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Showing papers by "Shanghai University published in 2018"


Journal ArticleDOI
TL;DR: In this article, the authors describe the implementation of real-space refinement in the phenixreal_space-refine program from the PHENIX suite, which makes use of extra information such as secondary-structure and rotamer-specific restraints.
Abstract: This article describes the implementation of real-space refinement in the phenixreal_space_refine program from the PHENIX suite The use of a simplified refinement target function enables very fast calculation, which in turn makes it possible to identify optimal data-restraint weights as part of routine refinements with little runtime cost Refinement of atomic models against low-resolution data benefits from the inclusion of as much additional information as is available In addition to standard restraints on covalent geometry, phenixreal_space_refine makes use of extra information such as secondary-structure and rotamer-specific restraints, as well as restraints or constraints on internal molecular symmetry The re-refinement of 385 cryo-EM-derived models available in the Protein Data Bank at resolutions of 6 A or better shows significant improvement of the models and of the fit of these models to the target maps

1,748 citations


Journal ArticleDOI
01 Mar 2018-Nature
TL;DR: This work combines Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps that solve for almost twice as many molecules, thirty times faster than the traditional computer-aided search method.
Abstract: To plan the syntheses of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis would be a valuable tool but at present it is slow and provides results of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion policy network that guides the search, and a filter network to pre-select the most promising retrosynthetic steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for almost twice as many molecules, thirty times faster than the traditional computer-aided search method, which is based on extracted rules and hand-designed heuristics. In a double-blind AB test, chemists on average considered our computer-generated routes to be equivalent to reported literature routes.

1,146 citations


Journal ArticleDOI
TL;DR: This work shows that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing, and demonstrates that the properties of the generated molecules correlate very well with those of the molecules used to train the model.
Abstract: In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active toward a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target. Against Staphylococcus aureus, the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria), it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecule...

1,041 citations


Journal ArticleDOI
26 Mar 2018
TL;DR: In this article, a review of state-of-the-art modeling progress in the investigation of solid electrolyte interphase (SEI) films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design.
Abstract: A passivation layer called the solid electrolyte interphase (SEI) is formed on electrode surfaces from decomposition products of electrolytes. The SEI allows Li+ transport and blocks electrons in order to prevent further electrolyte decomposition and ensure continued electrochemical reactions. The formation and growth mechanism of the nanometer thick SEI films are yet to be completely understood owing to their complex structure and lack of reliable in situ experimental techniques. Significant advances in computational methods have made it possible to predictively model the fundamentals of SEI. This review aims to give an overview of state-of-the-art modeling progress in the investigation of SEI films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design. Multi-scale simulations have been summarized and compared with each other as well as with experiments. Computational details of the fundamental properties of SEI, such as electron tunneling, Li-ion transport, chemical/mechanical stability of the bulk SEI and electrode/(SEI/) electrolyte interfaces have been discussed. This review shows the potential of computational approaches in the deconvolution of SEI properties and design of artificial SEI. We believe that computational modeling can be integrated with experiments to complement each other and lead to a better understanding of the complex SEI for the development of a highly efficient battery in the future.

897 citations


Journal ArticleDOI
TL;DR: This tutorial review provides a structured description of the main classes of organic photothermal agents and their characteristics and highlights recent advances in using PTT agents to address various cancers indications.
Abstract: Over the last decade, organic photothermal therapy (PTT) agents have attracted increasing attention as a potential complement for, or alternative to, classical drugs and sensitizers involving inorganic nanomaterials. In this tutorial review, we provide a structured description of the main classes of organic photothermal agents and their characteristics. Representative agents that have been studied in the context of photothermal therapy since 2000 are summarized and recent advances in using PTT agents to address various cancers indications are highlighted.

891 citations


Journal ArticleDOI
TL;DR: A soft carbon anode, namely highly nitrogen-doped soft carbon nanofibers, with superior rate capability and cyclability based on a surface dominated charge storage mechanism is reported.
Abstract: Potassium-ion batteries are a promising alternative to lithium-ion batteries. However, it is challenging to achieve fast charging/discharging and long cycle life with the current electrode materials because of the sluggish potassiation kinetics. Here we report a soft carbon anode, namely highly nitrogen-doped carbon nanofibers, with superior rate capability and cyclability. The anode delivers reversible capacities of 248 mAh g–1 at 25 mA g–1 and 101 mAh g–1 at 20 A g–1, and retains 146 mAh g–1 at 2 A g–1 after 4000 cycles. Surface-dominated K-storage is verified by quantitative kinetics analysis and theoretical investigation. A full cell coupling the anode and Prussian blue cathode delivers a reversible capacity of 195 mAh g–1 at 0.2 A g–1. Considering the cost-effectiveness and material sustainability, our work may shed some light on searching for K-storage materials with high performance. The development of potassium ion batteries calls for cheap, sustainable, and high-performance electrode materials. Here, the authors report a highly nitrogen-doped soft carbon anode that exhibits superior rate capability and cyclability based on a surface dominated charge storage mechanism.

855 citations



Journal ArticleDOI
08 Oct 2018
TL;DR: Li et al. as mentioned in this paper showed that single-atom catalysts can be synthesized directly from bulk metals using an ammonia atmosphere, owing to the formation of volatile metal-ammonia species that are trapped by the nitrogen-rich carbon support.
Abstract: Single-atom catalysts exhibit intriguing properties and receive widespread interest for their effectiveness in promoting a variety of catalytic reactions, making them highly desired motifs in materials science. However, common approaches to the synthesis of these materials often require tedious procedures and lack appropriate interactions between the metal atoms and supports. Here, we report a simple and practical strategy to access the large-scale synthesis of single-atom catalysts via direct atoms emitting from bulk metals, and the subsequent trapping on nitrogen-rich porous carbon with the assistance of ammonia. First, the ammonia coordinates with the copper atoms to form volatile Cu(NH3)x species based on the strong Lewis acid–base interaction. Then, following transportation under an ammonia atmosphere, the Cu(NH3)x species are trapped by the defects on the nitrogen-rich carbon support, forming the isolated copper sites. This strategy is readily scalable and has been confirmed as feasible for producing functional single-atom catalysts at industrial levels. Single-atom catalysts have proven successful in many catalytic applications. Now, Li, Wu and co-workers show that single-atom catalysts can be prepared directly from bulk metals using an ammonia atmosphere, owing to the formation of volatile metal–ammonia species that are trapped by the nitrogen-rich carbon support.

646 citations


Journal ArticleDOI
TL;DR: It is confirmed that sewage sludge discharge is an important source of microplastic (MP) pollution in the environment and further evaluation of the associated environmental hazards with MPs is deemed necessary.

600 citations


Journal ArticleDOI
TL;DR: The current understanding of biogenesis and gene regulatory mechanisms of circRNAs is provided, the recent studies oncircRNAs as potential diagnostic and prognostic biomarkers are summarized, and the major advantages and limitations of circ RNAs as novel biomarkers based on existing knowledge are highlighted.

515 citations


Journal ArticleDOI
TL;DR: New methods and PHENIX tools for quality assessment of cryo-EM maps, atomic models and model-to-map fitting are presented and results of systematic application of these tools to high-resolution cryospecies maps and corresponding atomic models are analyzed and discussed.
Abstract: Recent advances in the field of electron cryomicroscopy (cryo-EM) have resulted in a rapidly increasing number of atomic models of biomacromolecules that have been solved using this technique and deposited in the Protein Data Bank and the Electron Microscopy Data Bank. Similar to macromolecular crystallography, validation tools for these models and maps are required. While some of these validation tools may be borrowed from crystallography, new methods specifically designed for cryo-EM validation are required. Here, new computational methods and tools implemented in PHENIX are discussed, including d99 to estimate resolution, phenix.auto_sharpen to improve maps and phenix.mtriage to analyze cryo-EM maps. It is suggested that cryo-EM half-maps and masks should be deposited to facilitate the evaluation and validation of cryo-EM-derived atomic models and maps. The application of these tools to deposited cryo-EM atomic models and maps is also presented.

Journal ArticleDOI
TL;DR: The authors discover copper-containing complexes to reversibly transform during electrocatalysis into methane-producing copper nanoclusters that catalyzes the carbon dioxide-to-methane conversion.
Abstract: Restructuring-induced catalytic activity is an intriguing phenomenon of fundamental importance to rational design of high-performance catalyst materials. We study three copper-complex materials for electrocatalytic carbon dioxide reduction. Among them, the copper(II) phthalocyanine exhibits by far the highest activity for yielding methane with a Faradaic efficiency of 66% and a partial current density of 13 mA cm−2 at the potential of – 1.06 V versus the reversible hydrogen electrode. Utilizing in-situ and operando X-ray absorption spectroscopy, we find that under the working conditions copper(II) phthalocyanine undergoes reversible structural and oxidation state changes to form ~ 2 nm metallic copper clusters, which catalyzes the carbon dioxide-to-methane conversion. Density functional calculations rationalize the restructuring behavior and attribute the reversibility to the strong divalent metal ion–ligand coordination in the copper(II) phthalocyanine molecular structure and the small size of the generated copper clusters under the reaction conditions.

Journal ArticleDOI
19 Sep 2018-Joule
TL;DR: A comprehensive overview of the application of VO2 to smart windows with particular emphasis on recent progress from the electronic, atomic, nano, and micron perspectives is provided in this article.

Journal ArticleDOI
TL;DR: The synthesis of a two-dimensional few-layered covalent organic framework trapped by carbon nanotubes as the anode of lithium-ion batteries is reported, paving the way to the development of high-capacity electrodes for organic rechargeable batteries.
Abstract: Conjugated polymeric molecules have been heralded as promising electrode materials for the next-generation energy-storage technologies owing to their chemical flexibility at the molecular level, environmental benefit, and cost advantage. However, before any practical implementation takes place, the low capacity, poor structural stability, and sluggish ion/electron diffusion kinetics remain the obstacles that have to be overcome. Here, we report the synthesis of a few-layered two-dimensional covalent organic framework trapped by carbon nanotubes as the anode of lithium-ion batteries. Remarkably, upon activation, this organic electrode delivers a large reversible capacity of 1536 mAh g−1 and can sustain 500 cycles at 100 mA g−1. Aided by theoretical calculations and electrochemical probing of the electrochemical behavior at different stages of cycling, the storage mechanism is revealed to be governed by 14-electron redox chemistry for a covalent organic framework monomer with one lithium ion per C=N group and six lithium ions per benzene ring. This work may pave the way to the development of high-capacity electrodes for organic rechargeable batteries. Conjugated polymeric molecules are promising electrode materials for batteries. Here the authors show a two-dimensional few-layered covalent organic framework that delivers a large reversible capacity of more than 1500 mAh g−1 with the storage mechanism governed by 14-electron redox chemistry.


Journal ArticleDOI
TL;DR: In this review, the materials, fabrication methods, and microparticle structures produced with droplet microfluidics are summarized and a comprehensive overview of their recent uses in biomedical applications is provided.
Abstract: Droplet microfluidics offers exquisite control over the flows of multiple fluids in microscale, enabling fabrication of advanced microparticles with precisely tunable structures and compositions in a high throughput manner The combination of these remarkable features with proper materials and fabrication methods has enabled high efficiency, direct encapsulation of actives in microparticles whose features and functionalities can be well controlled These microparticles have great potential in a wide range of bio-related applications including drug delivery, cell-laden matrices, biosensors and even as artificial cells In this review, we briefly summarize the materials, fabrication methods, and microparticle structures produced with droplet microfluidics We also provide a comprehensive overview of their recent uses in biomedical applications Finally, we discuss the existing challenges and perspectives to promote the future development of these engineered microparticles

Journal ArticleDOI
TL;DR: In this paper, a series of heterostructured ZnIn2S4@NH2-MIL-125(Ti) nanocomposites were fabricated via a facile solvothermal method.
Abstract: Metal-organic frameworks (MOFs) have been attracted considerable attention in the field of energy generation and environmental remediation. However, the functionalization and diversification of MOFs are still challenging and imperative for the development of highly active MOF-based materials. In this article, a series of heterostructured ZnIn2S4@NH2-MIL-125(Ti) nanocomposites with different NH2-MIL-125(Ti) contents were fabricated via a facile solvothermal method. The photocatalytic activities of the obtained samples were evaluated by the photocatalytic H2 production under visible-light illumination (λ > 420 nm). The results showed that the ZnIn2S4 nanosheets were highly dispersed on the surface of NH2-MIL-125(Ti). The ZnIn2S4@NH2-MIL-125(Ti) photocatalysts displayed higher photocatalytic activity than the pristine components for H2 production. The optimal content of NH2-MIL-125(Ti) was about 40 wt% and the corresponding photocatalytic H2 production rate was 2204.2 μmol·h−1·g−1 (with an apparent quantum efficiency of 4.3% at 420 nm), which was 6.5 times higher than that of pure ZnIn2S4. The enhanced photocatalytic activity of ZnIn2S4@NH2-MIL-125(Ti) composites should be attributed to the well-matched band structure and intimate contact interfaces between ZnIn2S4 and NH2-MIL-125(Ti), which led to the effective transfer and separation of the photogenerated charge carriers. Moreover, the ZnIn2S4@NH2-MIL-125(Ti) nanocomposites showed excellent stability during the photocatalytic reactions under visible light. Therefore, these kinds of MOF-based composites have great potentiality in energy conversion fields.

Journal ArticleDOI
Kevin Van der Jeught1, Han-Chen Xu1, Yujing Li1, Xiongbin Lu1, Guang Ji1 
TL;DR: In this article, the αamanitin antibody-drug conjugate targeting hemizygous p53 loss was evaluated and new developments with clinical potentials to augment responses to checkpoint inhibitors.
Abstract: Colorectal cancer (CRC) is often diagnosed at an advanced stage when tumor cell dissemination has taken place. Chemo- and targeted therapies provide only a limited increase of overall survival for these patients. The major reason for clinical outcome finds its origin in therapy resistance. Escape mechanisms to both chemo- and targeted therapy remain the main culprits. Here, we evaluate major resistant mechanisms and elaborate on potential new therapies. Amongst promising therapies is α-amanitin antibody-drug conjugate targeting hemizygous p53 loss. It becomes clear that a dynamic interaction with the tumor microenvironment exists and that this dictates therapeutic outcome. In addition, CRC displays a limited response to checkpoint inhibitors, as only a minority of patients with microsatellite instable high tumors is susceptible. In this review, we highlight new developments with clinical potentials to augment responses to checkpoint inhibitors.

Journal ArticleDOI
Jun Shi1, Xiao Zheng1, Yan Li2, Qi Zhang1, Shihui Ying1 
TL;DR: Experimental results indicate that MM-SDPN is superior over the state-of-the-art multimodal feature-learning-based algorithms for AD diagnosis.
Abstract: The accurate diagnosis of Alzheimer's disease (AD) and its early stage, i.e., mild cognitive impairment, is essential for timely treatment and possible delay of AD. Fusion of multimodal neuroimaging data, such as magnetic resonance imaging (MRI) and positron emission tomography (PET), has shown its effectiveness for AD diagnosis. The deep polynomial networks (DPN) is a recently proposed deep learning algorithm, which performs well on both large-scale and small-size datasets. In this study, a multimodal stacked DPN (MM-SDPN) algorithm, which MM-SDPN consists of two-stage SDPNs, is proposed to fuse and learn feature representation from multimodal neuroimaging data for AD diagnosis. Specifically speaking, two SDPNs are first used to learn high-level features of MRI and PET, respectively, which are then fed to another SDPN to fuse multimodal neuroimaging information. The proposed MM-SDPN algorithm is applied to the ADNI dataset to conduct both binary classification and multiclass classification tasks. Experimental results indicate that MM-SDPN is superior over the state-of-the-art multimodal feature-learning-based algorithms for AD diagnosis.

Journal ArticleDOI
TL;DR: In this article, a facile approach of polymerizing the ultrathin graphene oxide on the surface of the MIL-88A(Fe) to form MIL88A (Fe)/grapheme oxide composite for enhancing the photocatalytic efficiency of organic molecules degradation was reported.
Abstract: It is very important to design excellent heterojunction structure for the improvement of the photocatalytic performance. In this study, we report a facile approach of polymerizing the ultrathin graphene oxide on the surface of the MIL-88A(Fe) to form MIL-88A(Fe)/grapheme oxide composite for enhancing the photocatalytic efficiency of organic molecules degradation. The optical grapheme oxide doping content in MIL-88A(Fe)/grapheme oxide hybrid is determined to be 9.0 wt%,which increases the surface area of the MOFs from 15.9 m 2 g −1 to 408.9 m 2 g −1 due to the emerging micropores, and the corresponding photocatalytic rate for RhB is 8.4 times higher than that of pure MIL-88A(Fe). Meanwhile, DMF-free MOF-based heterostructure could avoid secondary contamination in the photocatalytic application process, and the degree of RhB removal is maintained at about 100% after the five cycles of the reaction. Integrating the related electrochemical analysis and the active species trapping experiments, the decisive factors for the improved photocatalytic efficiency of MIL-88A(Fe)/grapheme oxide may be the unique structural advantages of ultrathin grapheme oxide sheets, compact and uniform interface contact, more adsorption sites and more reaction sites. This work provides a novel sight for preparing high-efficient and environment-stable photocatalysts by designing the surface heterojunction structure.

Journal ArticleDOI
TL;DR: Experiments and density functional theory calculations reveal that the atomically isolated single Co sites and the structural advantages of the unique 3D hierarchical porous architecture synergistically contribute to the high catalytic activity.
Abstract: Exploring efficient and cost-effective catalysts to replace precious metal catalysts, such as Pt, for electrocatalytic oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER) holds great promise for renewable energy technologies. Herein, we prepare a type of Co catalyst with single-atomic Co sites embedded in hierarchically ordered porous N-doped carbon (Co-SAS/HOPNC) through a facile dual-template cooperative pyrolysis approach. The desirable combination of highly dispersed isolated atomic Co-N4 active sites, large surface area, high porosity, and good conductivity gives rise to an excellent catalytic performance. The catalyst exhibits outstanding performance for ORR in alkaline medium with a half-wave potential (E1/2) of 0.892 V, which is 53 mV more positive than that of Pt/C, as well as a high tolerance of methanol and great stability. The catalyst also shows a remarkable catalytic performance for HER with distinctly high turnover frequencies of 0.41 and 3.8 s−1 at an overpotential of 100 and 200 mV, respectively, together with a long-term durability in acidic condition. Experiments and density functional theory (DFT) calculations reveal that the atomically isolated single Co sites and the structural advantages of the unique 3D hierarchical porous architecture synergistically contribute to the high catalytic activity.

Journal ArticleDOI
TL;DR: In this paper, the physicochemical parameters, structural and electrochemical properties of g-C3N4/UiO-66 nanohybrids (CNUO-x) were investigated.

Journal ArticleDOI
TL;DR: In this article, the fundamental understanding of zinc-electrode reaction mechanisms, technical challenges, mitigation strategies, and perspectives are presented and analyzed for facilitating further research and development of rechargeable zinc-air battery.
Abstract: As a promising energy storage device, the rechargeable zinc–air battery (RZAB) has attracted increasing attention because of its high energy density, cost-effectiveness, and high safety, and the rich abundance of zinc, as well as its environmental benignity. However, the widespread application of RZABs still faces considerable challenges derived from zinc-electrodes, electrolytes, and air-electrodes. In this paper, specific attention is given to RZAB zinc-electrode materials and fabrication with focus on the fundamental understanding of zinc-electrode reaction mechanisms, technical challenges, mitigation strategies, and perspectives. Particularly, the approaches to overcome the challenges are also presented and analyzed for facilitating further research and development of RZABs.

Journal ArticleDOI
TL;DR: Xun Cao et al. as mentioned in this paper reviewed the phase-transition mechanism and modulation of vanadium dioxide (VO2) materials and provided a representative understanding on the phase transition mechanism, such as the lattice distortion and electron correlations.
Abstract: Metal-to-insulator transition (MIT) behaviors accompanied by a rapid reversible phase transition in vanadium dioxide (VO2) have gained substantial attention for investigations into various potential applications and obtaining good materials to study strongly correlated electronic behaviors in transition metal oxides (TMOs). Although its phase-transition mechanism is still controversial, during the past few decades, people have made great efforts in understanding the MIT mechanism, which could also benefit the investigation of MIT modulation. This review summarizes the recent progress in the phase-transition mechanism and modulation of VO2 materials. A representative understanding on the phase-transition mechanism, such as the lattice distortion and electron correlations, are discussed. Based on the research of the phase-transition mechanism, modulation methods, such as element doping, electric field (current and gating), and tensile/compression strain, as well as employing lasers, are summarized for comparison. Finally, discussions on future trends and perspectives are also provided. This review gives a comprehensive understanding of the mechanism of MIT behaviors and the phase-transition modulations. Smart coatings that alter their electrical properties on demand can be created from shape-shifting vanadium dioxide (VO2) crystals. Xun Cao from Shanghai Institute of Ceramics, Chinese Academy of Sciences in Shanghai and co-workers review efforts to understand the mechanisms that enable VO2 to rapidly switch between two crystal states — one with metallic conductivity, the other insulating—at near-room temperature conditions. Theoretical calculations and nanoscale experiments reveal that VO2 transitions are triggered by a combination of interactions between electrons and atoms in the crystal lattice, and through forces that cause electrons to avoid each other. Several innovative methods of manipulating the VO2 switching temperature have emerged including foreign element additions, laser irradiation, and controlled substrate bending. The sensitivity of VO2 transitions to mechanical stress has inspired proposals for ultrafast response breath sensors and artificial skin. In this article, we review the prototypical phase-transition material-VO2, which undergoes structure and conductivity changes simultaneously. The recent progresses in the transition mechanism are also discussed. Besides, this work gives a comprehensive understanding of the phase-transition modulations, such as element doping, electric field (current and gating) and tensile/compression strain, as well as employing laser.

Journal ArticleDOI
TL;DR: An adaptive event- triggering LFC scheme is presented, where the event-triggering threshold can be dynamically adjusted to save more limited network resources, while preserving the desired control performance.
Abstract: Load frequency control (LFC) is a very important method to keep the power systems stable and secure. However, due to the introduction of communication networks in multi-area power systems, the traditional LFC method is not effective again. This motivates us to investigate an adaptive event-triggering ${H}_{\infty }$ LFC scheme for multi-area power systems. Compared with the existing time-invariant event-triggering communication scheme, an adaptive event-triggering communication scheme is presented, where the event-triggering threshold can be dynamically adjusted to save more limited network resources, while preserving the desired control performance. Compared with the existing emulation-based method, where the controller must be known a priori , the stability and stabilization criteria derived in this work can provide a tradeoff to balance the required communication resources and the desired control performance. The effectiveness of the proposed method is verified by two numerical examples.


Journal ArticleDOI
TL;DR: The information presented here will help pharmacologists explore the relevance of CES to human diseases or to assign the contribution of certain CES in xenobiotic metabolism, and facilitate medicinal chemistry efforts to design prodrugs activated by a given CES isoform, or to develop potent and selective modulators of CES for potential biomedical applications.

Journal ArticleDOI
TL;DR: In this paper, a review of recent progress of lithium-ion batteries is reviewed with a focus on positive electrode materials, negative electrode material, separators and electrolytes in terms of energy density, power density, life-cycle and safety.
Abstract: Lithium-ion batteries (LIBs) possess several advantages over other types of viable practical batteries, including higher operating voltages, higher energy densities, longer cycle lives, lower rates of self-discharge and less environmental pollution Therefore, LIBs have been widely and successfully applied in portable electronic devices and industrial fields However, the rapidly increasing demands of new energy vehicles have also quickly increased the performance requirements of LIBs, including the need for higher power densities, greater capacity densities and better safety As battery designs gradually standardize, improvements in LIB performances mainly depend on the technical progress in key electrode materials such as positive and negative electrode materials, separators and electrolytes For LIB performances to meet the rising requirements, many studies on the structural characteristics and morphology modifications of electrode/separator/electrolyte materials with different synthesis methods have been conducted In this review, recent progress of LIBs is reviewed with a focus on positive electrode materials, negative electrode materials, separators and electrolytes in terms of energy density, power density, life-cycle and safety To accelerate the research and development and to overcome the challenges of LIB technology and application, several possible research directions are also discussed to further improve LIB performances

Journal ArticleDOI
TL;DR: In this article, the origin and evolution of Li dendrite growth through SSEs have been studied and compared by using Li6.1Ga0.3La3Zr2O12 (LLZO) and NASICON-type Li2O-Al2O3-P2O5-TiO2-GeO2 (LATP) pellets as the separators.
Abstract: Lithium (Li) metal anodes have regained intensive interest in recent years due to the ever-increasing demand for next-generation high energy battery technologies. Li metal, unfortunately, suffers from poor cycling stability and low efficiency as well as from the formation of dangerous Li dendrites, raising safety concerns. Utilizing solid-state electrolytes (SSEs) to prevent Li dendrite growth provides a promising approach to tackle the challenge. However, recent studies indicate that Li dendrites easily form at high current densities, which calls for full investigation of the fundamental mechanisms of Li dendrite formation within SSEs. Herein, the origin and evolution of Li dendrite growth through SSEs have been studied and compared by using Li6.1Ga0.3La3Zr2O12 (LLZO) and NASICON-type Li2O–Al2O3–P2O5–TiO2–GeO2 (LATP) pellets as the separators. We discover that a solid electrolyte interphase (SEI)-like interfacial layer between Li and SSE plays a critical role in alleviating the growth of dendritic Li, providing new insights into the interface between SSE and Li metal to enable future all solid-state batteries.

Journal ArticleDOI
TL;DR: This paper summarizes the research advances in the utilization of lignin resources (mainly in the last three years), with a particular emphasis on two major approaches of lIGNin utilization: catalytic degradation into aromatics and thermochemical treatment for carbon material production.