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Deep learning-aided optical orthogonal frequency division multiplexing (O-OFDM) is proposed for intensity modulated direct detection transmissions, which is termed as O-OFDMNet. In particular, O-OFDMNet employs deep neural networks (DNNs) for converting a complex-valued signal into a non-negative signal in the time-domain at the transmitter and vice versa at the receiver. The associated frequency-domain signal processing remains the same as in conventional radio frequency (RF) OFDM. As a result, our scheme achieves the same spectral efficiency as the RF scheme, which has never been attained by the existing O-OFDM schemes, because they have relied on the Hermitian symmetry of the spectral-domain signal to guarantee that the time-domain signal becomes real-valued. We show that O-OFDMNet can be viewed as an autoencoder architecture, which can be trained in an end-to-end manner in order to simultaneously improve both the bit error ratio (BER) and the peak-to-average power ratio (PAPR) for transmission over both additive white Gaussian noise and frequency-selective channels. Furthermore, we intrinsically integrate a soft-decision aided channel decoder with our O-OFDMNet and investigate its coded performance relying on both convolutional and polar codes. The simulation results show that our scheme improves both the uncoded and coded BER as well as a reducing the PAPR compared to the benchmarks at the cost of a moderate additional DNN complexity. Furthermore, our scheme is capable of approaching the throughput of RF-OFDM, which is notably higher than that of conventional O-OFDM. Finally, our complexity analysis shows that O-OFDMNet is suitable for real-time operation.

We address counting and optimization variants of multicriteria global min-cut and size-constrained min-k-cut in hypergraphs. 1) For an r-rank n-vertex hypergraph endowed with t hyperedge-cost functions, we show that the number of multiobjective min-cuts is O(r2^{tr}n^{3t-1}). In particular, this shows that the number of parametric min-cuts in constant rank hypergraphs for a constant number of criteria is strongly polynomial, thus resolving an open question by Aissi, Mahjoub, McCormick, and Queyranne [Aissi et al., 2015]. In addition, we give randomized algorithms to enumerate all multiobjective min-cuts and all pareto-optimal cuts in strongly polynomial-time. 2) We also address node-budgeted multiobjective min-cuts: For an n-vertex hypergraph endowed with t vertex-weight functions, we show that the number of node-budgeted multiobjective min-cuts is O(r2^{r}n^{t+2}), where r is the rank of the hypergraph, and the number of node-budgeted b-multiobjective min-cuts for a fixed budget-vector b ∈ ℝ^t_+ is O(n²). 3) We show that min-k-cut in hypergraphs subject to constant lower bounds on part sizes is solvable in polynomial-time for constant k, thus resolving an open problem posed by Queyranne [Guinez and Queyranne, 2012]. Our technique also shows that the number of optimal solutions is polynomial. All of our results build on the random contraction approach of Karger [Karger, 1993]. Our techniques illustrate the versatility of the random contraction approach to address counting and algorithmic problems concerning multiobjective min-cuts and size-constrained k-cuts in hypergraphs.

Reinforcing electronic and ionic conductivity is very important to realize the high-rate Li2ZnTi3O8 (LZTO) anode for Lithium-ion batteries (LIBs). Here, we reported a synthetic strategy toward in situ growth of homodispersed Li2ZnTi3O8 on ultralight 3D carbon aerogels (CAs) via facile heat treatment and activation process taking LiOH as activating agent. Such an optimized composite obtains a specific surface area of 154.427 m2 g−1 and a high pore volume. The strong interaction between the LZTO and N-doped CAs, a highly electrical conductivity and multidimensional ion transport channels of the hybrid result in a high capacity, outstanding high-rate performance and long cycle life. As a result, the NPC-LZTO electrode (NPC-LZTO-B) delivers a commendable reversible capacity at high-rate (e.g. 162.4 mAh g−1 at 5 A g−1 (22 C) and 127.3 mAh g−1 at 10 A g−1) and durable long-term performance (capacity retention of 73% after 4500 cycles at 5 A g−1). Moreover, the kinetic analysis confirms that the feature of pseudocapacitance boosts lithium-ion storage performance at high rate. Porous carbon aerogels frame constructed LZTO nanocomposite electrodes provide a facile way to design high durable LIBs anode.

A novel laminated TiAl matrix composite (LMC) consisting of alternating equiaxed grain layers (EGLs) and fully lamellar grain layers (FGLs) has been fabricated successfully by hot pressing of alternating Ti/Al–6Si foils and subsequent multi-step reaction annealing. The oxidation behavior of the LMC at 800 °C was studied. The results show that the oxide scale is formed with typical multilayer structure after oxidized at 800 °C for 100 h. The oxidation behavior is different between EGLs and FGLs while the thickness of oxide scale is almost identical, suggesting an isotropy oxidation resistance of the LMC. Si addition effectively enhances the oxidation resistance of the LMC.

The thermal effect caused by deep magma intrusion can not only accelerate the metamorphism of coal body, but also bring additional thermal field that changes the mechanical environment of coal seams, thereby affecting the permeability of coal seams. Different from shallow coal resources, deep coal resources are in a mechanical environment characterized by limited stress and strain. Thus, the thermal effect has a more significant influence on the distribution and permeability characteristics of deep coal seams. In this study, the evolution history of highly metamorphic coal seams in Yangquan mining area was analyzed, and the main effect of magmatic activity on coal seams was obtained. Based on the determined vitrinite reflectance data of typical mines in Yangquan mining area, the maximum paleotemperature was calculated by adopting the Barker’s method. Furthermore, the paleotemperature distribution in Yangquan mining area was summarized, and its relationship with the metamorphic degree was acquired. Then, a new permeability model considering the thermal strain was proposed to analyze the permeability evolution in deep coal seams at different ground temperatures. Finally, through a combination of the results of gas pressure and outburst number in Sijiazhuang Mine, Yangquan No. 5 Mine and Xinjing Mine, the influence of ground temperature on the gas outburst risk in Yangquan mining area was explored. The following conclusions were drawn: The maximum paleotemperature in Yangquan area can be 303 °C. In addition, the paleotemperature in the south is higher than that in the north of Yangquan mining area. The various temperatures at different depths bring about different degrees of thermal stress to different coal seams, leading to different strains. Under the fixed displacement boundary conditions in the deep, the coal seam folds and bends to varying degrees. Moreover, the difference in the ground temperature raises the a value of coal seams and lowers the permeability, which promotes the formation of gas-rich zones and increases the risk of coal seam outburst. The research results can help mines to make proper gas disaster prevention plan for different zones.

Based on the local thermal non-equilibrium theory, a modified transient two-dimensional numerical model is developed to investigate the simultaneous charging and discharging performance of a molten-salt packed-bed thermocline tank employed in concentrated solar power plants. Two different types of operation including that of stable and periodic charging with steady discharging are analyzed. Three different solid fillers are utilized, including quartzite rock, slag pebbles, and alumina ceramics. The effects of charging/discharging flow rate ratio and non-charging periods on thermocline thickness and energy storage power have been investigated. The results show significant influences of the charging/discharging flow rate ratio. When charging is steady, the discharge performance of a packed-bed tank is better than that of a pure molten-salt tank at lower flow rate ratios. The thermocline thickness of the packed-bed tank is higher than that of a pure molten-salt tank for different solid materials. Compared with quartzite rock and slag pebbles, alumina ceramics achieves a higher thermal gradient. In periodic charging mode, as the cycle’s number of charging periods increases, thermocline thickness increases linearly. Operating at higher charging rates and shorter non-charging periods, the discharge outlet temperature of molten-salt becomes more stable for the steam generation process and hence, the discharge performance is improved.

Y-type hexaferrites with non-collinear conical magnetic structures, which induce electric polarization (P), are prospective single-phase multiferroics with broad applications, such as magnetic sensors, energy convertors, and memory devices, among others. Y-type hexaferrites have attracted considerable attention. In this study, we investigated the magnetoelectric properties of Ba0.7Sr1.3CoZnFe11AlO22 single crystals with Y-type hexaferrite structures by replacing half of Zn2+ ions with Co2+ ions. A transition from a screw order to the ferromagnetic is observed at TN2 = 356 K in Ba0.7Sr1.3CoZnFe11AlO22 single crystals. The electric polarization (P) and magnetoelectric coupling coefficient ( α ) reach a maximum of 130 μC/m2 and 16667 ps/m at T = 30 K and E = 880 kV/m, respectively. Most importantly, the in-plane Hab induced P can be fully reversed by applying in-plane Hab and it maintains a non-zero value even when the applied magnetic field is zero. Since the P does not decay and repeats many times under a fluctuating low magnetic field, it is important for potential applications in new types of non-volatile memory devices.

Steel Fiber Concrete Encased Steel (SFCES) beams were subjected to bending to investigate the effect of steel fibers on the behavior of Steel Reinforced Concrete beams with or without steel reinforcement. 18 SFCES beams reinforced with steel fibers, steel reinforcement, or both were cast. The parameters considered in the experiment were (a) the volume percentage of steel fiber (0%, 1%, and 2%), (b) the shear span to depth ratio( s/d = 2.5 and 3.5), (c) the stirrups spacing (180 mm and 360 mm), and (d) the presence or absence of longitudinal reinforcement (2Φ8+2Φ10).The cracking load, crack development, energy dissipation capacity, and ductility of the specimens were investigated. The results illustrate that the cracking load F c, the total energy consumption, and the energy ductility increase with increasing steel fiber volume, and the average improvement with a steel fiber volume increase of 1% can reach 36.5%, 21.2%, and 28.67%, respectively. However, this strengthening effect of steel fibers was weakened due to the addition of steel reinforcement. The influence of the steel fiber volume and reinforcement configuration on each stage of energy consumption was mainly concentrated in the elastic ( E 1) and failure stages ( E 3). Finally, mathematical equations were proposed to predict the cracking load and crack width of the SFCES specimens, which were verified by comparing the predictions with the experiment results.

Recently, image feature extraction algorithms based on 2D discriminant local preserving projection (2DDLPP) algorithms have been successfully applied in many fields. The 2DDLPP can maintain the discrimination information of the local intrinsic manifold structure using two-dimensional image representation data. However, the 2DDLPP algorithm encounters the problem of the sensitivity of overlapping points (outliers) and requires high computational cost in real-world applications. In order to resolve the problems mentioned above, we introduce a new elastic feature extraction algorithm called the sparse fuzzy 2D discriminant local preserving projection (SF2DDLPP). First, the membership matrix is calculated using the fuzzy k-nearest neighbours (FKNN), which is applied to the intraclass weighted matrix and the interclass weighted matrix. Second, two theorems are developed to directly solve the generalized eigenfunctions. Finally, the optimal sparse fuzzy 2D discriminant projection matrix is regressed using the elastic net regression. The experiments show the effectiveness and stability of this algorithm on several face (ORL, Yale, AR and Yale B), USPS and palm print datasets.

Nanostructured transition-metal oxides have been under intensive investigation for their tantalizing potential as anodes of next-generation lithium-ion batteries (LIBs). However, the exact mechanism for nanostructures to influence the LIB performance remains largely elusive. In this work, we discover the nanostructure-mediated lithiation mechanism in Co3O4 anodes using ex situ transmission electron microscopy (TEM) and X-ray diffractometry: while Co3O4 nanosheets exhibit a typical two-step conversion reaction (from Co3O4 to CoO and then to Co0), Co3O4 nanoarrays can go through a direct conversion from Co3O4 to Co0 at a high discharge rate. Such nanostructure-dependent lithiation can be rationalized by the slow lithiation kinetics intrinsic to Co3O4 nanoarrays, which at a high discharge rate may cause local accumulation of lithium to initiate a one-step Co3O4-to-Co0 conversion. Combined with the larger volume change observed in Co3O4 nanoarrays, the slow lithiation kinetics can lead to inhomogeneous expansion with large stress developed at the reaction front, which can eventually cause structure failure and irreversible capacity loss, as explicitly observed by in situ TEM as well as galvanostatic discharge-charge measurement. Our observation resolves the nanostructure-dependent lithiation mechanism of Co3O4 and provides important insights into the interplay among lithiation kinetics, phase evolution, and lithium-storage performance, which can be translated into electrode design strategies for next-generation LIBs.

The therapeutic efficacy of programmed cell death protein 1/programmed cell death-ligand 1 (PD-1/PD-L1) blockade immunotherapy is extremely dampened by complex immunosuppressive mechanisms including regulatory T cells (Treg), M2 macrophages (M2), and prostaglandin E2 (PGE2). The pivotal roles of PGE2 have been recognized by directly inactivating CD8+ T cells and indirectly inducing Treg and M2. Therefore, PGE2 abolishment through inactivating cyclooxygenase-2 (COX-2) could be robust to sensitize tumour toward anti-PD-1/PD-L1 immunotherapy, which has gone into clinical trials. However, exploring this promising strategy in nanomedicine to enhance immunotherapy remains unrevealed. The key challenge to synergistically combine COX-2 inhibition and anti-PD-1/PD-L1 lies in the different pharmacokinetic profiles and the spatial obstacles since PD-1/PD-L1 interaction occurs extracellularly and COX-2 locates intracellularly. Thus, the programmed release nanoparticles (termed as Cele-BMS-NPs) are rationally designed, which are composed of pH-sensitive human serum albumin derivative, BMS-202 compound as PD-1/PD-L1 inhibitor, glutathione (GSH)-activatable prodrug of celecoxib (COX-2 inhibitor). The in vitro experiments demonstrate that this smart Cele-BMS-NPs could extracellularly release BMS-202 under the acidic tumour microenvironment, and the intracellularly release of celecoxib in response to the elevated GSH concentration inside tumour cells. After systemic administration, the intratumoral infiltration of CD8+ T cells is significantly enhanced and meanwhile immunosuppressive M2, Treg, and PGE2 are reduced, thereby eliciting the anti-tumour immune responses toward low immunogenic tumours and postsurgical tumour recurrences.

In this study, three-dimensional numerical analyses were carried out to investigate the effects of reinforcement pullout resistance including facing connection strength on the behavior of geosynthetic-reinforced soil (GRS) piers under a service load condition. Three different piers were investigated in this study, which simulated different levels of reinforcement pullout resistance. Each pier had two cases with different reinforcement stiffness J and reinforcement spacing Sv but the same ratio of J/Sv. Numerical results showed that reinforcement pullout resistance had a significant effect on the behavior of GRS piers. When the pullout mode prevailed, the case with small Sv and low J had smaller lateral facing displacements and vertical strain of the pier under the same applied pressure as compared to the case with large Sv and high J when the ratio of J/Sv was kept constant. When the pullout mode did not prevail, two cases with the same ratio of J/Sv showed similar performance despite different combinations of Sv and J were used. To more effectively mobilize reinforcement strength and improve GRS pier performance, small reinforcement spacing or high-strength facing connection should be considered when sufficient reinforcement pullout resistance cannot be guaranteed otherwise.

To improve the application-level data efficiency, the scheduling of coflows, defined as a collection of parallel flows sharing the same objective, is prevailing in recent data centers. Meanwhile, optical circuit switches (OCS) are gradually applied to provide high data rate with low power consumption. However, so far few research outputs have covered the flow, let alone the coflow, scheduling in the context of OCS. In this work, we investigate coflow scheduling in OCS-based data centers. We first derive a novel operation called regularization processed respectively on the flow traffic demands and the flow start times, which can be efficiently implemented and reduce the circuit reconfiguration frequency dramatically. We then propose a 2-approximation algorithm, called Reco-Sin , for single coflow scheduling to minimize the coflow completion time (CCT). For multiple coflows, we derive Reco-Mul to minimize the total weighted CCT, which can transform any non-preemptive multi-coflow scheduling in packet switches to a scheduling scheme in OCS. Reco-Mul can achieve a constant approximation under the assumption that no tiny flows will be transmitted in OCS. To get rid of this assumption, we present another multiple coflow scheduling scheme, named Reco-Mul+ , which has an approximation ratio of $O(K)$ . Here, $K$ is the total number of coflows. Extensive simulations based on Facebook data traces show that our approaches outperform state-of-the-art schemes significantly, i.e., one single coflow can be finished up to $1.97\times $ faster with Reco-Sin , and multiple coflows can be completed up to more than $2\times $ faster with Reco-Mul and Reco-Mul+ .

Screened Poisson Surface Reconstruction has a good performance among the state-of-art surface reconstruction algorithms in obtaining a triangle mesh from oriented points. In order to better deal with nonuniform point clouds, Screened Poisson Surface Reconstruction uses B-spline functions with a fixed support for kernel density estimation to construct a vector field for solving the screened Poisson equation. In this paper, an adaptive bandwidth Gaussian kernel density estimator is applied, which reduces the bandwidth where the density is low, and increases the bandwidth where the density is high. Experiments show that such an estimator that makes use of both global and local points distribution can effectively remove noise and outliers in the reconstruction.

Conductive polymer hydrogels (CPHs) hold significant promise in broad applications, such as bioelectronics and energy devices. Hitherto, the development of a facile and scalable synthesis method for CPHs with high electrical conductivity and biocompatibility has still been a challenge. Herein, we demonstrate highly conductive PPy-PEDOT:PSS hybrid hydrogels which are prepared by a simple solution-mixing method. This fabrication method involves the mixing of a pyrrole monomer with a PEDOT:PSS dispersion, followed by in situ chemical oxidative polymerization to form polypyrrole (PPy). The electrostatic interaction between negatively charged PSS and positively charged conjugated PPy facilitates the formation of PPy-PEDOT:PSS hybrid hydrogels. The conductivity of the PPy-PEDOT:PSS hybrid hydrogels is 867 S m-1. The PPy-PEDOT:PSS hybrid hydrogels show excellent biocompatibility. Moreover, the PPy-PEDOT:PSS hybrid hydrogels have a hierarchical porous structure which facilitates the 3D cell culture within the hydrogels. The PPy-PEDOT:PSS hybrid hydrogels exhibit excellent in situ biomolecular detection and real-time cell proliferation monitoring performance, indicating their potential as highly sensitive electrochemical biosensors for bioelectronics applications. Our strategy for the fabrication of CPHs with the electrostatic interaction between the negatively charged conductive polymer and positively charged conductive polymer would provide new opportunities for the design of highly conductive conjugated hydrogels for bioelectronics applications and energy devices.

Label distribution learning (LDL) is a new learning paradigm, which assumes that the labels are related to each instance to some degree. It has been successfully applied in many scenarios due to its ability to tackle label ambiguity. Nevertheless, LDL has also enlarged the labeling costs and difficulties. In many real application areas, such as pattern recognition and image classification, the labeling information is often incomplete, i.e., we cannot determine each label degree to each instance. The performance of traditional LDL algorithm will degrade since they often require complete supervised information. In this paper, we have proposed fragmentary LDL algorithm via Graph Regularized Maximum Entropy criteria (GRME) to solve this problem. It explores the relationship among the labels to recover missing label factors, together with a classifier for categorization. The integration of these two components facilitate the performance enhancement of GRME. Besides, compared with most of traditional methods which are transductive, another advantage of our method is the inductive nature to predict for new coming data directly. We have also extended ADMM algorithm to fit this particular nonconvex problem. The effectiveness of our method is verified by the experimental results on real-world data sets with different settings.

A three-dimensional, non-isothermal, two-phase model for a PEM water electrolysis cell (PEMEC) is established in this study. An effective connection between two-phase transport and performance in the PEMECs is built through coupling the liquid water saturation and temperature in the charge conservation equation. The distributions of liquid water and temperature with different operating (voltage, temperature, inlet velocity) and physical (contact angle, and porosity of anode gas diffusion layer) parameters are examined and discussed in detail. The results show that the water and temperature distributions, which are affected by the operating and physical parameters, have a combined effect on the cell performance. The effects of various parameters on the PEMEC are of interaction and restricted mutually. As the voltage increases, the priority factor caused by the change of inlet water velocity changes from the liquid water saturation increase to the temperature drop in the anode catalyst layer. While the priority influence factor caused by the contact angle and porosity of anode gas diffusion layer is the liquid water saturation. Decreasing the contact angle or/and increasing the porosity can improve the PEMEC performance especially at the high voltage. The results can provide a better understanding of the effect of heat and mass transfer and the foundation for optimization design.

Green roofs are a key measure used to alleviate the urban heat island effect and reduce stagnant water from urban runoff. However, the expensive substrate material and high construction cost restrict the large-scale application of green roofs. Wheat straw (WS) contains abundant nutrients needed for plant growth; however, burning this straw waste causes severe environmental pollution. In this study, six pretreatment methods, including mixed, soaked, hydrothermal, ultrasonic, microwave, and steam explosion, and three liquid media, including deionized water, acetic acid, and wood vinegar, were used to treat WS to improve its properties and decrease its environmental pollution effects. The results showed that, compared to other treatments, physical methods (microwave, ultrasonic) used in conjunction with wood vinegar could effectively break down the particle structure of WS and increase porosity. Most of the crystallinities were reduced by 1.45–6.66% compared to WS when using these methods, and the absolute values of the surface zeta potential were reduced by 4.224.67 mV. Additionally, the contents of macromolecular lignocellulose, which is difficult to decompose, were reduced by 3.6613.75%. Compared with the use of deionized water or acetic acid, wood vinegar reduced the compressive force of the WS substrates and the energy consumption of compression. Hydrophilic groups such as hydroxyl were introduced into the WS to increase the water absorption rate. Overall, the microwave-assisted wood vinegar pretreatment was an effective method for improving the WS properties for use as a potential alternative substrate material in green roof construction.

Recent works in the person re-identification task mainly focus on the model accuracy while ignoring factors related to efficiency, e.g., model size and latency, which are critical for practical application. In this paper, we propose a novel Hierarchical and Efficient Network (HENet) that learns hierarchical global, partial, and recovery features ensemble under the supervision of multiple loss combinations. To further improve the robustness against the irregular occlusion, we propose a new dataset augmentation approach, dubbed random polygon erasing, to random erase the input image’s irregular area imitating the body part missing. We also propose an Efficiency Score (ES) metric to evaluate the model efficiency. Extensive experiments on Market1501, DukeMTMC-ReID, and CUHK03 datasets show the efficiency and superiority of our approach compared with epoch-making methods. We further deploy HENet on a robotic car, and the experimental result demonstrates the effectiveness of our method for robotic navigation.

Metastable β-titanium alloys are attractive for their high strength-to-density ratio, good hardenability, excellent fatigue behavior, and corrosion resistance. Among these alloys, β-21S, with a composition of Ti–15Mo–3Nb–3Al–0.2Si (wt%), is known to offer improved elevated temperature strength, creep resistance, thermal stability, and oxidation resistance. In this study, laser powder bed fusion (PBF-LB) of β-21S and the effect of post-PBF-LB heat treatment were investigated to understand the relationship between the microstructure and the mechanical properties. The as-built (AB) alloy is primarily composed of β-phase, with columnar grains oriented along the build direction. The alloy AB presented a microhardness of 278 HV, a yield strength (YS) of 917 MPa, an ultimate tensile strength (UTS) of 946 MPa, and a ductility of 25.3% at room temperature (RT). Such properties are comparable to β-21S in solution treatment (ST) condition. Solution treatment and aging (STA) of the alloy precipitated the α-phase, increasing the microhardness to 380 HV, YS to 1281 MPa and UTS to 1348 MPa, while reducing the ductility to 6.5% at RT. The STA alloy presented a YS of 827 MPa, UTS of 923 MPa, and a ductility of 7.7%, at 450 °C. The thermal treatment applied to PBF-LB β-21S had a similar effect compared to β-21S fabricated by non-AM techniques. The properties obtained demonstrate that β-21S is a potential candidate for AM.

The gender identification of silkworm pupae is a critical step in the sericulture industry's breeding process. In this study, a low cost, short-wavelength (815-1075 nm) near infrared (NIR) spectrometer combined with multivariate spectra evaluation methods was used to establish calibration models for the on-line identification of female and male pupae of eight silkworm varieties. The diffuse reflection short-wavelength spectra were recorded, and then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were tested for calibration model development. The PCA and LDA results showed, that spectral differences between the female and male silkworm pupae existed, however, the two evaluation techniques could not separate the female and male silkworm pupae with the required accuracy. The PLSDA calibration models, on the other hand, could separate the pupae according to their gender with the necessary prediction accuracy of >98%. Thus, it has been proved, that a low-cost, short-wavelength range NIR spectrometer in combination with a PLSDA calibration routine can be successfully applied for the reliable on-line identification of female and male silkworm pupae.

The effect of the rolling temperature on the room-temperature stretch formability, tensile properties, microstructure, and texture of Mg-4.9Al-0.16Mn (mass%) alloy sheet has been investigated. Rolling at 220°C resulted in the formation of a weakly aligned isotropic texture feature, and the annealed sheet showed splitting of (0001) poles to the rolling direction and broadening of (0001) poles to the transverse direction, leading to an excellent Index Erichsen value of 8.2 mm. The alloy sheet also formed a fine-grained structure with average grain size of ~9 µm, achieving isotropic tensile properties with a moderate 0.2% proof stress of ~ 150 MPa. Quasi-in situ electron backscattered diffraction was employed to study the evolution of the texture, revealing that the suppression of dynamic recrystallization, shear-band-related static recrystallization, and grain growth behavior within the shear bands had a significant impact on the texture weakening.

The visual inspection algorithms are the core of automatic optical inspection system on surface mounting machines. This article is concerned with the development of precise positioning algorithms for circular mark points and transistor (TR) components on surface mounting devices. To handle nonuniform illumination or occlusion of other components, a polar coordinate transform and smoothness selection based circular mark point location method is proposed. The TR components are fundamental chips in electronic products and have various package types. The illumination changes, background disturbance, and the diversity of package types have imposed great challenges on the development of the uniform algorithm for detection and location of TR components. To deal with these issues, the 1-D integral image based TR component detection and location algorithm is proposed and the coordinates and orientation of the component are calculated simultaneously. The efficiency of the proposed methods is tested on real images and compared with classical Hough transform method, commercial algorithms on SMT482 device, and two methods of Halcon software.

High quality Fe4Nb2O9 single crystal was grown by optical floating zone method. The magnetization-temperature(M-T) curves, isothermal magnetization curves(M-H) and pyroelectric current-temperature curves of the single crystal along different crystallographic directions were measured. The results of magnetization measurements which shows the Neel temperature TN of around 90 K and the in-plane magnetic structure of Fe4Nb2O9 are very consistent with the reported magnetic structure obtained by neutron diffraction. The isothermal magnetization curves along [210] direction show spin flop phase transition and a local ferromagnetic loop under 50 K. The critical field HC of spin flop phase transition is found to be 94 kOe. Pyroelectric current-temperature curves show ferroelectric polarization below about 90 K under zero magnetic field, which has not been reported before in single crystal Fe4Nb2O9. At the same time, Fe4Nb2O9 shows magnetoelectric coupling effect. With the increase of magnetic field, the polarization increases to over 300 μC/m2 along a axis under applied magnetic field of 70 kOe.

Analyzing small amplitude of floor vibrations is a new promising means for identifying the types of human activities, e.g., walking around and accidental falls. In this paper, we consider the binary classification problem of floor vibrations for the applications like fall detection. For practical use, there are two main issues of the problem. First, the prediction of the classifier should be fast. Second, the training set is sometimes small and the diversity of negative samples brings extra challenges when the training samples are insufficient. The state-of-the-art methods for time series classification, such as HIVE-COTE and ResNet, are computationally intensive or susceptible to the size of the training set. Therefore, we propose a new feature extraction method based on dynamic mode decomposition (DMD) and high-frequency characteristics, whose time complexity is linear with the size of training set and quadratic with the length of time series. The method is evaluated on the dataset of floor vibrations proposed by Madarshahian et al. (2016). The results show higher accuracy compared to the ResNet classifier and time series forests, especially when the negative training samples are deficient in type.

In this letter, we propose a lightweight yet effective Topology Guided Kinodynamic planner (TGK-Planner) for quadrotor aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, with novel designs to improve the robustness and efficiency in both the pathfinding and trajectory optimization sub-modules. Firstly, we propose the topology guided graph , which roughly captures the topological structure of the environment and guides the state sampling of a sampling-based kinodynamic planner. In this way, we significantly improve the efficiency of finding a safe and dynamically feasible trajectory. Then, we refine the smoothness and continuity of the trajectory in an optimization framework, which incorporates the homotopy constraint to guarantee the safety of the trajectory. The optimization program is formulated as a sequence of quadratic programmings (QPs) and can be iteratively solved in a few milliseconds. Finally, the proposed system is integrated into a fully autonomous quadrotor and validated in various simulated and real-world scenarios. Benchmark comparisons show that our method outperforms state-of-the-art methods with regard to efficiency and trajectory quality. Moreover, we will release our code as an open-source package. 1 1 Code is released at https://github.com/ZJU-FAST-Lab/TGK-Planner .

Coalbed methane (CBM) is not only the material cause of gas explosion and coal‐gas outburst disasters during underground coal mining, but also a kind of clean energy. Coal permeability is an important parameter for CBM drainage. Although many coal permeability models have been developed in the past decades to describe the permeability evolution characteristics under elastic state, few of them could explain the permeability behavior of the mining‐disturbed coal which is often the situation of CBM drainage during underground coal mining. The paper analyzed the mechanical factors affecting the damage‐permeability characteristics of mining‐disturbed coal, proposed the concept of the deviatoric stress ratio (DSR), and then established the statistical damage and permeability evolution models based on DSR. Results show that the deformation and damage of coal is controlled by the deviatoric stress and minimum principal stress. The plastic damage degree of coal mass becomes more serious with DSR increase, which leads to the improvement in permeability. The damage constitutive model was established based on the Weibull distribution function and DSR, and then the permeability model of mining‐disturbed coal was built combining the Kozeny–Carman equation. The acoustic emission (AE) and permeability experiments of the loading and unloading coal sample were conducted. After normalizing and fitting the accumulative AE counts, the damage and permeability evolutions with respect to DSR were found out. The model‐predicted permeability could match with the experiment results, verifying the reliability of the theoretical permeability model. The purpose of this paper is to provide a new approach for modeling damage and permeability of mining‐disturbed coal based on DSR. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd.

The development of efficient and sustainable methodologies for the synthesis of N-heterocycles is a constant focus of organic synthesis. Herein an electrochemical method is reported for the synthesis of benzimidazoles through dehydrogenative cyclization of easily available N-aryl amidines. The reactions were conducted under simple constant current conditions in an undivided cell without need for catalysts, chemical oxidants, or additives, and produced H2 as the only theoretical byproduct.

Transition metal oxides for high-temperature lithium-ion batteries have captivated orchestrated efforts for next-generation high-energy-density anodes. However, due to inherent low tap density, poor conductivity, and structural instability, their poor cyclability capacity and rate performance at elevated temperatures hinder further implementation. Oxygen vacancies (O

Magnesium (Mg) matrix composites have the potential to improve energy efficiency and system performance in aerospace, automobile, mobile electronics and biomedical applications. In this work, a novel graphene nanoplatelets (GNPs) reinforced Mg matrix composites with the bimodal microstructure have been fabricated. The combination of bubbles assisted assembly method, liquid metallurgy process and hot extrusion was developed to smash the agglomeration of nanoplatelets and construct the bimodal microstructure of the Mg/GNPs composites. The theoretical calculation for strengthening mechanisms showed that the enhanced strength of the composites were mainly contributed by the grain refinement effect and the load transfer effect by GNPs. Because of the concave function relationship between the grain size and the corresponding increased yield strength, the bimodal microstructure significantly improved the strengthening efficiency of the composites, which was superior to the composites with uniform refined grains. This behavior demonstrated new possibilities for scientific and technological advantages with architecture design of composites.

Geosynthetic-encased stone column (GESC) has been proven as an effective alternative to reinforcing soft soils. In this paper, a series of centrifuge model tests were conducted to investigate the performance of GESC-supported embankment over soft clay by varying the stiffness of encasement material. The enhancement in the performance of stone columns encased with geosynthetic materials was quantified by comparing the test with ordinary stone columns (OSCs) under identical test conditions. The test results reveal that by encasing stone columns with geosynthetic material, a significant reduction in the ground settlement, relatively faster dissipation of excess pore pressure and enhanced stress concentration ratio was noticed. Moreover, with the increase in the encasement stiffness from 450 kN/m to 3300 kN/m, the stress concentration ratio increased from 4 to 6.5, which signifies the importance of encasement stiffness. In addition, a relatively lower value of soil arching ratio observed for GESCs compared to OSCs indicate the formation of a relatively strong soil arch in the GESC-supported embankment. Interestingly, under embankment loading, GESCs fail by bending while OSCs fail by bulging. The stress reduction method can be used to calculate the settlement of GESC-supported embankment with larger stress reduction factor than that in the OSC-supported embankment. Finally, the limitation of the construction of the embankment at 1 g was addressed.

Geosynthetic reinforced soil embankment are extensively applied in the construction of high-speed railway and highway in mountainous regions but limited field monitoring is conducted on high and steep cases. Aiming to acquire better understanding, a 33-m-high single-tiered wrapped-facing geogrid reinforced soil embankment with the slope of 1 V:0.5H in China was monitored for 2 years during and after construction. Vertical earth pressure, strain of geogrids, horizontal displacement and settlement per layer were recorded and analysed. The results show that the geogrid tensile strains gradually increased during construction. And they were still developing after completion due to creep and subsequent vehicle surcharge load. The predictions of reinforcement loads by the FHWA methods were much higher than the estimated ones from measured strains. The vertical earth pressures linearly grew during construction and then stabilized fast. The horizontal displacement increases with height and the largest value achieved around the top of the slope two years after the construction is 0.14% the total height approximately. The settlement per layer is larger in the lower and middle portion of the embankment and no obvious change is observed over time. This study hopes to serve as a case reference for design and construction of similar reinforcement projects in the future.

Structure’s internal force transfer efficiency is the bases of pursuing the creative structural form. This paper reveals the mechanical mechanisms of the bio-inspired branching structures and further presents a numerical form-finding and shape optimization method for bio-inspired branching structures based on graphic statics with the constraints of strength, stiffness of boundary conditions are considered. Efficient structural form is obtained by connecting the internal force equilibrium and the structural performance in designing process. The reciprocal diagrams in graphic statics are used to solve the form-finding problem to generate compression or tension-only tree-like structure. Establishing the formula of the evaluation criteria of internal force transfer efficiency to characterize the structural performances, the criteria is compared with the continuum topology optimization method, the shape of tree-like structure is optimized by maximizing the structural efficiency under static loads. As a result, suitable external constraints can make a structure efficient and improve the structural redundancy, material properties determine the structural form, which in turn affects the structural behavior. Consequently, the interrelation mechanisms between material-property, structural-form, and structure-performance of the highly efficient bio-inspired branching structures are found. The internal force transfer efficiency and the strength and stiffness of boundary condition are the main factors to determine the optimal solution in the topological design exploration of load-bearing structure, these factors could be controlled to obtain the effective and elegant structural form for practical fabrication. The proposed numerical method could provide intuitive understanding and real-time feedback for the optimal solution, avoid the single solution obtained by the conventional optimization techniques and limited control to modify the output topology. Besides, more structural performance (e.g. buckling, vibration) can be considered in the structural designing process.

The redox cycle of doped CaMnO3-δ has emerged as an attractive way for cost-effective thermochemical energy storage (TCES) at high temperatures in concentrating solar power. The role of dopants is mainly to improve the thermal stability of CaMnO3-δ at high temperatures and the overall TCES density of the material. Herein, Co-doped CaMnO3-δ (CaCoxMn1-xO3-δ, x = 0-0.5) perovskites have been proposed as a promising candidate for TCES materials for the first time. The phase compositions, redox capacities, TCES densities, reaction rates, and redox chemistry of the samples have been explored via experimental analysis and theoretical calculations. The results demonstrate that CaCo0.05Mn0.95O3-δ showed an enhanced redox capacity (1000 °C at pO2 = 10-5 bar) without decomposition and provided the highest TCES density of ∼571 kJ kg-1 reported so far. The effective Co doping tended to increase the valence states of B-site cations in perovskite and facilitate the diffusion of the lattice oxygen atoms into the surface-active oxygen sites. Furthermore, the high cooling rates deteriorated the microstructure of CaCo0.05Mn0.95O3-δ particles and resulted in incomplete heat release, which is instructive to the design and operation of the TCES systems.

This paper proposes a combined milling process of electrical discharge ablation machining (EDAM) and electrochemical machining (ECM) as an alternative to the low efficiency problem of less efficient electrical discharge machining (EDM) and to reduce the recast layer of EDAM. The working medium was a mixed aerosol of NaCl solution and oxygen, which has electrolytic and dielectric characteristics. The mechanism was analyzed: the combined milling process was a mixed process of EDAM, ECM, and EDAM-ECM combined machining. The EDAM-ECM combined machining can be divided into three stages: the electrolysis stage, discharge channel formation stage, and rapid ablative removal stage of metal substrate. Experiments were performed to compare conventional EDM milling, EDAM milling, and combined milling of EDAM and ECM. Results showed that the material removal rate (MRR) of the combined milling was 11.5 times that of EDM milling, and it increased by 18.7% compared with EDAM milling. The relative tool wear ratio (RTWR) decreased by 46.6%, and the thicknesses of the recast layer on the bottom and side were reduced by 61.2% and 49.2%, respectively, compared with EDAM milling.

Pore scale immiscible displacement is crucial in oil industry. The surface roughness of throat is an important factor affecting water–oil interface movement. In this paper, the Navier–Stokes (N-S) equation coupled with the phase-field method is adopted to analyze the oil–water flow and interface movement in single channel, considering different surface roughness, diverse wettability and various capillary numbers. The simulation results show that the resistance increases significantly due to the surface roughness. The velocity of interface movement in rough channels is slower than that in smooth channels. The existence of asperities strengthens the interface deformation and promotes the formation of fingering phenomenon. The water flooding process presents different flow patterns in the rough channel with diverse wettability, and the influence of wall roughness on oil–water interface movement is different under various wettability conditions. There is an approximate exponential relationship between the ratio of interface length to channel length and capillary number. When the capillary number exceeds 0.03574, the phenomenon of viscous fingering is obvious, and the influence of capillary number is amplified by roughness.

Global switching on-the-fly trajectory surface hopping molecular dynamics simulation was performed on the accurate TD-B3LYP/6-31G* potential energy surfaces for E-to-Z and Z-to-E photoisomerization of dMe-OMe-NAIP up to S1(ππ*) excitation. The present TD(DFT) simulation provides accurate calculation for conical intersections between the first-excited and ground states. Thus, simulated quantum yield and lifetime of 0.23 and 620 fs (0.15 and 600 fs) for E-to-Z (Z-to-E) isomerization are in good (relatively good) agreement with experimental observation of 0.25 and 480 fs (0.24 and 430 fs), respectively. Simulated results reveal that photoisomerization pathways are initially uphill to conical intersection zones on the S1 potential energy surface and then downhill to product zones. Three types of representative conical intersections are found for determining photoisomerization mechanisms: one is the rotation type responsible for reactive isomerization and the other two are close to E and Z configurations, respectively, only for nonreactive isomerization. The present conclusions can be held in general for similar large NAIP systems of photoinduced isomerization based on E and Z configurations.

Data collected in modern industrial processes often exhibit complex non-Gaussian and multimodal characteristics. In order to address these problems, a robust mixture probabilistic partial least squares (RMPPLS) model-based soft sensor is developed in this article, where two different kinds of hidden variables are introduced in the formulated model structure. The multivariate Laplace distribution is employed for robust modeling, and mixture form of the probabilistic partial least squares model is adopted for multimodal description. The unknown parameters are estimated in the expectation-maximization (EM) scheme and the corresponding soft sensor is finally constructed. A numerical example and the Tennessee Eastman (TE) process case study are explored to verify the effectiveness of the proposed algorithm.

During the production process of electronic products, the accuracy of chip component placement on printed circuit boards is crucial and directly affects the realization of product functions. This article introduces a rectangular pin part positioning method based on point set registration to obtain the exact position of the chip component during the placement process. The model point set is built from the component’s datasheet. The feature points extracted from the component image are filtered according to the structure feature and the reckon angle to construct a data point set. A rigid point set registration algorithm is used to solve the alignment problem between these two point sets to obtain the offset and rotation angle. Compared with the Halcon algorithm, the Samsung method, and the state-of-the-art method, the positioning results show an advantage.

Enormous data are continuously collected by the structural health monitoring system of civil infrastructures. The structural health monitoring data inevitably involve anomalies caused by sensors, transmission errors, or abnormal structural behaviors. It is important to identify the anomalies and find their origin (e.g. sensor fault or structural damage) to make correct interventions. Moreover, online anomaly identification of the structural health monitoring data is critical for timely structural condition assessment and decision-making. This study proposes an online approach for detecting anomalies of the structural health monitoring data based on the Bayesian dynamic linear model. In particular, Bayesian dynamic linear model, consisting of various components, is implemented to characterize the feature of real-time measurements. Expectation maximization algorithm and Kalman smoother are combined to estimate the Bayesian dynamic linear model parameters and generate log-likelihood functions. The subspace identification method is introduced to overcome the initialization issue of the expectation maximization algorithm. The log-likelihood difference of consecutive time steps is then used to determine thresholds without introducing extra anomaly detectors. The proposed Bayesian dynamic linear model-based approach is first illustrated by the simulation data and then applied to the structural health monitoring data collected from two long-span bridges. The results indicate that the proposed method exhibits good accuracy and high computational efficiency and also allows for reconstructing the strain measurements to replace anomalies.

Separation studies during the past decades have demonstrated that ligands with “soft” donor atoms (e.g., N and S, relative to O) show greater affinity to An(III) over Ln(III) in solvent extraction....

We present a structural and magnetic study on two batches of polycrystalline LiNi$_{0.8}$Mn$_{0.1}$Co$_{0.1}$O$_2$ (commonly known as Li NMC 811), a Ni-rich Li ion battery cathode material, using elemental analysis, X-ray and neutron diffraction, magnetometry, and polarised neutron scattering measurements. We find that the samples, labelled S1 and S2, have the composition Li$_{1-x}$Ni$_{0.9+x-y}$Mn$_y$Co$_{0.1}$O$_2$, with $x = 0.025(2)$, $y = 0.120(2)$ for S1 and $x = 0.002(2)$, $y = 0.094(2)$ for S2, corresponding to different concentrations of magnetic ions and excess Ni$^{2+}$ in the Li$^+$layers. Both samples show a peak in the zero-field cooled (ZFC) dc susceptibility at 8.0(2) K but the temperature at which the ZFC and FC (field-cooled) curves deviate is substantially different: 64(2) K for S1 and 122(2) K for S2. Ac susceptibility measurements show that the transition for S1 shifts with frequency whereas no such shift is observed for S2 within the resolution of our measurements. Our results demonstrate the sample dependence of magnetic properties in Li NMC 811, consistent with previous reports on the parent material LiNiO$_2$. We further establish that a combination of experimental techniques are necessary to accurately determine the chemical composition of next generation battery materials with multiple cations., Revised manuscript, 27 pages main text, 6 figures, 5 pages supplementary material. Accepted for publication in Inorganic Chemistry

In this article, we investigate the stabilization for infinite-dimensional switched linear systems comprising two unstable subsystems. From the algebraic structure of the state space, two switching strategies are designed to stabilize the infinite-dimensional switched linear systems. Under these strategies and suitable assumptions, the systems with time-varying disturbances possess a good robust stability. In addition, we can also obtain an arbitrarily low switching frequency for the switched systems.

Dynamic oscillating behavior of the flexible structure immerged in viscous fluids has attracted growing attention and been widely used in various practical applications. A general electricity-structure-fluid coupled model for the forced dynamic responses of a cantilever immersed in fluids, with partially distributed macro fiber composite, is proposed in this paper. Based on the classical Euler–Bernoulli beam theory, the first mass-normalized mode shape of the cantilever with partially bonded macro fiber composite is determined using assumed mode method. The attachment of the macro fiber composite actuators stiffens the macro fiber composite-bonded portion of the cantilever. The established mode shape matches perfectly with experimental results. Considering the macro fiber composite actuator as a set of representative elements connected in parallel, the internally actuation moment provided by the macro fiber composite actuators is obtained. The hydrodynamic load caused by the surrounding fluids, decomposed into the added mass and hydrodynamic damping parts, is also added to the theoretical model in the frequency-domain form. The predicted in-air and underwater dynamic behaviors of the flexible beam are consistent with the experimental results at different auction levels. Thus, the obtained general electricity-structure-fluid coupled model can be used to predict the forced dynamic responses of flexible structure with partially bonded actuators immersed in fluids.

In recent years, there has been a significant increase in the utilization of Al/SiC particulate composite materials in engineering fields, and the demand for accurate machining of such composite materials has grown accordingly. In this paper, a feed-forward multi-layered artificial neural network (ANN) roughness prediction model, using the Levenberg-Marquardt backpropagation training algorithm, is proposed to investigate the mathematical relationship between cutting parameters and average surface roughness during milling Al/SiC particulate composite materials. Milling experiments were conducted on a computer numerical control (CNC) milling machine with polycrystalline diamond (PCD) tools to acquire data for training the ANN roughness prediction model. Four cutting parameters were considered in these experiments: cutting speed, depth of cut, feed rate, and volume fraction of SiC. These parameters were also used as inputs for the ANN roughness prediction model. The output of the model was the average surface roughness of the machined workpiece. A successfully trained ANN roughness prediction model could predict the corresponding average surface roughness based on given cutting parameters, with a 2.08% mean relative error. Moreover, a roughness control model that could accurately determine the corresponding cutting parameters for a specific desired roughness with a 2.91% mean relative error was developed based on the ANN roughness prediction model. Finally, a more reliable and readable analysis of the influence of each parameter on roughness or the interaction between different parameters was conducted with the help of the ANN prediction model.

International audience; Piezoelectric charge coefficient (d33) and piezoelectric voltage coefficient (g33) are the two most critical parameters that define output performance of piezoelectric nanogenerators (PNGs). Herein, we propose a vacancy-ordered double perovskite of TMCM2SnCl6 (where TMCM is trimethylchloromethylammonium) with a large d33 of 137 pC/N and g33 of 980 × 10–3 V·m/N. The piezoelectric coefficients are considered from the halogen-bonding-mediated synergistic movements of atomic displacement in inorganic [SnCl6]2– octahedrons, as well as the molecular rotation of organic TMCM+, which is revealed by a combined density functional theory (DFT) and experimental study. The TMCM2SnCl6 possesses a high saturated polarization (Ps) of 8.7 μC/cm2, a high Curie temperature (Tc) of 365 K, and a low coercive field (Ec) of 0.6 kV/cm. The output voltage (Voc) and current (Isc) of the PNGs are 81 V and 2 μA at an applied mechanical excitation of (4.9 N, 40 Hz). We hope this work will provide guidance in energy harvesting by innovatively designing highly piezoelectric perovskites for the PNGs.

Energy efficient building projects has become the focus of sustainable development. In this article, 2 indexes, energy-saving sensitivity and energy-saving contribution, are proposed to assess the energy efficiency of residential buildings. Four green measures to improve the energy efficiency of residential building with either passive or active technologies are designed and their saving performances are evaluated with the case study of a residential building simulation model in Changchun, region in China using the 2 indexes by simulations in the Designbuilder simulation software. The results reveal that improving the energy efficiency of residential buildings in severely cold regions should be focused on two key energy consumption factors, A1-heating (gas) and A2-zone sensible heating. Green measures M4-modifying the heating ventilating and air conditioning system and M1-improving envelope structures are found with high energy-saving sensitivities on the energy consumption factors A1 and A2. The energy-saving contribution of green measures M4 is the largest with the value of 80.17%, and that of green measure M2-adding shading facilities is the smallest with the negative value of − 8.53%. These results suggest that M4 and M1 are the effective green energy-saving renovation measures of the residential buildings in severely cold regions. The assessment method and simulation case study results provide a theoretical foundation and practical suggestions for the decision making to effectively reduce the energy consumption of residential buildings in severely cold regions by adopting appropriate green measures.

We thank EPSRC for the research funding under the grant EP/M009521/1 DJR00640, EP/P003532/1. J.L. thanks the EPSRC Underpinning Multi-User Equipment Call (EP/P030467/1) for electron microscopy facilities (SEM, TEM) located in the Department of Chemistry, University of Cambridge. J.L. thanks the Research Startup Fund from Harbin Institute of Technology, Shenzhen. S. D. acknowledges DST-Overseas Visiting Fellowship in Nanoscience and Technology (funded by Govt. of India, 2018-19). Y.J. acknowledges funding support from Faraday Institution NEXGENNA project. The X-ray photoelectron (XPS) data collection was performed at the EPSRC National Facility for XPS ("HarwellXPS"), operated by Cardiff University and UCL, under Contract No. PR16195. The authors thank Tao Liu, Evan Wenbo Zhao, James Ellison, Evelyna Wang for insightful discussions, Zachary Ruff for help with Raman spectroscopy, and Heather Greer for help with the TEM/SEM measurements.

Interaction of [Pb(SiPr)2]n with 1.5 equiv. of AgNO3 in DMF under aerobic conditions at room temperature gave a cationic lead-centered thiolate cluster [Pb13(SiPr)6O8](NO3)4 (1). While treatment of [Pb(SiPr)2]n in refluxing DMF in air afforded a two-dimensional layered structure of [Pb14(SiPr)16O6]n (2), comprising of [Pb14(SiPr)18O6]2− units bridged the iPrS− moieties. Molecular structures of the two oxidation products of μ4-oxygen-bridged high-nuclearity lead(II) clusters have been determined by single-crystal X-ray analysis. The UV/Vis properties of the two clusters in both solid state and solution state were also investigated in this paper.

Highly performance composite material nitrogen-doped mesoporous hollow carbon nanospheres and Ni-Co coordination polymer metal precursor (N-MHCNS700@Ni-Co-MOF) obtained by using hydrothermal reaction Ni-Co coordination polymer metal precursor to assist hollow carbon nanospheres as templates. Then the composite material (N-MHCNS700@Ni-Co-MOF) is calcined under nitrogen to obtain nitrogen-doped mesoporous hollow carbon nanospheres and nickel cobalt metal oxide (N-MHCNS700@NiCo2O4). Material characterization is used to analyze the morphology and structure of the material. The hybrid materials exhibit high specific capacitance (166 mAh g−1 at 1 A g−1) and great cyclic stability (approximately 85.6% retained after 5,000 cycles at 10 A g−1). The composite material also have outstanding power density of composite (624.9 W kg−1) and the energy density (42.8 Wh kg−1). Therefore, composite materials can be applied to electrode materials for high-performance supercapacitor.