The master thesis focuses on aggregation of colloidal solutions with different interactional pair potentials, as an effective coarse grain approximation for aggregation of proteins. We use numerical based method for the simulation of kinetics and dynamics of colloidal aggregation based on open-source program KAPSEL. The simulation solves Navier-Stokes equation for fluid flow using smooth profile method with addition of a random thermal noise and influence of interaction forces between the colloidal particles. We simulate aggregation of colloids in size range of 1 nm-1000 nm which interact with either van der Waals ($1/r^{6}$), London dispersion force between macroscopic objects ($1/r$) or hydrophobic interaction ($e^{-r/d}$). Also we explore the role of different particle density and different ratios of interactions strengths against thermal noise. As the main result of the study of aggregation we have observed, that the kinetics and dynamics of colloidal aggregation depend primarily on the ratio between the strength of inter-particle interaction and thermal noise ($\epsilon/k_bT$) and less on the exact form and range of interactional potentials. When the ratio ($\epsilon/k_bT$) is greater or equals roughly 2, stable process of aggregation is observed. By increasing this ration, the kinetics of aggregation qualitatively does not change and is qualitatively similar also for different particle densities of the system tested. Finally we show that aggregation of colloids in solutions depends primarily on their ability to explore space –i.e. effective Brownian motion-being directly connected with the temperature and fulfilment of thermodynamical condition for emergence of aggregates.
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