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Solid polymer electrolytes (SPEs) offer a safer battery electrolyte alternative but face design challenges. This review highlights applications of machine learning alongside theory-based models to improve SPE design. 

The stiffnesses, β-structures, hydrogen bonds, and vibrational modes of wild-type collagen triple helices are compared with osteogenesis imperfecta-related mutants using integrative structural and dynamic analysis via molecular dynamics simulations and Markov state models. Differences in these characteristics are strongly related to the unwound structural states in the mutated regions that are specific to each mutation. 

In ferroelectric heterostructures, the interaction between intrinsic polarization and the electric field generates a rich set of localized electrical properties. The local electric field is determined by several connected factors, including the charge distribution of individual unit cells, the interfacial electromechanical boundary conditions, and chemical composition of the interfaces. However, especially in ferroelectric perovskites, a complete description of the local electric field across micro-, nano-, and atomic-length scales is missing. Here, by applying four-dimensional scanning transmission electron microscopy (4D STEM) with multiple probe sizes matching the size of structural features, we directly image the electric field of polarization vortices in (PbTiO3)16/(SrTiO3)16 superlattices and reveal different electric field configurations corresponding to the atomic scale electronic ordering and the nanoscale boundary conditions. The separability of two different fields probed by 4D STEM offers the possibility to reveal how each contributes to the electronic properties of the film.