University Town of Shenzhen

Efficient and reliable energy storage systems are crucial for our modern society. Lithium-ion batteries (LIBs) with excellent performance are widely used in portable electronics and electric vehicles (EVs), but frequent fires and explosions limit their further and more widespread applications. This review summarizes aspects of LIB safety and discusses the related issues, strategies, and testing standards. Specifically, it begins with a brief introduction to LIB working principles and cell structures, and then provides an overview of the notorious thermal runaway, with an emphasis on the effects of mechanical, electrical, and thermal abuse. The following sections examine strategies for improving cell safety, including approaches through cell chemistry, cooling, and balancing, afterwards describing current safety standards and corresponding tests. The review concludes with insights into potential future developments and the prospects for safer LIBs.

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and obtained remarkable performance. However, most of the existing CNN-based SISR methods mainly focus on wider or deeper architecture design, neglecting to explore the feature correlations of intermediate layers, hence hindering the representational power of CNNs. To address this issue, in this paper, we propose a second-order attention network (SAN) for more powerful feature expression and feature correlation learning. Specifically, a novel train- able second-order channel attention (SOCA) module is developed to adaptively rescale the channel-wise features by using second-order feature statistics for more discriminative representations. Furthermore, we present a non-locally enhanced residual group (NLRG) structure, which not only incorporates non-local operations to capture long-distance spatial contextual information, but also contains repeated local-source residual attention groups (LSRAG) to learn increasingly abstract feature representations. Experimental results demonstrate the superiority of our SAN network over state-of-the-art SISR methods in terms of both quantitative metrics and visual quality.

Sodium-ion batteries have captured widespread attention for grid-scale energy storage owing to the natural abundance of sodium. The performance of such batteries is limited by available electrode materials, especially for sodium-ion layered oxides, motivating the exploration of high compositional diversity. How the composition determines the structural chemistry is decisive for the electrochemical performance but very challenging to predict, especially for complex compositions. We introduce the "cationic potential" that captures the key interactions of layered materials and makes it possible to predict the stacking structures. This is demonstrated through the rational design and preparation of layered electrode materials with improved performance. As the stacking structure determines the functional properties, this methodology offers a solution toward the design of alkali metal layered oxides.

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem that aims to obtain a high-resolution output from one of its low-resolution versions. Recently, powerful deep learning algorithms have been applied to SISR and have achieved state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods and group them into two categories according to their contributions to two essential aspects of SISR: The exploration of efficient neural network architectures for SISR and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is first established, and several critical limitations of the baseline are summarized. Then, representative works on overcoming these limitations are presented based on their original content, as well as our critical exposition and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally, we conclude this review with some current challenges and future trends in SISR that leverage deep learning algorithms.

2D graphitic carbon nitride (GCN) nanosheets have attracted tremendous attention in photocatalysis due to their many intriguing properties. However, the photocatalytic performance of GCN nanosheets is still restricted by the limited active sites and the serious aggregation during the photocatalytic process. Herein, a simple approach to produce holey GCN (HGCN) nanosheets with abundant in‐plane holes by thermally treating bulk GCN (BGCN) under an NH 3 atmosphere is reported. These formed in‐plane holes not only endow GCN nanosheets with more exposed active edges and cross‐plane diffusion channels that greatly speed up mass and photogenerated charge transfer, but also provide numerous boundaries and thus decrease the aggregation. Compared to BGCN, the resultant HGCN has a much higher specific surface area of 196 m 2 g −1 , together with an enlarged bandgap of 2.95 eV. In addition, the HGCN is demonstrated to be self‐modified with carbon vacancies that make HGCN show much broader light absorption extending to the near‐infrared region, a higher donor density, and remarkably longer lifetime of charge carriers. As such, HGCN has a much higher photocatalytic hydrogen production rate of nearly 20 times the rate of BGCN.

Exceptionally high OER & HER performances were achieved by rationally designing the electrode structure of non-noble NiFe materials.

The mixed halide perovskites have emerged as outstanding light absorbers for efficient solar cells. Unfortunately, it reveals inhomogeneity in these polycrystalline films due to composition separation, which leads to local lattice mismatches and emergent residual strains consequently. Thus far, the understanding of these residual strains and their effects on photovoltaic device performance is absent. Herein we study the evolution of residual strain over the films by depth-dependent grazing incident X-ray diffraction measurements. We identify the gradient distribution of in-plane strain component perpendicular to the substrate. Moreover, we reveal its impacts on the carrier dynamics over corresponding solar cells, which is stemmed from the strain induced energy bands bending of the perovskite absorber as indicated by first-principles calculations. Eventually, we modulate the status of residual strains in a controllable manner, which leads to enhanced PCEs up to 20.7% (certified) in devices via rational strain engineering.

Abstract Lithium–sulfur (Li–S) battery has emerged as one of the most promising next‐generation energy‐storage systems. However, the shuttle effect greatly reduces the battery cycle life and sulfur utilization, which is great deterrent to its practical use. This paper reviews the tremendous efforts that are made to find a remedy for this problem, mostly through physical or chemical confinement of the lithium polysulfides (LiPSs). Intrinsically, this “confinement” has a relatively limited effect on improving the battery performance because in most cases, the LiPSs are “passively” blocked and cannot be reused. Thus, this strategy becomes less effective with a high sulfur loading and ultralong cycling. A more “positive” method that not only traps but also increases the subsequent conversion of LiPSs back to lithium sulfides is urgently needed to fundamentally solve the shuttle effect. Here, recent advances on catalytic effects in increasing the rate of conversion of soluble long‐chain LiPSs to insoluble short‐chain Li 2 S 2 /Li 2 S, and vice versa, are reviewed, and the roles of noble metals, metal oxides, metal sulfides, metal nitrides, and some metal‐free materials in this process are highlighted. Challenges and potential solutions for the design of catalytic cathodes and interlayers in Li–S battery are discussed in detail.

A long-life, high-capacity, highly safe and wearable solid-state zinc ion battery was constructed using a novel gelatin and PAM based electrolyte.

Abstract Atomic interface regulation is thought to be an efficient method to adjust the performance of single atom catalysts. Herein, a practical strategy was reported to rationally design single copper atoms coordinated with both sulfur and nitrogen atoms in metal-organic framework derived hierarchically porous carbon (S-Cu-ISA/SNC). The atomic interface configuration of the copper site in S-Cu-ISA/SNC is detected to be an unsymmetrically arranged Cu-S 1 N 3 moiety. The catalyst exhibits excellent oxygen reduction reaction activity with a half-wave potential of 0.918 V vs. RHE. Additionally, through in situ X-ray absorption fine structure tests, we discover that the low-valent Cuprous-S 1 N 3 moiety acts as an active center during the oxygen reduction process. Our discovery provides a universal scheme for the controllable synthesis and performance regulation of single metal atom catalysts toward energy applications.

2D black phosphorus (BP) nanomaterials are presented as a delivery platform. The endocytosis pathways and biological activities of PEGylated BP nanosheets in cancer cells are revealed for the first time. Finally, a triple-response combined therapy strategy is achieved by PEGylated BP nanosheets, showing a promising and enhanced antitumor effect. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

A 3D porous Cu current collector is fabricated through chemical dealloying from a commerial Cu–Zn alloy tape. The interlinked porous framework naturally integrated can accommodate Li deposition, suppressing dendrite growth and alleviating the huge volume change during cycling. The Li metal anode combined with such a porous Cu collector demonstrates excellent performance and commerial potentials in Li-based secondary batteries. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Abstract The development of single molecule white light emitters is extremely challenging for pure phosphorescent metal-free system at room temperature. Here we report a single pure organic phosphor, namely 4-chlorobenzoyldibenzothiophene, emitting white room temperature phosphorescence with Commission Internationale de l’Éclair-age coordinates of (0.33, 0.35). Experimental and theoretical investigations reveal that the white light emission is emerged from dual phosphorescence, which emit from the first and second excited triplet states. We also demonstrate the validity of the strategy to achieve metal-free pure phosphorescent single molecule white light emitters by intrasystem mixing dual room temperature phosphorescence arising from the low- and high-lying triplet states.

In recent years, machine learning techniques have been widely used to solve many problems for fault diagnosis. However, in many real-world fault diagnosis applications, the distribution of the source domain data (on which the model is trained) is different from the distribution of the target domain data (where the learned model is actually deployed), which leads to performance degradation. In this paper, we introduce domain adaptation, which can find the solution to this problem by adapting the classifier or the regression model trained in a source domain for use in a different but related target domain. In particular, we proposed a novel deep neural network model with domain adaptation for fault diagnosis. Two main contributions are concluded by comparing to the previous works: first, the proposed model can utilize domain adaptation meanwhile strengthening the representative information of the original data, so that a high classification accuracy in the target domain can be achieved, and second, we proposed several strategies to explore the optimal hyperparameters of the model. Experimental results, on several real-world datasets, demonstrate the effectiveness and the reliability of both the proposed model and the exploring strategies for the parameters.

A 3D network gel polymer electrolyte (3D-GPE) is designed for lithium metal batteries and prepared by an initiator-free one-pot ring-opening polymerization technique. This 3D-GPE exhibits an unprecedented combination of mechanical strength, ionic conductivity, and more importantly, effective suppression of Li dendrite growth. The produced lithium-based battery presents long life, high rate, and excellent safety. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

The electrochemical behavior of a lithium/sulfur (Li/S) battery was studied by electrochemical impedance spectroscopy (EIS). An impedance model based on the analysis of EIS spectra as a function of temperature and depth of discharge was developed. Then, by monitoring the evolution of impedance during the cycling process, the capacity fading mechanism of Li/S battery was investigated. The results show that the semicircle at the middle frequency of the EIS spectra is ascribed to the charge-transfer process and the semicircle at high frequency is related to the interphase contact resistance. Furthermore, electrolyte resistance, interphase contact resistance, and charge-transfer resistance vary with cycle number in different manners, and the charge-transfer resistance is the key factor contributing to the capacity fading of Li/S battery.

MicroRNAs (miRNAs) are a class of 20-24 nt non-coding RNAs that regulate gene expression primarily through post-transcriptional repression or mRNA degradation in a sequence-specific manner. The roles of miRNAs are just beginning to be understood, but the study of miRNA function has been limited by poor understanding of the general principles of gene regulation by miRNAs. Here we used CNE cells from a human nasopharyngeal carcinoma cell line as a cellular system to investigate miRNA-directed regulation of VEGF and other angiogenic factors under hypoxia, and to explore the principles of gene regulation by miRNAs. Through computational analysis, 96 miRNAs were predicted as putative regulators of VEGF. But when we analyzed the miRNA expression profile of CNE and four other VEGF-expressing cell lines, we found that only some of these miRNAs could be involved in VEGF regulation, and that VEGF may be regulated by different miRNAs that were differentially chosen from 96 putative regulatory miRNAs of VEGF in different cells. Some of these miRNAs also co-regulate other angiogenic factors (differential regulation and co-regulation principle). We also found that VEGF was regulated by multiple miRNAs using different combinations, including both coordinate and competitive interactions. The coordinate principle states that miRNAs with independent binding sites in a gene can produce coordinate action to increase the repressive effect of miRNAs on this gene. By contrast, the competitive principle states when multiple miRNAs compete with each other for a common binding site, or when a functional miRNA competes with a false positive miRNA for the same binding site, the repressive effects of miRNAs may be decreased. Through the competitive principle, false positive miRNAs, which cannot directly repress gene expression, can sometimes play a role in miRNA-mediated gene regulation. The competitive principle, differential regulation, multi-miRNA binding sites, and false positive miRNAs might be useful strategies in the avoidance of unwanted cross-action among genes targeted by miRNAs with multiple targets.

The increasing demands of energy storage require the significant improvement of current Li-ion battery electrode materials and the development of advanced electrode materials. Thus, it is necessary to gain an in-depth understanding of the reaction processes, degradation mechanism, and thermal decomposition mechanisms under realistic operation conditions. This understanding can be obtained by in situ/operando characterization techniques, which provide information on the structure evolution, redox mechanism, solid-electrolyte interphase (SEI) formation, side reactions, and Li-ion transport properties under operating conditions. Here, the recent developments in the in situ/operando techniques employed for the investigation of the structural stability, dynamic properties, chemical environment changes, and morphological evolution are described and summarized. The experimental approaches reviewed here include X-ray, electron, neutron, optical, and scanning probes. The experimental methods and operating principles, especially the in situ cell designs, are described in detail. Representative studies of the in situ/operando techniques are summarized, and finally the major current challenges and future opportunities are discussed. Several important battery challenges are likely to benefit from these in situ/operando techniques, including the inhomogeneous reactions of high-energy-density cathodes, the development of safe and reversible Li metal plating, and the development of stable SEI.

A macroscopic 3D porous graphitic carbon nitride (g-CN) monolith is prepared by the one-step thermal polymerization of urea inside the framework of a commercial melamine sponge and exhibits improved photocatalytic water-splitting performance for hydrogen evolution compared to g-CN powder due to the 3D porous interconnected network, larger specific surface area, better visible light capture, and superior charge-separation efficiency. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Abstract The detrimental shuttle effect in lithium–sulfur batteries mainly results from the mobility of soluble polysulfide intermediates and their sluggish conversion kinetics. Herein, presented is a multifunctional catalyst with the merits of strong polysulfides adsorption ability, superior polysulfides conversion activity, high specific surface area, and electron conductivity by in situ crafting of the TiO 2 ‐MXene (Ti 3 C 2 T x ) heterostructures. The uniformly distributed TiO 2 on MXene sheets act as capturing centers to immobilize polysulfides, the hetero‐interface ensures rapid diffusion of anchored polysulfides from TiO 2 to MXene, and the oxygen‐terminated MXene surface is endowed with high catalytic activity toward polysulfide conversion. The improved lithium–sulfur batteries deliver 800 mAh g −1 at 2 C and an ultralow capacity decay of 0.028% per cycle over 1000 cycles at 2 C. Even with a high sulfur loading of 5.1 mg cm −2 , the capacity retention of 93% after 200 cycles is still maintained. This work sheds new insights into the design of high‐performance catalysts with manipulated chemical components and tailored surface chemistry to regulate polysulfides in Li–S batteries.