Controlled self-assembly of charged particles
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Self-assembly is a process of non-intrusive transformation of a system from a disordered to an ordered state. For engineering purposes, self-assembly of microscopic objects can benefit significantly from macroscopic guidance and control. This dissertation is concerned with controlling self-assembly in binary monolayers of electrically charged particles that follow basic laws of statistical mechanics. First, a simple macroscopic model is used to determine an optimal thermal control for self-assembly. The model assumes that a single rate-controlling mechanism is responsible for the formation of spatially ordered structures and that its rate follows an Arrhenius form. The model parameters are obtained using molecular dynamics simulations. The optimal control is derived in an analytical form using classical optimization methods. Two major lessons were learned from that work: (i) isothermal control was almost as effective as optimal time-dependent thermal control, and (ii) neither electrostatic interactions nor thermal control were particularly effective in eliminating voids formed during self-assembly. Accordingly, at the next stage, the focus is on temperature-pressure control under isothermal-isobaric conditions. In identifying optimal temperature and pressure conditions, several assumptions, that allow one to relate the optimal conditions to the phase diagram, are proposed. Instead of verifying the individual assumptions, the entire approach is verified using molecular dynamics simulations. It is estimated that under optimal isothermal-isobaric conditions the rate of self-assembly is about five time faster than that under optimal temperature control conditions. It is argued that the proposed approach of relating optimal conditions to the phase diagram is applicable to other systems. Further, the work reveals numerous and useful parallels between self-assembly and crystal physics, which are important to exploit for developing robust engineering self-assembly processes.