“Can one make quantum-chemical predictions using coarse-grained representations of soft materials?”
Computational studies aimed at understanding conformationally dependent electronic structure in soft materials require a combination of classical and quantum-mechanical simulations, for which the sampling of conformational space can be particularly demanding. Coarse-grained (CG) models provide a means of accessing relevant spatiotemporal scales, but CG configurations must be backmapped into atomistic representations to perform quantum-chemical calculations, which is computationally intensive and inconsistent with the spatial resolution of the CG model. We have recently introduced a methodology called electronic coarse graining (ECG) in which the conformationally dependent electronic structure of a molecule is mapped directly to CG pseudo-atom configurations. By averaging over decimated degrees of freedom, ECG accelerates simulations by eliminating backmapping and ad nauseum quantum-chemical calculations. We demonstrate how ECG can be tailored to provide molecular weight transferable electronic structure predictions of polymers at CG model resolutions via utilization of simple model Hamiltonians for ground and excited state properties. The accuracy and transferability of ECG presents considerable opportunities for scalable optoelectronic property prediction in soft materials directly from coarse-grained models.
