Nano-building blocks from polymer self-assembly: A coarse grain simulation approach

Block-copolymer self assembly in water result in a variety of morphologies that greatly impact technological, material and biomedical applications. Despite extensive experimental research, simulation studies in this field are scarce. Large length and timescales involved makes this task near impossible for the traditional simulations based on complete atomistic representation. We use novel coarse grain (CG) simulation methodology to explore block copolymer self-assembly in solvent as well as on solid surfaces. Simulations provide insights into experimental twilight zone thereby highlighting the crucial roles of relative block composition and interaction strength in determining outcome of self-assembly. In addition, copolymer adsorption on hydrophobic surfaces such as model graphite and nanotubes reveal mechanism behind the self-organized structure formation. As a further step, controlled nanobuilding blocks for the next generation supramolecular self assembly are obtained using biologically inspired self-assembly of binary copolymer mixture. At various stages, these studies highlight the importance of combining the CG approach with higher resolution simulation approaches. Fortunately, coarse-grain models have the advantage that they can be back mapped to the respective atomistic/quantum representation and thus providing an opportunity for hybrid approaches involving quantum, classical and coarse-grain methods.