Showing papers by "Shanghai University published in 2019"
TL;DR: Comprehensive results show that the proposed CE-Net method outperforms the original U- net method and other state-of-the-art methods for optic disc segmentation, vessel detection, lung segmentation , cell contour segmentation and retinal optical coherence tomography layer segmentation.
Abstract: Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation, blood vessel detection, lung segmentation, cell segmentation, and so on. Previously, U-net based approaches have been proposed. However, the consecutive pooling and strided convolutional operations led to the loss of some spatial information. In this paper, we propose a context encoder network (CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation. CE-Net mainly contains three major components: a feature encoder module, a context extractor, and a feature decoder module. We use the pretrained ResNet block as the fixed feature extractor. The context extractor module is formed by a newly proposed dense atrous convolution block and a residual multi-kernel pooling block. We applied the proposed CE-Net to different 2D medical image segmentation tasks. Comprehensive results show that the proposed method outperforms the original U-Net method and other state-of-the-art methods for optic disc segmentation, vessel detection, lung segmentation, cell contour segmentation, and retinal optical coherence tomography layer segmentation.
906 citations
TL;DR: This review summarizes the latest SCR reaction mechanisms and emerging poison-resistant mechanisms in the beginning and subsequently gives a comprehensive overview of newly developed SCR catalysts, including metal oxide catalysts ranging from VOx, MnOx, CeO2, and Fe2O3 to CuO based catalysts.
Abstract: Selective catalytic reduction with NH3 (NH3-SCR) is the most efficient technology to reduce the emission of nitrogen oxides (NOx) from coal-fired industries, diesel engines, etc. Although V2O5-WO3(MoO3)/TiO2 and CHA structured zeolite catalysts have been utilized in commercial applications, the increasing requirements for broad working temperature window, strong SO2/alkali/heavy metal-resistance, and high hydrothermal stability have stimulated the development of new-type NH3-SCR catalysts. This review summarizes the latest SCR reaction mechanisms and emerging poison-resistant mechanisms in the beginning and subsequently gives a comprehensive overview of newly developed SCR catalysts, including metal oxide catalysts ranging from VOx, MnOx, CeO2, and Fe2O3 to CuO based catalysts; acidic compound catalysts containing vanadate, phosphate and sulfate catalysts; ion exchanged zeolite catalysts such as Fe, Cu, Mn, etc. exchanged zeolite catalysts; monolith catalysts including extruded, washcoated, and metal-mesh/foam-based monolith catalysts. The challenges and opportunities for each type of catalysts are proposed while the effective strategies are summarized for enhancing the acidity/redox circle and poison-resistance through modification, creating novel nanostructures, exposing specific crystalline planes, constructing protective/sacrificial sites, etc. Some suggestions are given about future research directions that efforts should be made in. Hopefully, this review can bridge the gap between newly developed catalysts and practical requirements to realize their commercial applications in the near future.
800 citations
TL;DR: Li et al. as mentioned in this paper proposed a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation, which mainly contains three major components: a feature encoder module, a context extractor and a feature decoder module.
Abstract: Medical image segmentation is an important step in medical image analysis. With the rapid development of convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation, blood vessel detection, lung segmentation, cell segmentation, etc. Previously, U-net based approaches have been proposed. However, the consecutive pooling and strided convolutional operations lead to the loss of some spatial information. In this paper, we propose a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation. CE-Net mainly contains three major components: a feature encoder module, a context extractor and a feature decoder module. We use pretrained ResNet block as the fixed feature extractor. The context extractor module is formed by a newly proposed dense atrous convolution (DAC) block and residual multi-kernel pooling (RMP) block. We applied the proposed CE-Net to different 2D medical image segmentation tasks. Comprehensive results show that the proposed method outperforms the original U-Net method and other state-of-the-art methods for optic disc segmentation, vessel detection, lung segmentation, cell contour segmentation and retinal optical coherence tomography layer segmentation.
788 citations
01 Apr 2019
TL;DR: Wu et al. as mentioned in this paper constructed a series of alloy-supported Ru1 using different PtCu alloys through sequential acid etching and electrochemical leaching, and found a volcano relation between OER activity and the lattice constant of the alloys.
Abstract: Single-atom precious metal catalysts hold the promise of perfect atom utilization, yet control of their activity and stability remains challenging. Here we show that engineering the electronic structure of atomically dispersed Ru1 on metal supports via compressive strain boosts the kinetically sluggish electrocatalytic oxygen evolution reaction (OER), and mitigates the degradation of Ru-based electrocatalysts in an acidic electrolyte. We construct a series of alloy-supported Ru1 using different PtCu alloys through sequential acid etching and electrochemical leaching, and find a volcano relation between OER activity and the lattice constant of the PtCu alloys. Our best catalyst, Ru1–Pt3Cu, delivers 90 mV lower overpotential to reach a current density of 10 mA cm−2, and an order of magnitude longer lifetime over that of commercial RuO2. Density functional theory investigations reveal that the compressive strain of the Ptskin shell engineers the electronic structure of the Ru1, allowing optimized binding of oxygen species and better resistance to over-oxidation and dissolution. While Ru-based electrocatalysts are among the most active for acidic water oxidation, they suffer from severe deactivation. Now, Yuen Wu, Wei-Xue Li and co-workers report a core–shell Ru1–Pt3Cu catalyst with surface-dispersed Ru atoms for a highly active and stable oxygen evolution reaction in acid electrolyte.
616 citations
Shandong University1, Stanford University2, Osaka City University3, Sun Yat-sen University4, Xi'an Jiaotong University5, Kyushu University6, Shanghai University7, Harbin Medical University8, Saga Group9, Fu Jen Catholic University10, Chung Shan Medical University11, Hanyang University12, The Chinese University of Hong Kong13, Veterans Health Administration14
TL;DR: NAFLD prevalence in Asia is increasing and is associated with poor outcomes including hepatocellular carcinoma and death, especially in high-risk groups, such as older obese men, and targeted public health strategies must be developed in Asia.
527 citations
TL;DR: Li et al. as discussed by the authors examined the internal mechanisms and contingent conditions that link green technology innovation to a firm's financial performance and found that green product innovation mediates the relationship between green process innovation and the firm's performance.
462 citations
TL;DR: This work uses lamellar microstructure inherited from casting, rolling, and annealing to produce an ultrafine duplex eutectic high entropy alloy with outstanding properties and widens the design toolbox for high-performance materials based upon EHEAs.
Abstract: Realizing improved strength–ductility synergy in eutectic alloys acting as in situ composite materials remains a challenge in conventional eutectic systems, which is why eutectic high-entropy alloys (EHEAs), a newly-emerging multi-principal-element eutectic category, may offer wider in situ composite possibilities. Here, we use an AlCoCrFeNi2.1 EHEA to engineer an ultrafine-grained duplex microstructure that deliberately inherits its composite lamellar nature by tailored thermo-mechanical processing to achieve property combinations which are not accessible to previously-reported reinforcement methodologies. The as-prepared samples exhibit hierarchically-structural heterogeneity due to phase decomposition, and the improved mechanical response during deformation is attributed to both a two-hierarchical constraint effect and a self-generated microcrack-arresting mechanism. This work provides a pathway for strengthening eutectic alloys and widens the design toolbox for high-performance materials based upon EHEAs. Producing in situ composite materials with superior strength and ductility has long been a challenge. Here, the authors use lamellar microstructure inherited from casting, rolling, and annealing to produce an ultrafine duplex eutectic high entropy alloy with outstanding properties.
451 citations
TL;DR: Single boron atoms supported on graphene and substituted into h-MoS2 are identified as the most promising NRR catalysts, offering excellent energy efficiency and selectivity against hydrogen evolution reaction.
Abstract: Boron has been explored as p-block catalysts for nitrogen reduction reaction (NRR) by density functional theory. Unlike transition metals, on which the active centers need empty d orbitals to accept the lone-pair electrons of the nitrogen molecule, the sp3 hybrid orbital of the boron atom can form B-to-N π-back bonding. This results in the population of the N–N π* orbital and the concomitant decrease of the N–N bond order. We demonstrate that the catalytic activity of boron is highly correlated with the degree of charge transfer between the boron atom and the substrate. Among the 21 concept-catalysts, single boron atoms supported on graphene and substituted into h-MoS2 are identified as the most promising NRR catalysts, offering excellent energy efficiency and selectivity against hydrogen evolution reaction.
444 citations
TL;DR: In this paper, a competitive complexation strategy has been developed to construct a novel electrocatalyst with Zn-Co atomic pairs coordinated on N doped carbon support (Zn/CoN-C).
Abstract: A competitive complexation strategy has been developed to construct a novel electrocatalyst with Zn-Co atomic pairs coordinated on N doped carbon support (Zn/CoN-C). Such architecture offers enhanced binding ability of O2 , significantly elongates the O-O length (from 1.23 A to 1.42 A), and thus facilitates the cleavage of O-O bond, showing a theoretical overpotential of 0.335 V during ORR process. As a result, the Zn/CoN-C catalyst exhibits outstanding ORR performance in both alkaline and acid conditions with a half-wave potential of 0.861 and 0.796 V respectively. The in situ XANES analysis suggests Co as the active center during the ORR. The assembled zinc-air battery with Zn/CoN-C as cathode catalyst presents a maximum power density of 230 mW cm-2 along with excellent operation durability. The excellent catalytic activity in acid is also verified by H2 /O2 fuel cell tests (peak power density of 705 mW cm-2 ).
414 citations
TL;DR: In this article, a small amount of diethyl ether (Et2O) was used as an electrolyte additive to improve the performance of Zn-MnO2 batteries.
388 citations
TL;DR: In this paper, the authors review the recent advances on the understanding of structural heterogeneities in metallic supercooled liquids and the influence of the structural heterogeneity on the overall mechanical properties of the corresponding amorphous alloys.
TL;DR: Theabrownin alters the gut microbiota in mice and humans, predominantly suppressing microbes associated with bile-salt hydrolase (BSH) activity, and it is suggested that decreased intestinal BSH microbes and/or decreased FXR-FGF15 signaling may be potential anti- hypercholesterolemia and anti-hyperlipidemia therapies.
Abstract: Pu-erh tea displays cholesterol-lowering properties, but the underlying mechanism has not been elucidated. Theabrownin is one of the most active and abundant pigments in Pu-erh tea. Here, we show that theabrownin alters the gut microbiota in mice and humans, predominantly suppressing microbes associated with bile-salt hydrolase (BSH) activity. Theabrownin increases the levels of ileal conjugated bile acids (BAs) which, in turn, inhibit the intestinal FXR-FGF15 signaling pathway, resulting in increased hepatic production and fecal excretion of BAs, reduced hepatic cholesterol, and decreased lipogenesis. The inhibition of intestinal FXR-FGF15 signaling is accompanied by increased gene expression of enzymes in the alternative BA synthetic pathway, production of hepatic chenodeoxycholic acid, activation of hepatic FXR, and hepatic lipolysis. Our results shed light into the mechanisms behind the cholesterol- and lipid-lowering effects of Pu-erh tea, and suggest that decreased intestinal BSH microbes and/or decreased FXR-FGF15 signaling may be potential anti-hypercholesterolemia and anti-hyperlipidemia therapies. Pu-erh tea displays cholesterol-lowering properties. Here, Huang et al. show that this is mostly due to the action of a pigment in Pu-erh tea that induces changes in certain gut microbiota and bile acid levels, thus modulating the gut-liver metabolic axis.
TL;DR: Wang et al. realize smooth and pinhole-free, small-grained inorganic perovskite films with improved photoluminescence quantum yield by introducing trifluoroacetate anions to effectively passivate surface defects and control the crystal growth.
Abstract: Quantum efficiencies of organic-inorganic hybrid lead halide perovskite light-emitting devices (LEDs) have increased significantly, but poor device operational stability still impedes their further development and application. All-inorganic perovskites show better stability than the hybrid counterparts, but the performance of their respective films used in LEDs is limited by the large perovskite grain sizes, which lowers the radiative recombination probability and results in grain boundary related trap states. We realize smooth and pinhole-free, small-grained inorganic perovskite films with improved photoluminescence quantum yield by introducing trifluoroacetate anions to effectively passivate surface defects and control the crystal growth. As a result, efficient green LEDs based on inorganic perovskite films achieve a high current efficiency of 32.0 cd A−1 corresponding to an external quantum efficiency of 10.5%. More importantly, our all-inorganic perovskite LEDs demonstrate a record operational lifetime, with a half-lifetime of over 250 h at an initial luminance of 100 cd m−2. All-inorganic cesium lead bromide perovskite based light-emitting diodes show improved operational stability but the film quality limits their performance. Here Wang et al. use trifluoroacetate anions to passivate defects and achieve excellent device performance and stability.
TL;DR: In this review, the biomimetic platform of erythrocyte membrane-coated nano-cores is described with regard to various aspects, with particular focus placed on the coating mechanism, preparation methods, verification methods, and the latest anti-tumor applications.
TL;DR: In this article, the authors present an overview on the development of metasurfaces, including both homogeneous and inhomogeneous ones, focusing particularly on their working principles, the fascinating wave-manipulation effects achieved both statically and dynamically, and the representative applications so far realized.
Abstract: Metasurfaces are ultrathin metamaterials consisting of planar electromagnetic (EM) microstructures (e.g., meta-atoms) with pre-determined EM responses arranged in specific sequences. Based on careful structural designs on both meta-atoms and global sequences, one can realize homogenous and inhomogeneous metasurfaces that can possess exceptional capabilities to manipulate EM waves, serving as ideal candidates to realize ultracompact and highly efficient EM devices for next-generation integration-optics applications. In this paper, we present an overview on the development of metasurfaces, including both homogeneous and inhomogeneous ones, focusing particularly on their working principles, the fascinating wave-manipulation effects achieved both statically and dynamically, and the representative applications so far realized. Finally, we also present our own perspectives on possible future directions of this fast-developing research field in the conclusion.
TL;DR: This review highlights various hypoxia-targeted and activated design strategies for the formulation of drugs or prodrugs and their mechanism of action for tumour diagnosis and treatment.
Abstract: Hypoxia is a state of low oxygen tension found in numerous solid tumours. It is typically associated with abnormal vasculature, which results in a reduced supply of oxygen and nutrients, as well as impaired delivery of drugs. The hypoxic nature of tumours often leads to the development of localized heterogeneous environments characterized by variable oxygen concentrations, relatively low pH, and increased levels of reactive oxygen species (ROS). The hypoxic heterogeneity promotes tumour invasiveness, metastasis, angiogenesis, and an increase in multidrug-resistant proteins. These factors decrease the therapeutic efficacy of anticancer drugs and can provide a barrier to advancing drug leads beyond the early stages of preclinical development. This review highlights various hypoxia-targeted and activated design strategies for the formulation of drugs or prodrugs and their mechanism of action for tumour diagnosis and treatment.
TL;DR: This paper makes the first attempt to introduce a dynamic event-triggering strategy into the design of synchronization controllers for complex dynamical networks for the efficiency of energy utilization and verification of the effectiveness of the proposedynamic event-triggered synchronization control scheme.
Abstract: This paper is concerned with the synchronization control problem for a class of discrete time-delay complex dynamical networks under a dynamic event-triggered mechanism. For the efficiency of energy utilization, we make the first attempt to introduce a dynamic event-triggering strategy into the design of synchronization controllers for complex dynamical networks. A new discrete-time version of the dynamic event-triggering mechanism is proposed in terms of the absolute errors between control input updates. By constructing an appropriate Lyapunov functional, the dynamics of each network node combined with the introduced event-triggering mechanism are first analyzed, and a sufficient condition is then provided under which the synchronization error dynamics is exponentially ultimately bounded. Subsequently, a set of the desired synchronization controllers is designed by solving a matrix inequality. Finally, a simulation example is provided to verify the effectiveness of the proposed dynamic event-triggered synchronization control scheme.
01 Jun 2019
TL;DR: A cross-modal self-attention (CMSA) module that effectively captures the long-range dependencies between linguistic and visual features and a gated multi-level fusion module to selectively integrateSelf-attentive cross- modal features corresponding to different levels in the image.
Abstract: We consider the problem of referring image segmentation. Given an input image and a natural language expression, the goal is to segment the object referred by the language expression in the image. Existing works in this area treat the language expression and the input image separately in their representations. They do not sufficiently capture long-range correlations between these two modalities. In this paper, we propose a cross-modal self-attention (CMSA) module that effectively captures the long-range dependencies between linguistic and visual features. Our model can adaptively focus on informative words in the referring expression and important regions in the input image. In addition, we propose a gated multi-level fusion module to selectively integrate self-attentive cross-modal features corresponding to different levels in the image. This module controls the information flow of features at different levels. We validate the proposed approach on four evaluation datasets. Our proposed approach consistently outperforms existing state-of-the-art methods.
TL;DR: In this paper, the authors comprehensively discuss the recent developments in advanced single-atom and dual-atom metal catalysts for the oxygen reduction reaction (ORR), including synthesis and characterization, reaction mechanisms and energy applications such as in fuel cells and metal-air batteries.
Abstract: In recent years, atomically dispersed metal catalysts (ADMCs) with well-defined structures have attracted great interest from researchers for electrocatalytic applications due to their maximum atom utilization efficiency (100%), distinct active sites and high catalytic activity, stability and selectivity. Based on this, this review will comprehensively discuss the recent developments in advanced single-atom and dual-atom ADMCs for the oxygen reduction reaction (ORR), including synthesis and characterization, reaction mechanisms and energy applications such as in fuel cells and metal–air batteries. In addition, challenges will be summarized and analyzed, including the rational design and fabrication of ADMCs and a deeper understanding of their geometric configuration, electronic structure and reaction dynamics towards the ORR. Furthermore, to facilitate further development, future research directions are proposed to overcome associated challenges, such as (1) the exploration of new/advanced materials including metal precursors and supporting substrates for the fabrication of ADMCs; (2) the optimization of rational design and synthesis techniques for single- and dual-atom catalysts to significantly enhance catalytic ORR activity and stability based on modern characterization techniques; (3) a deeper understanding of ADMC structures, reactive active sites, interactions between metal atoms and support surfaces and corresponding electrocatalytic ORR mechanisms at the atomic level using a combination of density functional theory (DFT) calculations and advanced experimental techniques; (4) the optimization of ADMC-based catalyst layers and membrane electrode assemblies to achieve high performance fuel cells and metal–air batteries using advanced electrochemical testing strategies.
TL;DR: In this paper, the authors present a heterogeneous-structures-architecting strategy, in which they design bulk high-entropy alloys with the largelyenhanced strength-ductility trade-off, possessing a yield strength of 711 MPa, a tensile strength of 928 MPa and a uniform elongation of 30.3%.
TL;DR: In this paper, a permissioned energy blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts, and a reputation-based delegated Byzantine fault tolerance consensus algorithm is proposed to efficiently achieve the consensus in the permissioned blockchain.
Abstract: The smart community (SC), as an important part of the Internet of Energy (IoE), can facilitate integration of distributed renewable energy sources and electric vehicles (EVs) in the smart grid. However, due to the potential security and privacy issues caused by untrusted and opaque energy markets, it becomes a great challenge to optimally schedule the charging behaviors of EVs with distinct energy consumption preferences in SC. In this paper, we propose a contract-based energy blockchain for secure EV charging in SC. First, a permissioned energy blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts. Second, a reputation-based delegated Byzantine fault tolerance consensus algorithm is proposed to efficiently achieve the consensus in the permissioned blockchain. Third, based on the contract theory, the optimal contracts are analyzed and designed to satisfy EVs’ individual needs for energy sources while maximizing the operator’s utility. Furthermore, a novel energy allocation mechanism is proposed to allocate the limited renewable energy for EVs. Finally, extensive numerical results are carried out to evaluate and demonstrate the effectiveness and efficiency of the proposed scheme through comparison with other conventional schemes.
TL;DR: Both experimental results and theoretical calculations demonstrate that defect-rich TiO2 provides more chemical adhesions to SnS2 and discharge products, compared to defect-poorTiO2, and then effectively stabilizes the electrode structure, and the composite exhibits an unprecedented cycle stability.
Abstract: Nanostructured-alloy-type anodes have received great interest for high-performance lithium-ion batteries (LIBs). However, these anodes experience huge volume fluctuations during repeated lithiation/delithiation and are easily pulverized and subsequently form aggregates. Herein, an efficient method to stabilize alloy-type anodes by creating defects on the surface of the metal oxide support is proposed. As a demonstration, PPy-encapsulated SnS2 nanosheets supported on defect-rich TiO2 nanotubes were produced and investigated as an anode material for LIBs. Both experimental results and theoretical calculations demonstrate that defect-rich TiO2 provides more chemical adhesions to SnS2 and discharge products, compared to defect-poor TiO2 , and then effectively stabilizes the electrode structure. As a result, the composite exhibits an unprecedented cycle stability. This work paves the way to designing durable and active nanostructured-alloy-type anodes on oxide supports.
TL;DR: In this paper, a Schiff base epoxy thermoset combining excellent recyclability and high performance was facilely prepared from a synthesized formyl group-containing vanillin-based monoepoxide and a diamine via in situ formation of the Schiff base structure and epoxy network.
TL;DR: In this paper, a porous nitrogen-doped carbon matrix catalyst with 3.5 wt % single Fe atoms (Fe SAs/N-C) was proposed for oxygen reduction reaction (ORR).
Abstract: It is highly desired but remains a great challenge to develop nonprecious metal single-atom catalysts to supersede the Pt-based material for oxygen reduction reaction (ORR). Herein, we report a porous nitrogen-doped carbon matrix catalyst with 3.5 wt % single Fe atoms (Fe SAs/N–C) through a versatile molecules-confined pyrolysis strategy. In 0.1 M KOH condition, the Fe SAs/N–C catalyst possesses a half-wave potential of 0.91 V vs RHE. In a more challenging acidic solution, Fe SAs/N–C catalyst also offers good ORR activity, comparable with the commercial Pt/C. Impressively, Fe SAs/N–C shows extremely high stability both in alkaline and acidic media. In addition, this Fe SAs/N–C-derived Zn–air battery and proton exchange membrane fuel cells (PEMFCs) exhibit high performance. This work opens an avenue for designing and preparing single-atom catalysts.
TL;DR: This work retrieved all new lncRNA–target relationships from papers published from 1 August 2014 to 30 April 2018 and RNA-seq datasets before and after knockdown or overexpression of a specific lnc RNA.
Abstract: Long non-coding RNAs (lncRNAs) play crucial roles in regulating gene expression, and a growing number of researchers have focused on the identification of target genes of lncRNAs. However, no online repository is available to collect the information on target genes regulated by lncRNAs. To make it convenient for researchers to know what genes are regulated by a lncRNA of interest, we developed a database named lncRNA2Target to provide a comprehensive resource of lncRNA target genes in 2015. To update the database this year, we retrieved all new lncRNA-target relationships from papers published from 1 August 2014 to 30 April 2018 and RNA-seq datasets before and after knockdown or overexpression of a specific lncRNA. LncRNA2Target database v2.0 provides a web interface through which its users can search for the targets of a particular lncRNA or for the lncRNAs that target a particular gene, and is freely accessible at http://123.59.132.21/lncrna2target.
TL;DR: It is shown that coupling titanium dioxide and other anode materials with diglyme does enable higher efficiency and reversible capacity than those for the combination involving ester electrolytes.
Abstract: Ether based electrolytes have surfaced as alternatives to conventional carbonates allowing for enhanced electrochemical performance of sodium-ion batteries; however, the primary source of the improvement remains poorly understood. Here we show that coupling titanium dioxide and other anode materials with diglyme does enable higher efficiency and reversible capacity than those for the combination involving ester electrolytes. Importantly, the electrolyte dependent performance is revealed to be the result of the different structural evolution induced by a varied sodiation depth. A suit of characterizations show that the energy barrier to charge transfer at the interface between electrolyte and electrode is the factor that dominates the interfacial electrochemical characteristics and therefore the energy storage properties. Our study proposes a reliable parameter to assess the intricate sodiation dynamics in sodium-ion batteries and could guide the design of aprotic electrolytes for next generation rechargeable batteries.
TL;DR: In this article, the PdAu/SnO2 sensor can not only effectively detect acetone at 250 °C with response of 6.6 to 2 ppm acetone, but also detect formaldehyde at 110 Ã 0 Ã Ã c with response 4.1-2 Ã 1 Ã 2 Ã ) formaldehyde, and the corresponding detection limit is as low as 45 Ã pb and 30 Ã n Ã
Abstract: In this study, SnO2 nanosheets (NSs) was firstly prepared by the hydro-solvothermal treatment, and then decorated with Pd, Au and PdAu bimetallic nanoparticles (NPs) by an in situ reduction with ascorbic acid (AA). Their morphology, chemistry, and crystal structure were characterized at the nanoscale. It was found that SnO2 NSs were flower-like with thickness of 7–12 nm, and PdAu NPs with the size of 3–10 nm were dispersed uniformly on the surface of SnO2 NSs. Their gas sensing properties were carefully studied. The results demonstrated that the PdAu/SnO2 sensor can not only effectively detect acetone at 250 °C with response of 6.6 to 2 ppm acetone, but also detect formaldehyde at 110 °C with response of 4.1–2 ppm formaldehyde, and the corresponding detection limit is as low as 45 ppb and 30 ppb, respectively. Moreover, the PdAu/SnO2 sensor exhibited excellent reusability, and reliability to the low concentration of acetone and good anti-interference to humidity and other biomarkers in human breath. Compared with that decorated with their parent metal (Pd or Au), the enhanced response of SnO2 NSs decorated with PdAu bimetallic NPs may be ascribed to the chemical sensitization of Au, the electronic sensitization of Pd and the synergistic effect of PdAu bimetallic NPs. The PdAu/SnO2 sensor has a great potential application in detecting formaldehyde and diabetes diagnosis.
TL;DR: In this article, a review on the enhancement method of kinetics in Mg-based hydrogen storage materials and introduces the new kinetic models is presented, which is an efficient way to reveal the hydriding/dehydriding (H/D) kinetic mechanism.
TL;DR: The authors apply the inverse design approach to identify and experimentally realize TaFeSb-based half Heuslers with high thermoelectric performance and demonstrate that the TaFe Sb- based half-Heuslers are highly promising for thermoelectedric power generation.
Abstract: Discovery of thermoelectric materials has long been realized by the Edisonian trial and error approach. However, recent progress in theoretical calculations, including the ability to predict structures of unknown phases along with their thermodynamic stability and functional properties, has enabled the so-called inverse design approach. Compared to the traditional materials discovery, the inverse design approach has the potential to substantially reduce the experimental efforts needed to identify promising compounds with target functionalities. By adopting this approach, here we have discovered several unreported half-Heusler compounds. Among them, the p-type TaFeSb-based half-Heusler demonstrates a record high ZT of ~1.52 at 973 K. Additionally, an ultrahigh average ZT of ~0.93 between 300 and 973 K is achieved. Such an extraordinary thermoelectric performance is further verified by the heat-to-electricity conversion efficiency measurement and a high efficiency of ~11.4% is obtained. Our work demonstrates that the TaFeSb-based half-Heuslers are highly promising for thermoelectric power generation. The discovery of thermodynamically stable thermoelectric materials for power generation has relied on empirical methods that were not effective. Here, the authors apply the inverse design approach to identify and experimentally realize TaFeSb-based half Heuslers with high thermoelectric performance.
TL;DR: A simple one-step hydrothermal synthesis of SnS2/graphene/SnS2 (SnS 2/rGO/snS2) composite with ultrathin SnS 2 nanosheets covalently decorated on both sides of reduced graphene oxide sheets via C‒S bonds is reported, demonstrating that this composite with high rate capabilities and excellent cycle stability are the promising candidate for lithium/sodium storage.
Abstract: SnS2 materials have attracted broad attention in the field of electrochemical energy storage due to their layered structure with high specific capacity. However, the easy restacking property during charge/discharge cycling leads to electrode structure instability and a severe capacity decrease. In this paper, we report a simple one-step hydrothermal synthesis of SnS2/graphene/SnS2 (SnS2/rGO/SnS2) composite with ultrathin SnS2 nanosheets covalently decorated on both sides of reduced graphene oxide sheets via C-S bonds. Owing to the graphene sandwiched between two SnS2 sheets, the composite presents an enlarged interlayer spacing of ∼8.03 A for SnS2, which could facilitate the insertion/extraction of Li+/Na+ ions with rapid transport kinetics as well as inhibit the restacking of SnS2 nanosheets during the charge/discharge cycling. The density functional theory calculation reveals the most stable state of the moderate interlayer spacing for the sandwich-like composite. The diffusion coefficients of Li/Na ions from both molecular simulation and experimental observation also demonstrate that this state is the most suitable for fast ion transport. In addition, numerous ultratiny SnS2 nanoparticles anchored on the graphene sheets can generate dominant pseudocapacitive contribution to the composite especially at large current density, guaranteeing its excellent high-rate performance with 844 and 765 mAh g-1 for Li/Na-ion batteries even at 10 A g-1. No distinct morphology changes occur after 200 cycles, and the SnS2 nanoparticles still recover to a pristine phase without distinct agglomeration, demonstrating that this composite with high-rate capabilities and excellent cycle stability are promising candidates for lithium/sodium storage.