Lithium bonds are analogous to hydrogen bonds and are therefore expected to exhibit similar characteristics and functions. Additionally, the metallic nature and large atomic radius of Li bestow the Li bond with special features. As one of the most important applications of the element, Li batteries afford emerging opportunities for the exploration of Li bond chemistry. Herein, the historical development and concept of the Li bond are reviewed, in addition to the application of Li bonds in Li batteries. In this way, a comprehensive understanding of the Li bond in Li batteries and an outlook on its future developments is presented.

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Lithium bonds are analogous to hydrogen bonds and are therefore expected to exhibit similar characteristics and functions. Additionally, the metallic nature and large atomic radius of Li bestow the Li bond with special features. As one of the most important applications of the element, Li batteries afford emerging opportunities for the exploration of Li bond chemistry. Herein, the historical development and concept of the Li bond are reviewed, in addition to the application of Li bonds in Li batteries. In this way, a comprehensive understanding of the Li bond in Li batteries and an outlook on its future developments is presented.

cycles, finally resulting in capacity fading, but also can penetrate through the separator, causing the short circuit and safety hazards. [8,14,15] Constructing a composite Li metal anode framework has been strongly considered to both retard the formation of Li dendrites and reduce the volume expansion. [14,[16][17][18][19][20] Among various host candidates, carbon materials, including carbon nanotubes, [21] graphene, [22,23] graphite paper, [24] graphene balls, [25] and carbon nanospheres, [26,27] have been widely probed due to their lightweight, high electrical conductivity, and large specific surface area. Pure carbon can only afford a weak interaction with Li metal, which renders a high specific interfacial energy and a large nucleation barrier. Therefore, heteroatomdoping strategies are often adopted to enhance the electrochemical performance of carbon hosts, and the working mechanism of doping sites is comprehensively investigated. [3,22,28] For instance, Foroozan et al. constructed a 3D conformal graphene oxide nanosheet to effectively regulate uniform Li deposition. [29] Through scanning electron microscopy and optical observations, they demonstrated that a dense and uniform deposition of Li could be achieved by the 3D conformal graphene oxide nanosheet.Defects are almost inevitably introduced during the synthesis of various carbon materials, especially the heteroatomdoped carbon. [3,[30][31][32] More importantly, carbon atoms in defects often play as the active sites in surface reactions as the unsaturated-coordination nature affords them a stronger interaction with reactants than the other atoms. In Li metal batteries, defective graphene was reported to increase the Coulombic efficiency and prevent dendritic growth. [33,34] However, Liu et al. reported that pristine graphene (PG) yields state-ofthe-art electrochemical performance with the post cycled metal surface, which is relatively smoother and more dendrite-free than defective graphene. [35] The different results induced by defects are originated from various defect types. Therefore, it is very important to understand the fundamental role of various defects in regulating the Li nucleation. If a comprehensive and deep understanding of defect chemistry can be built, highly lithiophilic carbon materials can be rationally designed through both defect engineering and heteroatom-doping strategies.

The quantitative structure–property relationship (QSPR) is a fundamental technique for evaluating and screening potentially valuable molecules in the field of drug discovery. There is an urgent need to speed up pharmaceutical research and development and a huge chemical space to explore, which necessitate effective and precise computer‐aided QSPR modeling methods. Previous studies with various deep learning models are limited because they are trained on separate small datasets, known as the small‐sample problem. Using transfer learning, this article describes a sparse sharing method that uses advanced graph‐based models to construct an efficient and reasonable multitask learning workflow for QSPR prediction. The proposed workflow is systematically and comprehensively tested with four benchmark datasets containing different targets, and several precisely predicted molecular examples are illustrated. The results demonstrate that an obvious improvement in the prediction of molecular properties is achieved, along with the ability to predict multiple properties simultaneously.

Standard therapies for heart failure with preserved ejection fraction (HFpEF) remain controversial. Vagus nerve stimulation (VNS) can downregulate extracellular matrix (ECM) expression and improve the prognosis of patients with heart failure. In order to verify whether the positive effect of VNS on HFpEF is feasible, HFpEF model constructed by Dahl salt-sensitive rats were subjected to VNS. Thirty male Dahl salt-sensitive rats were fed a high-salt diet (inducing HFpEF) and ten were fed a low-salt diet (controls) from the age of 7 weeks old. Roughly 12 weeks later, rats with HFpEF were randomly assigned to VNS (HF-VNS group, n = 13) and sham stimulation (HF-SS group, n = 13). Age-matched controls also underwent sham stimulation (control-SS group, n = 10). Cardiac function, myocardial hypertrophy, and fibrosis were evaluated after 72 h of treatment. Heart rate and systolic blood pressure decreased in rats receiving VNS compared with untreated counterparts. In addition, both systolic and diastolic cardiac function improved concurrently. The concentration of serum brain natriuretic peptide (BNP) concentration and the mRNA and protein expression of ECM proteins in serum and tissues, including collagen type I and III, connective tissue growth factor (CTGF), and transforming growth factor-β1 (TGF-β1) in serum and in tissue (mRNA and protein expression), were remarkably downregulated by VNS. VNS improved cardiac function and mitigated myocardial remodeling in Dahl salt-sensitive rats with HFpEF, which exhibited a good clinical application prospect.