Predicting Self-assembly of Nonspherical Particles using Density Functional Theory

Due to the great wealth of experimentally available particle shapes, efficient methods for predicting self-assembly are of paramount importance in soft matter. I will present recent advances in density functional theory that allow fast exploration of parameter space to be followed by more precise particle-resolved computer simulation techniques or experiments. We have been focusing on liquid crystal phases of hard particles so far, since these constitute stringent tests on our theory due to the small free energy differences between the phases involved. Comparison between the theory and particle-resolved simulations for spherocylinders and rod-like polyhedra shows that the theory predicts self-assembly of liquid crystals with the required accuracy for fast exploration. We find that the flat-topped, rod-like polyhedra exhibit a significantly more stable smectic phase than the archetypical spherocylinders. This subtle effect of the particle shape is well captured by the theory, which is promising for applications of the theory to other phases and other interaction potentials.