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Stable plating/stripping of metal electrodes under high power and high capacity remains a great challenge. Tailoring the deposition behavior on the substrate could partly resolve dendrites’ formation, but it usually works only under low current densities and limited capacities. Here we turn to regulate the separator’s interfacial chemistry through tin coating with decent conductivity and excellent zincophilicity. The former homogenizes the electric field distribution for smooth zinc metal on the substrate, while the latter enables the concurrent zinc deposition on the separator with a face-to-face growth. Consequently, dendrite-free zinc morphologies and superior cycling stability are achieved at simultaneous high current densities and large cycling capacities (1000 h at 5 mA/cm 2 for 5 mAh/cm 2 and 500 h at 10 mA/cm 2 for 10 mAh/cm 2 ). Furthermore, the concept could be readily extended to sodium metal anodes, demonstrating the interfacial chemistry regulation of separator is a promising route to circumvent the metal anode challenges. Zinc metal anodes suffer from severe dendrites’ growth. Herewith authors construct electrically conductive and zincophilic tin coating on separator to suppress dendrites initiation and eliminate the inevitably formed dendrites.

Covalent organic frameworks (COFs) have emerged as a new class of crystalline porous materials prepared by integrating organic molecular building blocks into predetermined network structures entirely through strong covalent bonds. The consequently encountered “crystallization problem” has been conquered by dynamic covalent chemistry in syntheses and reticular chemistry in materials design. In this contribution, we have reviewed the progress in the crystallization of COF materials and their hydrogen, methane and carbon dioxide gas storage properties for clean energy applications.

Crystal size effect is of vital importance in materials science by exerting significant influence on various properties of materials and furthermore their functions. Crystal size effect of covalent organic frameworks (COFs) has never been reported because their controllable synthesis is difficult, despite their promising properties have been exhibited in many aspects. Here, we report the diverse crystal size effects of two representative COFs based on the successful realization of crystal-size-controlled synthesis. For LZU-111 with rigid spiral channels, size effect reflects in pore surface area by influencing the pore integrity, while for flexible COF-300 with straight channels, crystal size controls structural flexibility by altering the number of repeating units, which eventually changes sorption selectivity. With the understanding and insight of the structure-property correlation not only at microscale but also at mesoscale for COFs, this research will push the COF field step forward to a significant advancement in practical applications. Crystal size effects are of vital importance to understand various properties and functions of a material but have not been reported for Covalent Organic Frameworks (COFs). Here, the authors report a crystal-size-controlled synthesis of two COFs and look into different crystal size effects.

Ozone is one of the most important air pollutants, with significant impacts on human health, regional air quality and ecosystems. In this study, we use geographic information and environmental information of the monitoring site of 5577 regions in the world from 2010 to 2014 as feature input to predict the long-term average ozone concentration of the site. A Bayesian optimization-based XGBoost-RFE feature selection model BO-XGBoost-RFE is proposed, and a variety of machine learning algorithms are used to predict ozone concentration based on the optimal feature subset. Since the selection of the underlying model hyperparameters is involved in the recursive feature selection process, different hyperparameter combinations will lead to differences in the feature subsets selected by the model, so that the feature subsets obtained by the model may not be optimal solutions. We combine the Bayesian optimization algorithm to adjust the parameters of recursive feature elimination based on XGBoost to obtain the optimal parameter combination and the optimal feature subset under the parameter combination. Experiments on long-term ozone concentration prediction on a global scale show that the prediction accuracy of the model after Bayesian optimized XGBoost-RFE feature selection is higher than that based on all features and on feature selection with Pearson correlation. Among the four prediction models, random forest obtained the highest prediction accuracy. The XGBoost prediction model achieved the greatest improvement in accuracy.

Among all three-dimensional (3D) printing materials, thermosetting photopolymers claim almost half of the market, and have been widely used in various fields owing to their superior mechanical stability at high temperatures, excellent chemical resistance as well as good compatibility with high-resolution 3D printing technologies. However, once these thermosetting photopolymers form 3D parts through photopolymerization, the covalent networks are permanent and cannot be reprocessed, i.e., reshaped, repaired, or recycled. Here, we report a two-step polymerization strategy to develop 3D printing reprocessable thermosets (3DPRTs) that allow users to reform a printed 3D structure into a new arbitrary shape, repair a broken part by simply 3D printing new material on the damaged site, and recycle unwanted printed parts so the material can be reused for other applications. These 3DPRTs provide a practical solution to address environmental challenges associated with the rapid increase in consumption of 3D printing materials. Thermosetting polymers are widely used in 3D printing owing to their superior mechanical stability, but once they are printed, the highly crosslinked polmyers cannot be reprocessed or repaired. Here the authors demonstrate a two-step polymerization strategy toward 3D printing of reprocessable thermosets.

With the increasing number of long tunnelling and urban subway constructions, mixed-face ground conditions are frequently encountered. Rock fragmentation mechanism under disc cutter cutting in TBM tunneling through the mixed-face ground is complex and can lead to engineering difficulties. During TBM tunneling in mixed-face ground with soft rock in upper layer and hard rock in the lower layer, reduction of the advance rate and reduced rotational speed of cutter head occur compared with homogeneous ground. As a result, the muck in the working chamber cannot be replaced timely, leading to the formation of mud cake. Additionally, the disc cutters cannot rotate normally and are worn eccentrically and severely. Finally, the cutters collide with hard rock periodically at the interface between soft and hard rock, thus being subject to a huge impact load, even overload on some cutters, resulting in chipping of the cutter ring and damage to the cutter holder. This paper presents numerical analysis of the disc cutter cutting process considering the difference of rock-cutting behaviors of disc cutters in the mixed-face ground with the aid of PFC3D code. Based on the forces imposed on the disc cutter and rock crack propagation, TBM tunneling in the mixed-face ground is investigated. The decrease of the mean rolling force of the disc cutter causes rotation hindering in the disc cutter in soft rock stratum leading to flat cutter wear. The gap of the normal force between the soft rock and hard rock generates the overturning moment of the cutter head, which causes the eccentricity and vibration of the cutter head.

Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity 1 – 3 , but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible 4 , 5 . More reversible chemistry can improve crystallinity 6 – 9 , but this typically yields COFs with poor physicochemical stability and limited application scope 5 . Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h −1  g −1 . This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control. A protocol in which monomers are pre-organized using a reversible and removable urea linkage enables the production of covalent organic frameworks with higher crystallinity and porosity than those produced using standard approaches with randomly aligned monomers.

Nuclear localization signals (NLS) are generally short peptides that act as a signal fragment that mediates the transport of proteins from the cytoplasm into the nucleus. This NLS-dependent protein recognition, a process necessary for cargo proteins to pass the nuclear envelope through the nuclear pore complex, is facilitated by members of the importin superfamily. Here, we summarized the types of NLS, focused on the recently reported related proteins containing nuclear localization signals, and briefly summarized some mechanisms that do not depend on nuclear localization signals into the nucleus. 9b35b5XrF5YBVYeQB6JADF Video Abstract

Molecular recognition is an attractive approach to designing sensitive and selective sensors for volatile organic compounds (VOCs). Although organic macrocycles and cages have been well-developed for recognising organics by their adaptive pockets in liquids, porous solids for gas detection require a deliberate design balancing adaptability and robustness. Here we report a dynamic 3D covalent organic framework (dynaCOF) constructed from an environmentally sensitive fluorophore that can undergo concerted and adaptive structural transitions upon adsorption of gas and vapours. The COF is capable of rapid and reliable detection of various VOCs, even for non-polar hydrocarbon gas under humid conditions. The adaptive guest inclusion amplifies the host-guest interactions and facilitates the differentiation of organic vapours by their polarity and sizes/shapes, and the covalently linked 3D interwoven networks ensure the robustness and coherency of the materials. The present result paves the way for multiplex fluorescence sensing of various VOCs with molecular-specific responses. Organic macrocycles and cages have been well-developed as porous solids for gas detection but balancing adaptability and robustness in these materials remains challenging. Here, the authors report a dynamic 3D covalent organic framework that can undergo concerted and adaptive structural transitions upon adsorption of gas and vapours.

Accurate measurements and assessments of gas adsorption isotherms are important to characterize porous materials and develop their applications. Although these isotherms provide knowledge of the overall gas uptake within a material, they do not directly give critical information concerning the adsorption behaviour of adsorbates in each individual pore, especially in porous materials in which multiple types of pore are present. Here we show how gas adsorption isotherms can be accurately decomposed into multiple sub-isotherms that correspond to each type of pore within a material. Specifically, two metal–organic frameworks, PCN-224 and ZIF-412, which contain two and three different types of pore, respectively, were used to generate isotherms of individual pores by combining gas adsorption measurements with in situ X-ray diffraction. This isotherm decomposition approach gives access to information about the gas uptake capacity, surface area and accessible pore volume of each individual pore, as well as the impact of pore geometry on the uptake and distribution of different adsorbates within the pores. Gas sorption studies in porous materials typically reflect their overall gas uptake. Now, using a ‘gas adsorption crystallography’ method, the gas adsorption isotherms of two metal–organic frameworks (MOFs) have been quantitatively decomposed into sub-isotherms that reflect the pore-filling behaviour of various guests in the different types of pores present in the MOFs.