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Friction and wear are ubiquitous, from nano-electro-mechanical systems in biomedicine to large-scale integrated electric propulsion in aircraft carriers. Applications of nanomaterials as lubricating oil additives have achieved great advances, which are of great significance to control friction and wear. This review focuses on the applications of nanomaterials in lubricating oil and comprehensively compares their tribological characteristics as lubricating oil additives. Statistical analysis of tribology data is provided and discussed accordingly; moreover, the interaction between nanomaterials and sliding surface, lubricating oil, other additives, and synergistic lubrication in nanocomposites are systematically elaborated. Finally, suggestions for future research on nanomaterials as lubricating oil additives are proposed. Hence, this review will promote a better fundamental understanding of nanomaterials for lubricating oil application and help to achieve the superior design of nanoadditives with outstanding tribological performances.

Iridium (Ir)-based electrocatalysts are widely explored as benchmarks for acidic oxygen evolution reactions (OERs). However, further enhancing their catalytic activity remains challenging due to the difficulty in identifying active species and unfavorable architectures. In this work, we synthesized ultrathin Ir-IrO

Most ground-based remote sensing cloud classification methods focus on learning representation features for cloud images while ignoring the correlations among cloud images. Recently, graph convolutional network (GCN) is applied to provide the correlations for ground-based remote sensing cloud classification, in which the graph convolutional layer aggregates information from the connected nodes of graph in a weighted way. However, the weights assigned by GCN cannot reflect the importance of connected nodes precisely, which declines the discrimination of the aggregated features (AFs). To overcome the limitation, in this article, we propose the context graph attention network (CGAT) for ground-based remote sensing cloud classification. Specifically, the context graph attention layer (CGA layer) of CGAT is proposed to learn the context attention coefficients (CACs) and obtain the AFs of nodes based on the CACs. We compute the CACs not only considering the two connected nodes but also their neighborhood nodes in order to stabilize the aggregation process. In addition, we propose to utilize two different transformation matrices to transform the node and its connected nodes into new feature spaces, which could enhance the discrimination of AFs. We concatenate the AFs with the deep features (DFs) as final representations for cloud classification. Since existing ground-based cloud data sets (GCDs) have limited cloud images, we release a new data set named GCD that is the largest one for ground-based cloud classification. We conduct a series of experiments on GCD, and the experimental results verify the effectiveness of CGAT.

In this work, the advantage of Coulomb repulsion in the intermolecular forces experienced by molecules on the solid-liquid nanosized contact interface is taken, and the superior friction-reducing property of Cu3(PO4)2·3H2O (CuP) oil-based additives has been confirmed for titanium alloy. 3D CuP nanoflowers (CuP-Fs) with a strong capillary absorption effect are prepared to achieve the homogeneous mixing of solid CuP and lubricating oil. Lubrication by CuP-Fs additives for titanium alloy, friction coefficient (COF) can be reduced by 73.68%, and wear rate (WR) reduced by 99.69%. It is demonstrated that the extraordinary friction-reducing property is due to the repulsive solid-liquid interface with low viscous shear force originating from Coulomb repulsion between polar water molecules in CuP and non-polar oil molecules. However, any steric hindrance or connection between this repulsive solid-liquid interface will trigger the adhesion and increase the viscous shear force, for example, dispersant, hydrogen bondings, and shaky adsorbed water molecules. Besides, the lamellar thickness of CuP and molecular size of lubricant both have a great influence on tribological properties. Here the lubrication mechanism based on interface Coulomb repulsion is proposed that may help broaden the scope of the exploration in low-friction nanomaterial design and new lubricant systems.

Precise synthesis of well-ordered ultrathin nanowire arrays with tunable active surface, though attractive in optoelectronics, remains challenging to date. Herein, well-aligned sub-10 nm TiO

Multi-chambered architectures have attracted much attention due to the ability to establish multifunctional partitions in different chambers, but manipulating the chamber numbers and coupling multi-functionality within the multi-chambered mesoporous nanoparticle remains a challenge. Herein, we propose a nanodroplet remodeling strategy for the synthesis of hierarchical multi-chambered mesoporous silica nanoparticles with tunable architectures. Typically, the dual-chambered nanoparticles with a high surface area of ~469 m2 g−1 present two interconnected cavities like a calabash. Furthermore, based on this nanodroplet remodeling strategy, multiple species (magnetic, catalytic, optic, etc.) can be separately anchored in different chamber without obvious mutual-crosstalk. We design a dual-chambered mesoporous nanoreactors with spatial isolation of Au and Pd active-sites for the cascade synthesis of 2-phenylindole from 1-nitro-2-(phenylethynyl)benzene. Due to the efficient mass transfer of reactants and intermediates in the dual-chambered structure, the selectivity of the target product reaches to ~76.5%, far exceeding that of single-chambered nanoreactors (~41.3%).

Glycosaminoglycan from Apostichopus japonicus (AHG) and its depolymerized fragments (DAHGs) are anticoagulant fucosylated chondroitin sulfate. The aim of this study was to further evaluate the anticoagulant and antithrombic activity of AHG and DAHGs, as well as reveal the dynamic relationship between exposure and effect in vivo. The results demonstrated that AHG100 (Mw~100 kDa), DAHG50 (Mw~50 kDa), and DAHG10 (Mw~10 kDa) exhibited potent anticoagulant activity by inhibiting intrinsic factor Xase complex (FXase) as well as antithrombin-dependent factor IIa (FIIa) and factor Xa (FXa). These glycosaminoglycans markedly prevented thrombosis formation and thrombin-induced platelet aggregation in a dose- and molecular weight-dependent manner in vitro and in vivo. The further bleeding time measurement indicated that DAHG10 exhibited obviously lower hemorrhage risks than native AHG100. Following oral administration, DAHG10 could be absorbed into blood, further dose-dependently prolonging activated partial thromboplastin time (APTT) and thrombin time (TT) as well as inhibiting FXa and FIIa partially through FXase. Anticoagulant activity was positively associated with plasma concentration following oral administration of DAHG10. Our study proposed a new point of view to understand the correlation between effects and exposure of fucosylated chondroitin sulfate as an effective and safe oral antithrombotic agent.

Glycosaminoglycan from

A sulfhydryl monomicelles interfacial assembly strategy is presented for the synthesis of fully exposed single-atom-layer Pt clusters on 2D mesoporous TiO

Summary Owing to the weak self-assembly ability of precursor components and the unadjustable limitation of micelle structures during assembly process, the synthesis of mesoporous colloidal nanospheres with sophisticated multimodal pore system remains a great challenge. Herein, we report a programmable shear-induced dynamic assembly approach to synthesize radially gradient-structured mesoporous carbon nanospheres with tunable core-shell architectures. Detailed mechanism studies reveal that the micelle structures in our system can be well adjusted by changing the shear force. More importantly, the synthetic process can be programmatically proceeded by setting up an on-demand stirring model, resulting in the intelligent assembly of multimodal mesostructures. The resultant mesoporous carbon nanospheres show small particle size, high surface area, abundant nitrogen species, and radially oriented open-porous structure and, as a result, deliver high capability and ultra-long cyclic life for sodium-ion storage. This facile programmable assembly approach would offer new opportunities in exploring sophisticated multimodal mesostructures for innovative applications.

Constructing hierarchical three-dimensional (3D) mesostructures with unique pore structure, controllable morphology, highly accessible surface area, and appealing functionality remains a great challenge in materials science. Here, we report a monomicelle interface confined assembly approach to fabricate an unprecedented type of 3D mesoporous N-doped carbon superstructure for the first time. In this hierarchical structure, a large hollow locates in the center (∼300 nm in diameter), and an ultrathin monolayer of spherical mesopores (∼22 nm) uniformly distributes on the hollow shells. Meanwhile, a small hole (4.0-4.5 nm) is also created on the interior surface of each small spherical mesopore, enabling the superstructure to be totally interconnected. Vitally, such interconnected porous supraparticles exhibit ultrahigh accessible surface area (685 m

Sodium-ion batteries (SIBs) are a promising candidate for grid-scale energy storage, however, the sluggish ion-diffusion kinetics brought by the large radius of Na

Recently, multimodal cloud samples are utilized to learn completed feature representations for cloud classification. However, the existing methods neglect the related information from other multimodal cloud samples in the learning process, which leads to inadequate learning. In this article, we propose a novel deep model to learn heterogeneous deep features (HDFs) for multimodal ground-based remote sensing cloud classification. Specifically, we first design the convolutional neural network (CNN) extractor to combine the visual information and the multimodal information (MI) to obtain the CNN-based features of multimodal cloud samples. Afterward, we treat the CNN-based features of multimodal cloud samples as the nodes of graph, and utilize the similarity between nodes as the adjacency matrix. We feed the graph and the adjacency matrix into the graph convolutional network (GCN) extractor to obtain the GCN-based features that could capture correlations among multimodal cloud samples using graph convolutional layers. After obtaining CNN-based features and GCN-based features, we concatenate the two kinds of heterogeneous features to represent the multimodal cloud samples. As a result, the concatenated feature contains the visual information, the MI and the related information among multimodal cloud samples. We conduct a series of experiments on the multimodal ground-based cloud database (MGCD), and the experimental results verify that the proposed HDF outperforms state-of-the-art methods.

Cities rely on massive amounts of physical, chemical, and biological resources to support their growth and metabolism. These ‘metabolic inputs’ are accumulated in cities to form material stocks in buildings, infrastructures, transportation facilities, and household appliances. This study takes China’s urbanization as an example to illustrate the characteristics of material stock changes in developing countries and compare them with those in developed countries. Results show that (1) material stocks have been growing in China, but have saturated in developed countries, and (2) the major components of urban metabolism are construction and industrial materials (e.g., steel) in developing countries but biomass (e.g., food) in developed countries. The changes in the magnitude and types of material stocks can not only measure urban development but also directly link city and its residents, offering advantages in representing urbanization over the existing indices such as population, land use, or gross domestic product (GDP). Given the new insights provided by material stock, we recommend to embrace it as a critical index of urbanization for guiding urban planning and policy-making.

Mesoporous semiconducting metal oxides (SMOs) heterojunctions are appealing sensors for gas detecting. However, due to the different hydrolysis and condensation mechanism of every metal precursor and the contradiction between high crystallinity and high surface area, the synthesis of mesoporous SMOs heterojunctions with highly ordered mesostructures, highly crystallized frameworks, and high surface area remains a huge challenge. In this work, we develop a novel “acid-base pair” adjusted solvent evaporation induced self-assembly (EISA) strategy to prepare highly crystallized ordered mesoporous TiO2/WO3 (OM-TiO2/WO3) heterojunctions. The WCl6 and titanium isopropoxide (TIPO) are used as the precursors, respectively, which function as the “acid-base pair”, enabling the co-assembly with the structure directing agent (PEO-b-PS) into highly ordered mesostructures. In addition, PEO-b-PS can be converted to rigid carbon which can protect the mesostructures from collapse during the crystallization process. The resultant OM-TiO2/WO3 heterojunctions possess primitive cubic mesostructures, large pore size (∼21.1 nm), highly crystalline frameworks and surface area (∼98 m2/g). As a sensor for acetone, the obtained OM-TiO2/WO3 show excellent response/recovery performance (3 s/5 s), good linear dependence, repeatability, selectivity, and long-term stability (35 days).

Synthesis of hierarchically porous structures with uniform spatial gradient and structure reinforcement effect still remains a great challenge. Herein, we report the synthesis of zeolite@mesoporous silica core-shell nanospheres (ZeoA@MesoS) with a gradient porous structure through a micellar dynamic assembly strategy. In this case, we find that the size of composite micelles can be dynamically changed with the increase of swelling agents, which

Mimicking natural nitrogenase to create highly efficient single-atom catalysts (SACs) for ambient N

Mesoporous Janus nanoparticles, due to the independent mesoporous compartments, tunable spatial isolated surfaces and compositions, have great application potentials in establishing biological logic systems. However, the reported Janus nanoparticles without large pores are incompatible for the loading of large bio-molecules, limiting their usages as biological logic gates. Herein, an emulsion-oriented assembly approach is demonstrated for the fabrication of highly-uniform Janus double-spherical MSN&mPDA (MSN = mesoporous silica nanoparticle, mPDA = mesoporous polydopamine) nanoparticles with dual large and tunable mesopores. In this novel approach, oil droplets first interact with MSNs to form double-spherical structures, and then orient the selective-encapsulation of mPDA, leading to the final Janus double-spherical MSN&mPDA nanoparticles. The delicate Janus nanoparticle possesses a spherical MSN with a uniform size of ~ 150 nm in diameter, and a mPDA hemisphere with a diameter of ~ 120 nm. The dual-mesoporous nanoparticles possess surface area of ~ 250 m2 g−1 and also a high pore volume of ~ 0.56 cm3 g−1. In addition, the mesopore size in MSN compartment is tunable from ~ 3 to ~ 25 nm, while the mPDA compartments possess mesopores with the diameter ranging from ~ 5 to ~ 50 nm. Due to varied chemical properties and mesopore sizes in the two compartments, selective loading of guests in different compartments of the Janus mesoporous nanoparticles can be achieved. Based on such selective loading, single-particle-level biological logic gates with YES, OR and AND logics have been successfully established for the first time. We believe such work paves the way for constructing advanced asymmetric nanomaterials and realizing complex stimuli-responsive systems.

Functional mesoporous materials have gained tremendous attention due to their distinctive properties and potential applications. In recent decades, the self-assembly of micelles and framework precursors into mesostructures on the liquid-solid, liquid-liquid, and gas-liquid interface has been explored in the construction of functional mesoporous materials with diverse compositions, morphologies, mesostructures, and pore sizes. Compared with the one-phase solution synthetic approach, the introduction of a two-phase interface in the synthetic system changes self-assembly behaviors between micelles and framework species, leading to the possibility for the on-demand fabrication of unique mesoporous architectures. In addition, controlling the interfacial tension is critical to manipulate the self-assembly process for precise synthesis. In particular, recent breakthroughs based on the concept of the "monomicelles" assembly mechanism are very promising and interesting for the synthesis of functional mesoporous materials with the precise control. In this review, we highlight the synthetic strategies, principles, and interface engineering at the macroscale, microscale, and nanoscale for oriented interfacial assembly of functional mesoporous materials over the past 10 years. The potential applications in various fields, including adsorption, separation, sensors, catalysis, energy storage, solar cells, and biomedicine, are discussed. Finally, we also propose the remaining challenges, possible directions, and opportunities in this field for the future outlook.

Streamlined architectures with a low fluid-resistance coefficient have been receiving great attention in various fields. However, it is still a great challenge to synthesize streamlined architecture with tunable surface curvature at the nanoscale. Herein, we report a facile interfacial dynamic migration strategy for the synthesis of streamlined mesoporous nanotadpoles with varied architectures. These tadpole-like nanoparticles possess a big streamlined head and a slender tail, which exhibit large inner cavities (75-170 nm), high surface areas (424-488 m2 g-1), and uniform mesopore sizes (2.4-3.2 nm). The head curvature of the streamlined mesoporous nanoparticles can be well-tuned from ∼2.96 × 10-2 to ∼5.56 × 10-2 nm-1, and the tail length can also be regulated from ∼30 to ∼650 nm. By selectively loading the Fe3O4 catalyst in the cavity of the streamlined silica nanotadpoles, the H2O2-driven mesoporous nanomotors were designed. The mesoporous nanomotors with optimized structural parameters exhibit outstanding directionality and a diffusion coefficient of 8.15 μm2 s-1.

Multistage pump of lean amine liquid is crucial rotating equipment in an industrial refining catalytic reforming unit. Cavitation often causes the damage of impeller in the pump to affect the long-term safe operation of unit. The formation of cavitation on impeller is 3D simulated by using Zwart-Gerber-Belamri model in accord with the actual position under the industrial operating condition. The discrepancies of cavitation range between different volume flux (400 to 800 m3/s. operating pressure (0.4 to 2.0 MPa) and vapor pressure of lean amine liquid (0.05 to 0.5 MPa) in terms of the industrial running conditions every stage impeller are investigated to guide design and safety operation of pump. The simulation results indicate that the impeller cavitation often starts from the forward-curved groove of the blade. and then gradually expands along the flow path of the blade and the two side walls of the forward bend. When the volume flux exceeds critical value of cavitation. the impellers appear cavitation and those ranges enlarge and expend along the flow direction of the blade with the increase of volume flux. With the cavitation pressure increasing. the cavitation ranges of impeller lesson even to disappear. especially at 2.0 MPa. Bigger vapor pressure of lean amine liquid leads easily to erosion.

In this work, the erosion in the four-way pipe of the heavy oil thermal production was studied by experiment and CFD simulations. The metallographic analysis and the micro erosion morphology of the damaged four-way pipe were done and analyzed. The erosion experiment of four-way pipe material ZG(J)35CrMo was carried out by the multiphase flow erosion tester, and the erosion prediction model was established and modified, which was coupled with the Euler-Largrangian gas-solid two phase flow model and used in the CFD simulations. First, the simulation results were compared with the actual invalidation case, through which the validity of the model is proved. Then, the effects of whether the pit defect located in the erodible site or not, fluid velocity, particle diameter and mass flow rate on the erosion rate were investigated using the CFD model. The erosion rate would increase with the fluid velocity, mass flow rate. And the results show that if the pit defect located in the erodible site coincidentally, the erosion rate will increase sharply, maybe several times, which may increase the failure risk of the four-way pipe increase.

Facile synthesis of ultrahigh surface area porous carbons with well-defined functionalities such as N-doping remains a formidable challenge as extensive pore creation results in significant damage to the active sites. Herein, an ultrahigh surface area, N-doped hierarchically porous carbon was prepared through a multicomponent co-assembly approach. The resultant N-doped hierarchically porous carbon (N-HPC) possessed an ultrahigh surface area (≈1960 m2 g-1 ), a uniform interpenetrating micropore (≈1.3 nm) and large mesopore (≈7.6 nm) size, and high N-doping in the carbon frameworks (≈5 wt %). The N-HPC exhibited a high specific capacitance (358 F g-1 at 0.5 A g-1 ) as a supercapacitor electrode in aqueous alkaline electrolyte with a stable cycling performance after10 000 charge/discharge cycles. Moreover, as a CO2 absorbent, N-HPC displayed an adsorption capacity of 29.0 mmol g-1 at 0 °C under a high pressure of 30 bar.

High capacity transition metal oxides have attracted much attention as potential sodium-ion batteries (SIBs) anodes. However, the fast capacity fading greatly limits their practical applications. In this study, highly crystallized mesoporous Fe3O4 nanoparticles encapsulated in the hollow nitrogen-doped carbon nanospheres (denoted as HCM-Fe3O4@void@N-C) have been synthesized and then explored as anode materials for SIBs. The resultant HCM-Fe3O4@void@N-C nanospheres possess a uniform particle size of ~ 180 nm with highly crystallized mesoporous Fe3O4 cores (~ 100 nm in diameter), a large surface area of ~ 250 m2 g−1 and a nitrogen-doped carbon shell (~ 7.6 wt%). Notably, a high discharge capacity of 372 mA h g−1 is obtained after the first five cycles at 160 mA g−1, which can gradually increase and be maintained at an ultrahigh specific capacity of 522 mA h g−1 even after 800 cycles. Besides, remarkable rate performance with a capacity of 196 mA h g−1 at a current density of 1200 mA g–1 and a high Coulombic efficiency (~ 100%) are obtained. Such good performance can be attributed to the unique yolk-shell nanostructure with a high crystallized mesoporous Fe3O4 core, a high conductive N-doped carbon shell, and a suitable void space, paving a new way to design and synthesize high-performance anode materials for SIBs.

Recently, the multimodal information is taken into consideration for ground-based cloud classification in weather station networks, but intrinsic correlations between the multimodal information and the visual information cannot be mined sufficiently. We propose a novel approach called hierarchical multimodal fusion (HMF) for ground-based cloud classification in weather station networks, which fuses the deep multimodal features and the deep visual features in different levels, i.e., low-level fusion and high-level fusion. The low-level fusion directly fuses the heterogeneous features, which focuses on the modality-specific fusion. The high-level fusion integrates the output of low-level fusion with deep visual features and deep multimodal features, which could learn complex correlations among them owing to the deep fusion structure. We employ one loss function to train the overall framework of the HMF so as to improve the discrimination of cloud representations. The experimental results on the MGCD dataset indicate that our method outperforms other methods, which verifies the effectiveness of the HMF in ground-based cloud classification.

Ultrafine nanoparticles with organic-inorganic hybridization have essential roles in myriad applications. Over the past three decades, although various efforts on the formation of organic or inorganic ultrasmall nanoparticles have been made, ultrafine organic-inorganic hybrid nanoparticles have scarcely been achieved. Herein, a family of ultrasmall hybrid nanoparticles with a monodisperse, uniform size is synthesized by a facile thermo-kinetics-mediated copolymer monomicelle approach. These thermo-kinetics-mediated monomicelles with amphiphilic ABC triblock copolymers are structurally robust due to their solidified polystyrene core, endowing them with ultrahigh thermodynamic stability, which is difficult to achieve using Pluronic surfactant-based micelles (e.g., F127). This great stability combined with a core-shell-corona structure makes the monodispersed monomicelles a robust template for the precise synthesis of ultrasmall hybrid nanoparticles with a highly uniform size. As a demonstration, the obtained micelles/SiO2 hybrid nanoparticles display ultrafine sizes, excellent uniformity, monodispersity, and tunable structural parameters (diameters: 24-47 nm and thin shell thickness: 2.0-4.0 nm). Notably, this approach is universal for creating a variety of multifunctional ultrasmall hybrid nanostructures, involving organic/organic micelle/polymers (polydopamine) nanoparticles, organic/inorganic micelle/metal oxides (ZnO, TiO2 , Fe2 O3 ), micelle/hydroxides (Co(OH)2 ), micelle/noble metals (Ag), and micelle/TiO2 /SiO2 hybrid composites. As a proof of concept, the ultrasmall micelle/SiO2 hybrid nanoparticles demonstrate superior toughness as biomimetic materials.

The cloud recognition technology is helpful in weather analysis, climate research, and communication, and various automatic cloud recognition methods are proposed. Among them, the cloud recognition methods using the multimodal information to show their superiority. In this paper, we give a review of these methods and divide them into two categories, i.e., separate fusion and end-to-end fusion. The separate fusion means directly fusing the multimodal information with features of cloud image, and the end-to-end fusion is to train the fusion of mutlimodal features and visual features of cloud images in an unified framework. Finally, we list experiment results on the cloud datasets to evaluate their performances.

Iridium (Ir)-based electrocatalysts are widely explored as benchmarks for acidic oxygen evolution reaction (OER), but further enhancing their catalytic activity has been retarded by the unidentified active species and unfavorable architectures. In this work, we first report two-dimensional (2D), ordered mesoporous Ir-IrOx/C catalysts with mixed valent species (Ir0, IrIV, and IrV) through a nanoconfined self-assembly strategy. The mesoporous Ir-IrOx/C catalyst has highly ordered layered nanochannels (~20 nm) and uniformly dispersed Ir-IrOx nanoparticles (~2 nm). Benefits from the mixed valence states and favorable mesostructured architecture, the resultant catalyst displays the lowest overpotential (η) of 198 mV at 10 mA cm-2geo for Ir-based OER electrocatalysts in an acid medium. Both experimental and computational results reveal that the IrV moiety of 2D mesoporous Ir-IrOx/C catalysts with a shortened Ir-O(II-δ)- bond (1.91 A) is the key active species for the enhancement of OER by balancing the adsorption free energy of oxygen-containing intermediates. This study provides a model for an in-depth understanding of the active origin of the ordered mesoporous Ir-based electrocatalysts and role of V species in OER, as well as opens an avenue for designing high-efficient 2D ordered mesoporous electrocatalysts for water oxidation.

In satellite communication, carrier parameter estimation usually uses a serial structure, and the accuracy of frequency offset estimation (FOE) will greatly affect the accuracy of phase offset estimation (POE). A new carrier synchronization mode (NCSM) can realize the decoupling of carrier FOE and POE to a certain extent, but this mode is based on multibase phase shift keying (MPSK) modulation analysis, the decoupling performance is poor when uses in amplitude phase shift keying (APSK) modulation, and the decoupling performance of NCSM has a low tolerance of frequency offset. An improved carrier parameter estimation decoupling technique is proposed to solve these problems. The simulation results show that, compared with the original method, under the premise of ensuring the accuracy of carrier parameter estimation, the proposed method is more robust to the modulation mode, the POE has stronger antioffset ability, and the normalized FOE range has been significantly enhanced.

The functionalization of otherwise unreactive C–H bonds adds a new dimension to synthetic chemistry, yielding useful molecules for a range of applications. Arylation has emerged as an increasingly viable strategy for functionalization of heteroarenes which constitute an important class of structural moieties for organic materials. However, direct bisarylation of heteroarenes to enable aryl-heteroaryl-aryl bond formation remains a formidable challenge, due to the strong coordination between heteroatom of N or S and transitional metals. Here we report Pd interstitial nanocatalysts supported on ordered mesoporous carbon as catalysts for a direct and highly efficient bisarylation method for five-membered heteroarenes that allows for green and mild reaction conditions. Notably, in the absence of any base, ligands and phase transfer agents, high activity (turn-over frequency, TOF, up to 107 h−1) and selectivity (>99%) for the 2,5-bisarylation of five-membered heteroarenes are achieved in water. A combination of characterization reveals that the remarkable catalytic reactivity here is attributable to the parallel adsorption of heteroarene over Pd clusters, which breaks the barrier to electron transfer in traditional homogenous catalysis and creates dual electrophilic sites for aryl radicals and adsorbate at C2 and C5 positions. The d-band filling at Pd sites shows a linear relationship with activation entropy and catalytic activity. The ordered mesopores facilitate the absence of a mass transfer effect. These findings suggest alternative synthesis pathways for the design, synthesis and understanding of a large number of organic chemicals by ordered mesoporous carbon supported palladium catalysts., The developed ordered mesoporous carbon supported palladium interstitial catalysts demonstrate simultaneous multiple electron transfer and provide alternative paths for heteroarenes synthesis, which overcome the electron transfer restriction of the traditional homogenous catalyst.

Carbonic anhydrase (CA) has great potential for CO2 capture; however, the application of CA is still a challenge due to its difficult recovery, low operational stability, and poor reusability. This paper reports the synthesis of hybrid nanoflowers (M–CANFs) by self-assembly of CA and metal phosphates. Mn–CANFs were first discovered in this work although their performance is not excellent, and the performance of M–CANFs formed by different metal phosphates was compared in detail. The results of catalyzing p-nitrophenyl acetate (p-NPA) hydrolysis showed that Ca–CANFs exhibited ca. 286% enhancement of catalytic activity. The stability, reusability, and thermal stability of M–CANFs had enhanced remarkably. The newly formed flowerlike hybrid nanostructures presented multiple flower morphology with great biocatalytic activity and stability enhancement by cycle analysis. The excellent performances are meaningful for biology, catalysis science, and nanomaterials science.

Carcinogenic arsenic pollution in ground water seriously threatens the health and lives of humans all over the world. It is highly desirable to fabricate new materials for sustainable arsenate removal with high capacities, stabilities and recyclabilities. In this study, we demonstrate that uniform magnetic core–shell structured Fe3O4@Resorcinol-Formaldehyde@mesoporous TiO2 microspheres (denoted Fe3O4@RF@mTiO2) can function as excellent adsorbents for the fast removal of arsenate (AsV) in acidic environments with very high efficiency. The mesoporous TiO2 outer shell (50 nm in thickness) endows them with a high surface area of 337 m2 g−1 and a large pore volume of 0.42 cm3 g−1, thus resulting in a fast adsorption rate (1.16 g mg−1 h−1) and a high adsorption capacity (up to 139 mg g−1) calculated using the Langmuir model at a pH of 3. The inner Fe3O4 core (130 nm in diameter) makes separation facile from wastewater using a magnet. Moreover, the hydrophobic properties of the RF interlayer (10 nm in thickness) are increased after calcination at 200 °C, and this can protect the inner Fe3O4 cores against etching from acid solutions over long cycles. In addition, the study of the AsV adsorption mechanism on the core–shell mesoporous Fe3O4@RF@mTiO2 microspheres shows the existence of electrostatic forces and surface complexation interactions between arsenate and partially crystallized TiO2. Benefiting from all of these advantages, the multilayer magnetic core–shell structured design is expected to be a promising nanomaterial for long-term wastewater treatment.

Copper is ubiquitously used in buildings, infrastructure, transportation, machinery, and other products because of its high conductivity. Massive amounts of copper have accumulated in cities with rapid urbanization. However, the lack of detailed spatiotemporal information on copper stocks presents a challenge for waste management and resource recycling. Here, we took the Jing-Jin-Ji urban agglomeration in China, which has experienced rapid urbanization over the past few decades, as a case study to characterize the spatiotemporal patterns of in-use copper stock. The results showed that in-use copper stocks per capita had reached 61 kg in 2016, about 3.8 times the level it was in 1990. Buildings, electric power transmission and distribution systems, small passenger cars, industrial machinery, and air conditioners dominated the in-use stocks and thus, they were the main reservoirs of secondary resources. Significant economic and population growth stimulated a rapid increase in copper stocks, especially in the megacities (e.g., Beijing, Tianjin, Shijiazhuang, Tangshan, and Handan). Based on the scenarios of urbanization, we estimated that in-use stocks of copper per capita would continue to grow in the Jing-Jin-Ji urban agglomeration until saturation, and that the saturation level might be lower than that of developed countries. High population density was key to promoting copper resource utilization efficiency, particularly in the infrastructure sector. This critical information highlights the urgent need for developing compact cities to reduce the pressure caused by copper resource consumption in China.

Many kinds of dangerous chemicals, like liquefied natural gas etc., are stored or transported in liquid state by pressure vessel. Liquid sloshing will occur in many scenarios such as during the geological disasters, and the transit operations. Sloshing might lead to large deformation or even damage to containers, causing serious safety threats. In this study, the sloshing phenomenon in a cylindrical tank with four baffle shapes are investigated. The volume-of-fluid (VOF) method is used to track the distorted and broken free surface. Fluid movement phenomenon in tank with different baffles is observed. The effect of four different baffles shapes is compared, impacting force on tank and baffle walls which induced by liquid sloshing is analyzed. Baffles openings affect the impact forces on the tank and baffle walls. More number of baffle orifices, liquid distribution is more even in sections of the tank. Maximum force value of y direction occurs as the liquid climbs up the tank ceiling. Reasonable number and position of baffle openings can increase the stability of the tank during driving. For this simulation method, more validation with experimental data is necessary, the same size of tank and four baffle shapes will be tested on the shaking platform.

Plastics are ubiquitous in the environment and have become a hot topic in academic circles. Extensive studies have focused on analytical methods, source, abundance, transport, fate, degradation of plastics in the environment and threats to natural surroundings, wildlife or even human health. However, characteristics of plastic pollution, which are critical to understand this emerging problem, remain unknown up to now. Here, this paper reviews the major characteristics of plastic pollution in the environment to enhance present understanding of this issue. These characteristics, including diversity, persistence, global issues, combined pollution and threats to organisms and human health, are critically summarized in this work. Further, "plastic cycle" in the environment, namely, aquatic, atmospheric, and terrestrial system, is also discussed in this review. Finally, we highlight current challenges of plastic pollution posed to the public and also recommend the research trends in future work.

A molecular design strategy is used to construct ordered mesoporous Ti3+-doped Li4Ti5O12 nanocrystal frameworks (OM-Ti3+-Li4Ti5O12) by the stoichiometric cationic coordination assembly process. Ti4+/Li+-citrate chelate is designed as a new molecular precursor, in which the citrate can not only stoichiometrically coordinate Ti4+ with Li+ homogeneously at the atomic scale, but also interact strongly with the PEO segments in the Pluronic F127. These features make the co-assembly and crystallization process more controllable, thus benefiting for the formation of the ordered mesostructures. The resultant OM-Ti3+-Li4Ti5O12 shows excellent rate (143 mAh g?1 at 30 C) and cycling performances (

Facile synthesis of ultrahigh surface area porous carbons with well-defined functionalities such as N-doping remains a formidable challenge as extensive pore creation results in significant damage to the active sites. Herein, an ultrahigh surface area, N-doped hierarchically porous carbon was prepared through a multicomponent co-assembly approach. The resultant N-doped hierarchically porous carbon (N-HPC) possessed an ultrahigh surface area (≈1960 m

CFD is used to simulate liquid sloshing which affects the safety of baffles in this study, a three-dimensional model of a tank is established. The fluid-structure interaction method is applied to analyze the liquid sloshing phenomenon, deformation and stress of baffles during the acceleration. The distribution of liquid phase in a tank with 0.5 and 0.8 liquid filling ratios are studied. Force distribution of the baffles at different times under 0.8 liquid filling ratio is researched to obtain deformation and stress of baffles under this condition. The simulation results show that the liquid distribution in a tank with 0.8 liquid filling ratio is more stable than that with 0.5. During the acceleration process of the tank with 0.8 liquid filling ratio, the deformation and stress of the baffles are inversely proportional. The roots of baffles suffer from large stress, which is easy to crack under certain conditions. It should take protective measures at the root of the baffles to avoid cracking.

An aqueous emulsion polymerization self‐assembly approach is demonstrated for the first time to synthesize ultrahigh nitrogen containing mesoporous polymer nanospheres, using melamine‐formaldehyde resin oligomers as precursors. In the synthesis, change from alkaline to acidic conditions is critical for the formation of monodisperse mesostructured polymer nanospheres. Owing to unique structure of triazine stabilized in the covalent polymeric networks during the pyrolysis process, the derived mesoporous carbon nanospheres possess an ultrahigh nitrogen content (up to 15.6 wt%) even after pyrolysis at 800 °C, which is the highest nitrogen content among mesoporous carbon nanospheres. Furthermore, these monodisperse mesoporous carbon nanospheres possess a high surface area (≈883 m2 g−1) and large pore size (≈8.1 nm). As an anode for sodium‐ion batteries, the ultrahigh nitrogen‐containing mesoporous carbon nanospheres exhibit superior rate capability (117 mAh g−1 at a high current density of 3 A g−1) and high reversible capacity (373 mAh g−1 at 0.06 A g−1), indicating a promising material for energy storage.

In order to ensure microsecond slot scheduling, all terminals must maintain high precision of time synchronization in MF-TDMA(Multi-Frequency Time Division Multiple Access) satellite communication system. Due to the different frequency of crystal oscillator at the terminal, the absolute value of the clock deviation is constantly increasing, so a clock synchronization algorithm is required to keep the time synchronization of the satellite system. The traditional satellite clock synchronization algorithm minimizes the clock error through periodic synchronization, but it only considers the phase offset, not the crystal frequency offset, the synchronization accuracy is low and waste of bandwidth resources. Based on the traditional satellite clock synchronization, this paper proposes a gradient descent algorithm for the satellite system based on MF-TDMA(GDAS), adding clock frequency offset prediction and compensation mechanism to improve clock synchronization accuracy and bandwidth resource utilization rate. The simulation results of the proposed algorithm has optimized the precision performance of clock synchronization.

The fast estimation of synchronization parameters plays an extremely important role in the demodulation of burst signals. In order to solve the problem of high computational complexity in the implementation of traditional algorithms, a synchronization parameter (frequency offset, phase offset, and timing error) estimation algorithm based on Offset Quadrature Phase Shift Keying (OQPSK) burst signal detection is proposed in this article. We first use the Data-Aided (DA) method to detect where the burst signal begins by taking the segment correlation between the receiving signals and the known local Unique Word (UW). In the sequel, the above results are adopted directly to estimate the synchronization parameters, which is obviously different from the conventional algorithms. In this way, the complexity of the proposed algorithm is greatly reduced, and it is more convenient for hardware implementation. The simulation results show that the proposed algorithm has high accuracy and can track the Modified Cramer&ndash, Rao Bound (MCRB) closely.

The completely C2-selective arylation of N-methylindole was achieved by using a reusable solid Pd catalyst and water as a solvent without any other ligands or additives or exclusion of air. The catalysts possess well-dispersed Pd nanoparticles (∼1.5 nm), N-containing functional groups (∼11 wt %), and uniform mesopores (∼5 nm). The turnover frequency (TOF) is calculated to be 82 h–1.Arylations of both N-H indoles and N-protected indoles with diaryliodonium salts were achieved to give the desired products in high to excellent isolated yields in water. Mercapto-functionalized silica as a selective trapping agent, together with hot filtration, confirms the undetected leaching of Pd. The catalyst samples can be reused at least eight times without any additional activation treatment. The catalytic performance of the Pd catalyst is also compared with the performance of other mesoporous Pd catalysts on silica, carbon, and resins. The catalytic activity and stability of the present catalyst may be related to the w...

The photocatalytic properties of TiO have aroused a broad range of research interest since 1972 due to its abundance, chemical stability, and easily available nature. To increase its overall activity, in the past few decades, much effort has been devoted to the fabrication of advanced TiO-based photocatalysts with visible-light response and these photocatalysts have shown great potential in the field of solar energy utilization. Here, recent progress in the investigation of visible-light responsive TiO-based materials are reviewed. Notably, the fabrication strategies and corresponding chemical/physical properties of visible-light responsive TiO-based materials are described in detail, with a focus on bandgap engineering and junction engineering from the perspective of light absorption, charge transfer and separation, and surface reactions. Their applications in solar-fuel production, organic synthesis, bacterial disinfection, pollutant degradation and nitrogen fixation are also discussed. Moreover, the new trends and ongoing challenges in this field are proposed and highlighted.