Experimental and computational tools go hand in hand to developing a full understanding of the behavior of chain molecules in solution. Our group uses multiscale computational approaches to enhance our capabilities for interpreting experimental findings, in particular on self-organizing oligomers in various solvents. In a typical scenario, the equilibrium conformations of single chains in the solvent of interest are obtained by standard molecular dynamics simulations. These also provide the necessary interaction parameters that feed into dissipative particle dynamics (DPD) simulations on coarse grained beads constructed out of clustered atomic units obtained from the oligomeric chains and solvent molecules. DPD runs are utilized to estimate the mesoscale morphologies of the oligomer in the solvent. Atomistic detail in the morphological units are then reverse mapped, followed by relaxation simulations to interpret individual interactions that stabilize the self-organized systems. Various properties that are also experimentally measurable are calculated at this stage; once a good fit is observed between actual experiments and predictions, the simulations are utilized to interpret the observations. Chain construction tools relying on most probable conformations of dihedrals are frequently employed during this procedure. We will present results from our predictions of the XRD patterns of PIPOX nanoribbons in aqueous solutions, tuning interaction parameters of thermoplastic polyurethanes in binary solvents to achieve precise control over micro-phase separation, and solvent dependent morphologies of oligomeric chains on electrosprayed surfaces.

Multiscale computational approaches for building realistic molecular models of self-organized co-oligomers in select solvents

2019 Fall National Meeting

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