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Calculations with high accuracy for atomic and inter-atomic properties, such as nuclear magnetic resonance (NMR) spectroscopy and bond dissociation energies (BDEs) are valuable for pharmaceutical molecule structural analysis, drug exploration, and screening. It is important that these calculations should include relativistic effects, which are computationally expensive to treat. Non-relativistic calculations are less expensive but their results are less accurate. In this study, we present a computational framework for predicting atomic and inter-atomic properties by using machine-learning in a non-relativistic but accurate and computationally inexpensive framework. The accurate atomic and inter-atomic properties are obtained with a low dimensional deep neural network (DNN) embedded in a fragment-based graph convolutional neural network (F-GCN). The F-GCN acts as an atomic fingerprint generator that converts the atomistic local environments into data for the DNN, which improves the learning ability, resulting in accurate results as compared to experiments. Using this framework, the 13C/1H NMR chemical shifts of Nevirapine and phenol O–H BDEs are predicted to be in good agreement with experimental measurement.

Sodium–sulfur (Na–S) batteries with durable Na‐metal stability, shuttle‐free cyclability, and long lifespan are promising to large‐scale energy storages. However, meeting these stringent requirements poses huge challenges with the existing electrolytes. Herein, a localized saturated electrolyte (LSE) is proposed with 2‐methyltetrahydrofuran (MeTHF) as an inner sheath solvent, which represents a new category of electrolyte for Na–S system. Unlike the traditional high concentration electrolytes, the LSE is realized with a low salt‐to‐solvent ratio and low diluent‐to‐solvent ratio, which pushes the limit of localized high concentration electrolyte (LHCE). The appropriate molecular structure and solvation ability of MeTHF regulate a saturated inner sheath, which features a reinforced coordination of Na⁺to anions, enlarged Na⁺‐solvent distance, and weakened anion‐diluent interaction. Such electrolyte configuration is found to be the key to build a sustainable interphase and a quasi‐solid–solid sulfur redox process, making a dendrite‐inhibited and shuttle‐free Na–S battery possible. With this electrolyte, pouch cells with decent cycling performance under rather demanding conditions are demonstrated.