The self-assembly of nano patterns is very important because it can potentially allow us to create circuits and thus devices at the nanoscale. For example, the smaller we can make circuits, the more “things” we can fit on a single computer chip. This will allow us to create faster computers because data will only need to be transferred over extremely short distances. In addition, the cost and energy required to operate such devices will be greatly reduced. Therefore, nanotechnology can revolutionize our existing industry.

The self-assembly of nano patterns has been observed in many systems (see Figure 1). Those patterns are formed when some chemicals are deposited over a surface. Two major factors cause this pattern formation. The minimums in Gibb’s free energy drive the phase separation of the chemical components, which increases the amount of surface free energy. To minimize its total energy, the system reacts by reducing the number of phase boundaries. On the other hand, the surface stress produced by concentration variations tends to create finer patterns by increasing the number of phase boundaries. These two opposing factors cause the system to reach equilibrium and form a stable pattern. A computer model simulating such processes can be used for pattern design.

Because pattern formation happens spontaneously, the same self-assembly process could affect the life of pre-made nano devices. Even though we might achieve making nano devices, the patterns on these devices could at any point reassemble into something else, which would cause it to malfunction. Thus, a computer code that simulates how patterns evolve over time under certain conditions (e.g. temperature fluctuations) could be useful for predicting device lifetime.

The self-assembly of nanoscale patterns is not only important because of their applications, but also because they are so mysterious and fascinating. Many of these patterns are so stunning and beautiful that we would never expect. In this project, we develop computer software to simulate these patterns under constant and changing temperature. Using simulations, we investigate the effects of prescribing an initial pattern and show that initial patterns can be used to control the pattern formations. We also investigate the effects of temperature changes on these patterns.

Figure 1