49 research outputs found

    High-Capacity, Dendrite-Free, and Ultrahigh-Rate Lithium-Metal Anodes Based on Monodisperse N-Doped Hollow Carbon Nanospheres

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    To unlock the great potential of lithium metal anodes for high-performance batteries, a number of critical challenges must be addressed. The uncontrolled dendrite growth and volume changes during cycling (especially, at high rates) will lead to short lifespan, low Coulombic efficiency (CE), and security risks of the batteries. Here it is reported that Li metal anodes, employing the monodisperse, lithiophilic, robust, and large-cavity N-doped hollow carbon nanospheres (NHCNSs) as the host, show remarkable performances—high areal capacity (10 mAh cm−2), high CE (up to 99.25% over 500 cycles), complete suppression of dendrite growth, dense packing of Li anode, and an extremely smooth electrode surface during repeated Li plating/stripping. In symmetric cells, a highly stable voltage hysteresis over a long cycling life >1200 h is achieved, and a low and stable voltage hysteresis can be realized even at an ultrahigh current density of 64 mA cm−2. Furthermore, the NHCNSs-based anodes, when paired with a LiFePO4 (LFP) cathode in full cells, give rise to highly improved rate capability (104 mAh g−1 at 10 C) and cycling stability (91.4% capacity retention for 200 cycles), enabling a promising candidate for the next-generation high energy/power density batteries

    Strategies for Exploring Functions from Dynamic Combinatorial Libraries

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    Dynamic combinatorial chemistry (DCC) is a powerful approach for creating complex chemical systems, giving access to the studies of complexity and exploration of functionality in synthetic systems. However, compared with more advanced living systems, the man‐made chemical systems are still less functional, due to their limited complexity and insufficient kinetic control. Here we start by introducing strategies to enrich the complexity of dynamic combinatorial libraries (DCLs) for exploiting unexpected functions by increasing the species of building blocks and/or templates used. Then, we discuss how dynamic isomerization of photo‐switchable molecules help DCLs increase and alter the systemic complexity in‐situ. Multi‐phase DCLs will also be reviewed to thrive complexity and functionality across the interfaces. Finally, there will be a summary and outlook about remote kinetic control in DCLs that are realized by applying exogenous physical transduction signals of stress, light, heat and ultrasound.</p

    Preparation and Properties of Liquefied Banana Pseudo-stem based PVAc Membrane

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    A series of novel membrane materials were prepared based on liquefied banana pseudo-stem (LBPS) blended with various proportions of polyvinyl acetate emulsion (PVAc). The mechanical properties, structure, thermal stability, and cross-sectional morphologies were investigated using a universal testing machine, Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and scanning electron microscopy (SEM), respectively. The addition of LBPS to PVAc led to a structural change, and this change depended on the reaction temperature. The enhancement of elongation and the thermostability of membranes is attributed to an increase in C-O-C groups. Furthermore, the LBPS/PVAc membranes have a higher water resistance

    Microstructural, Thermal, and Tensile Characterization of Banana Pseudo-stem Fibers Obtained with Mechanical, Chemical, and Enzyme Extraction

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    Banana pseudo-stem fibers (BPSFs) have desirable tensile properties. In this study, BPSFs were extracted using mechanical, chemical, and enzymatic methods. The aim was to evaluate the effect of these three extraction methods on the tensile, thermal, and morphological properties of BPSFs. Microstructural analysis showed the presence of structural and arch fibers in banana pseudo-stem (BPS). The average tensile strength and elongation for mechanically, chemically, and enzyme-extracted BPSFs were 210, 333, and 235 MPa, and 0.8%, 1.6%, and 1.4%, respectively. Young’s modulus was enhanced by 19.1% in the mechanically extracted BPSFs compared with that of chemically extracted BPSFs. The morphology of BPSFs was correlated with their tensile properties via scanning electron microscopy (SEM) image analysis. Fourier transform infra-red (FTIR) and X-ray diffraction (XRD) analyses of fibers showed that chemically extracted BPSFs contained less hemicellulose and lignin with a crystallinity index of 61.2%. Chemically extracted BPSFs exhibited enhanced thermal properties over mechanically extracted BPSFs. Mechanically extracted BPSFs demonstrated similar thermal and tensile properties to chemically and enzyme-extracted BPSFs. Thus, mechanically extracted BPSFs could act as highly suitable reinforcing agents in bio-based composite material preparation. Given that mechanical methods need no chemicals and they are environmentally friendly, such techniques have potential applications

    Recent Advanced Development of Acid-Resistant Thin-Film Composite Nanofiltration Membrane Preparation and Separation Performance in Acidic Environments

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    Membrane filtration technology has attracted extensive attention in academia and industry due to its advantages of eco-friendliness related to environmental protection and high efficiency. Polyamide thin-film composite nanofiltration (PA TFC NF) membranes have been widely used due to their high separation performance. Non-acid-resistant PA TFC NF membranes face tremendous challenges in an acidic environment. Novel and relatively acid-resistant polysulfonamide-based and triazine-based TFC NF membranes have been developed, but these have a serious trade-off in terms of permeability and selectivity. Hence, how to improve acid resistance of TFC NF membranes and their separation performance in acidic environments is a pivotal issue for the design and preparation of these membranes. This review first highlights current strategies for improving the acid resistance of PA TFC NF membranes by regulating the composition and structure of the separation layer of the membrane performed by manipulating and optimizing the construction method and then summarizes the separation performances of these acid-resistant TFC NF membranes in acidic environments, as studied in recent years

    Numerical Simulation Method for Tunnel Excavation Considering Mechanical Characteristic Variation of Soft Rock with the Confining Pressure Influence

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    The accurate prediction and evaluation of stress and displacement fields of surrounding rock is the fundamental premise for the deformation control of soft rock tunnels under high geo-stress condition. However, due to the complicated mechanical characteristics of soft rock with confining pressure influence, the current numerical simulation method usually regards the mechanical parameters of surrounding rock as constant and ignores the variation of these parameters in the simulation process, which leads to results that cannot accurately reflect the mechanical behavior of surrounding rock. Therefore, this paper firstly investigates the effect of confining pressure on deformation and strength parameters for soft rock and proposes corresponding variable models for mechanical parameters with the confining pressure influence. Secondly, a transversal loop discriminant update procedure is proposed and introduced into the iteration calculation process of FLAC3D, thus forming an improved numerical simulation method. This improved method can integrally consider the mechanical parameter variation of surrounding rock with variable confining pressure and realize the automatic update for such a parameter with its variable stress state. Finally, as an application example, an improved expression of longitudinal deformation profile (LDP) for tunnels considering the confining pressure influence is proposed based on numerous simulation results for a soft rock tunnel obtained by this proposed method

    Strategies for Exploring Functions from Dynamic Combinatorial Libraries

    No full text
    Dynamic combinatorial chemistry (DCC) is a powerful approach for creating complex chemical systems, giving access to the studies of complexity and exploration of functionality in synthetic systems. However, compared with more advanced living systems, the man‐made chemical systems are still less functional, due to their limited complexity and insufficient kinetic control. Here we start by introducing strategies to enrich the complexity of dynamic combinatorial libraries (DCLs) for exploiting unexpected functions by increasing the species of building blocks and/or templates used. Then, we discuss how dynamic isomerization of photo‐switchable molecules help DCLs increase and alter the systemic complexity in‐situ. Multi‐phase DCLs will also be reviewed to thrive complexity and functionality across the interfaces. Finally, there will be a summary and outlook about remote kinetic control in DCLs that are realized by applying exogenous physical transduction signals of stress, light, heat and ultrasound.peerReviewe

    The utility of long non-coding RNAs in chronic obstructive pulmonary disease: a comprehensive analysis

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    Abstract Objectives Chronic obstructive pulmonary disease (COPD) is one of the main causes of morbidity and mortality in the world. However, there are some patients who are not diagnosed early and correctly through routine methods because of inconspicuous or serious symptoms. This study aims to assess the diagnostic role of long non-coding RNA (lncRNA) in COPD. Methods We searched literature from electronic databases, after excluding non-COPD literature, the bibliometric analysis was performed, and VOSviewer software was used to represent the data analyzed. Literature evaluating the diagnostic test accuracy of lncRNA for COPD was eligible, and the QUADAS-2 checklist was used to evaluate the quality. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (sROC) were used to analyze the overall diagnostic performance. Subgroup and meta-regression analyses were performed to explore the heterogeneity, and a funnel plot was assessed for publication bias. Also, lncRNAs related to COPD were identified and explored for their potential biological function. Results An increased annual growth rate of literature on this subject from 2016 focused on COPD, humans, RNA, and lncRNA. The meta-analysis enrolled 17 literature indicated that the SEN, SPE, and DOR differentiating COPD patients from normal controls (NCs) were 0.86 (95% CI [0.80, 0.90]), 0.78 (95% CI [0.67, 0.86]), and 21.59 (95% CI [11.39, 40.91]), respectively. Meanwhile, lncRNAs had the ability to distinguish acute exacerbations of COPD (AECOPD) patients from COPD; the SEN, SPE, and DOR were 0.75 (95% CI [0.62, 0.85]), 0.81 (95% CI [0.71, 0.89]), and 13.02 (95% CI [7.76, 21.85]), respectively. The area under the sROC were calculated to be greater than 0.8 at least. Subgroup and meta-regression analysis showed that the types of specimens and dysregulated lncRNAs might affect the diagnostic accuracy. The funnel plot showed there was a certain publication bias. 41 lncRNAs related to COPD were identified and mainly located in the nucleus and cytoplasm, associated with proliferation, invasion, and prognosis. These lncRNA-binding proteins were involved in the spliceosome, Rap1 signaling pathway, MAPK signaling pathway, and so on. Conclusion LncRNA suggests potential diagnostic biomarkers and therapeutic targets for COPD patients
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