Understanding the disorder to order transitions in block copolymers: How do complex phases nucleate?
Block copolymers are known to self-assemble into a multitude of phases with vastly different geometries, depending on the ordering of its molecules. Due to their highly regular patterns, these phases find use in applications ranging from high-surface area separation membranes, to catalysts, solar cells, and energy storage devices. In order to tap into the unique properties of the different phases, we need to be able to design and control its formation. This requires a deeper understanding of the mechanisms through which it self-assembles.
Order Parameters (OP) are variables used to track the changes occurring in the system as it transitions from disorder to order. Often times, the definition of an optimal OP is highly nontrivial especially for complex systems like block copolymers, and there exists a need to develop simple and general strategies for identifying known phase transitions.
In this talk, I will discuss a pattern recognition-based framework that we developed to track the kinetics of order-disorder phase transitions in common block copolymer systems. The OP framework was also found to be a suitable tool to map the free energy landscapes of a system undergoing this phase transition.
The proposed framework can potentially be improved by incorporating machine learning techniques to automatically detect incipient structural patterns as they form. Much of my ongoing work is thus centered around this idea and I’ll briefly discuss the various methods, that we believe would make our OP framework applicable to a much broader range of materials.