X-ray scattering studies of self-assembled nanostructures
The structure and growth of self-assembled nanoparticle networks and epitaxial rare-earth thin-films have been studied using X-ray scattering.;A diffusive growth model was developed to model the specular reflected X-ray signal monitored at the anti-phase position, during the growth of two rare-earth (RE) metals, gadolinium and samarium onto molybdenum(110) single crystals. The model identifies atomic layer spacings and the degree of interlayer mass transport. Both RE elements are shown to grow in a layerwise manner but with significant roughness after the initial layer is occupied. The RE growth mode was modified by raised substrate temperatures. The presence of pre-deposition oxygen at the surface was found to encourage layer-by-layer growth for both Gd and Sm.;The structure of noble-metal nanoparticles passivated with thiolate organic ligands was studied using small and wide angle X-ray scattering (SAXS/WAXS). Ag nanoparticles were found to consist of a spherical metal core with fcc atomic packing. The passivating shell was modified to induce direct cross-linking between nanoparticles. The structure and development of the nanoparticle aggregates formed due to the interactions between functionalised thiol derivatives of porphyrin, benzene, C5 dithiol and MUA was monitored with SAXS. In all cases the structures were found to be open and fractal, with the size of the cross-link determined by the size of the functionalised ligand.;The structural quality of self-assembled noble-metal nanoparticle superlattices was investigated using GISAXS. Au nanoparticle networks were formed at the air/water interface. Fits to the GISAXS data, revealed that strain build-up in the layer can directly control the interparticle spacing. Larger Au nanoparticles were allowed to self-assembly onto a Si(111) substrate. The influence of the substrate temperature prior to assembly was investigated and revealed a striking phase transition below 16.7Â°C from disordered nanoparticle networks to highly ordered layered nanoparticle structures. It is thought that solvent volatility plays a crucial role in the ordering process.