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Abstract The application of machine learning models to predict material properties is determined by the availability of high-quality data. We present an expert-curated dataset of lithium ion conductors and associated lithium ion conductivities measured by a.c. impedance spectroscopy. This dataset has 820 entries collected from 214 sources; entries contain a chemical composition, an expert-assigned structural label, and ionic conductivity at a specific temperature (from 5 to 873 °C). There are 403 unique chemical compositions with an associated ionic conductivity near room temperature (15–35 °C). The materials contained in this dataset are placed in the context of compounds reported in the Inorganic Crystal Structure Database with unsupervised machine learning and the Element Movers Distance. This dataset is used to train a CrabNet-based classifier to estimate whether a chemical composition has high or low ionic conductivity. This classifier is a practical tool to aid experimentalists in prioritizing candidates for further investigation as lithium ion conductors.

We use ab initiomolecular dynamics simulations to obtain classically the effects of H2O cage motions on the potential-energy surface (PES) of encapsulated H2in the H2/tetrahydrofuran-hydrate system. The significant differences between the PES for the H2in rigid and flexible cages that we find will influence calculation of the quantum dynamics of the H2. Part of these differences arises from the relaxation of the H2O cage around the classical H2, with a second part arising from the coupling of both translational and rotational motions of H2with the H2O cage. We find that isotopic substitution of 2H for 1H of the H2O cage affects the coupling, which has implications for experiments that require the use of 2H2O, including inelastic neutron scattering that uses 2H2O cages in order to focus on the H2guest dynamics. Overall, this work emphasizes the importance of taking into account cage dynamics in any approach used to understand the dynamics of H2guests in porous framework materials. [ABSTRACT FROM AUTHOR]