Here we consider two studies which show how computer modeling and simulation can be used to study aspects of material science for which experimental methods would be time consuming or difficult. In the first we examined the optimization of electromagnetic levitation coils, for reduced sample temperature, through the development of a genetic algorithm and a rigorous analytical model. In the development of the analytical model for levitation, we propose a new model for the heating effect from a design consisting of a series of co-axial circular loops. With the new model we are better able to predict sample temperatures as compared with existing models. The new model is incorporated into a robust genetic algorithm to produce a powerful and generic design tool for the creation of levitation coils. Using this new design tool we seek to expand the range of temperatures (specifically to lower temperatures) and materials that are able to be studied using EML.

In the second study, we examine the growth of a grain structure in the presence of second phase particles that act as pinning agents. The existing models of grain growth with pinning agents have thus far focused on particle distributions at the extremes of grain boundary correlation. When experimental measurements at the limits of correlation are compared to the appropriate models, they have shown good agreement but seem to suggest that there is a transition in behavior between the limits but the nature and mechanisms are not well known. As such we look to study pinning agent distributions centered around the initial grain boundaries and varied in such a way as to examine the transition from high to low boundary correlation. The results show that the average grain size varies smoothly during the transition. However, the results also show that there is an anomalous increase in grain size, when the boundary region containing pinning agents is slightly larger than the diffuse boundary width from the phase-field model and the local density of pinning agents is held constant. In this situation, it is believed that the reduction in the probability of an agent beginning on a boundary leads to a reduction in the fraction of boundaries interacting with a pinning agent and consequently an increase in the average grain size. This effect appears to out weigh the effect of the increased number of available pinning agents.