Phase-Equilibrium-Mediated Assembly of Colloidal Nanoparticles

Colloidal dispersion of nanoparticles (CNPs) has interesting properties both in terms of fundamental studies and industrials applications. Particular focus on the phase equilibrium and separation dynamics of CNPs has been necessary for understanding how exactly and fast CNPs are assembled and for controlling the assembly structure and dynamic properties. For understanding and controlling assembly structure and dynamics of CNPs, theoretical analysis in conjunction with computational approaches supported by experimental validation is necessary. In this thesis, studies on the phase-equilibrium-mediated assembly of CNPs are performed by using various computational tools accompanied by theoretical modeling to cover wide range of spatio and temporal dimensions of the desired system containing CNPs. To address the phase separation of CNPs, we studied on two main mechanisms; (1) cluster formation and (2) spinodal decomposition. In each mechanism, we developed novel, effective, and efficient computational algorithms to elucidate phase-equilibrium assembly structure and formation dynamics of CNPs: (1) a kinetic Monte Carlo (KMC) algorithm for cluster formation in microscopic dimensions and spinoda