloids have spherical or quasi-spherical shapes and interact through simple potentials with repulsive cores and short-range attractions. Using computer simulations we demonstrate that agglomeration experiments with heterogeneous binary mixtures of nanoparticles can be exploited for the synthesis of structured clusters which are proposed as potential intermediate building blocks in hierarchical self-assembly of colloidal molecules and crystals. To describe the structural properties of aggregates resulting from confined mixtures of particles with heterogeneous attractions we analyse the structure diagrams of binary Lennard-Jones clusters by means of a basin-hopping global optimisation approach for a broad range of cluster sizes, compositions and interaction energies and present a large database of minimal energy structures. We identify a variety of structures such as core-shell clusters, Janus clusters and clusters in which the minority species is located at the vertices of icosahedra. For a binary mixture with heterogeneous particle diameters we use molecular dynamics simulations to demonstrate that pressure-dependent inter-particle potentials affect the self-assembly route of the confined particles. This is in agreement with experiments where crystalline superlattices, Janus particles, and core-shell particle arrangements form in the same dispersions for moderate changes in the working pressure or the surfactant that sets the Laplace pressure inside the droplets. Comparison of experimental analysis and simulations confirms th

Computational modelling is helpful for elucidating the cellular mechanisms driving biological morphogenesis. Previous simulation studies of blood vessel growth based on the Cellular Potts model (CPM) proposed that elongated, adhesive or mutually attractive endothelial cells suffice for the formation of blood vessel sprouts and vascular networks. Because each mathematical representation of a model introduces potential artifacts, it is important that model results are reproduced using alternative modelling paradigms. Here, we present a lattice-free, particle-based simulation of the cell elongation model of vasculogenesis. The new, particle-based simulations confirm the results obtained from the previous Cellular Potts simulations. Furthermore, our current findings suggest that the emergence of order is possible with the application of a high enough attractive force or, alternatively, a longer attraction radius. The methodology will be applicable to a range of problems in morphogenesis and noisy particle aggregation in which cell shape is a key determining factor.

Computational modelling is helpful for elucidating the cellular mechanisms driving biological morphogenesis. Previous simulation studies of blood vessel growth based on the Cellular Potts model (CPM) proposed that elongated, adhesive or mutually attractive endothelial cells suffice for the formation of blood vessel sprouts and vascular networks. Because each mathematical representation of a model introduces potential artifacts, it is important that model results are reproduced using alternative modelling paradigms. Here, we present a lattice-free, particle-based simulation of the cell elongation model of vasculogenesis. The new, particle-based simulations confirm the results obtained from the previous Cellular Potts simulations. Furthermore, our current findings suggest that the emergence of order is possible with the application of a high enough attractive force or, alternatively, a longer attraction radius. The methodology will be applicable to a range of problems in morphogenesis and noisy particle aggregation in which cell shape is a key determining factor.