Search

Novel dual-ionic imidazolium salts are shown to display excellent catalytic activity for cycloaddition of carbon dioxide and epoxides under room temperature and atmospheric pressure (0.1 MPa) without any solvent and co-catalyst leading to 96.1% product yield. It can be reused five times to keep the product yield over 90%. These intriguing results are attributed to a new reaction mechanism, which is supported by theoretical calculations along with the measurements of 13C NMR spectrum and Fourier transform infrared spectroscopy (FT-IR). The excellent catalytic activity can be traced to a CO2-philic group along with an electrophilic hydrogen atom. Our work shows that incorporation of CO2-philic group is an feasible pathway to develop the new efficient ionic liquids.

Solid–liquid phase change has been widely used in practice, but most of the existing literature focuses on Newtonian phase change materials, and there are few studies on power-law phase change mate...

The application of Si as the anode materials for lithium-ion batteries (LIBs) is still severely hindered by the rapid capacity decay due to the structural damage caused by large volume change (>300%) during cycling. Herein, a three-dimensional (3D) aerogel anode of Si@carbon@graphene (SCG) is rationally constructed via a polydopamine-assisted strategy. Polydopamine is coated on Si nanoparticles to serve as an interface linker to initiate the assembly of Si and graphene oxide, which plays a crucial role in the successful fabrication of SCG aerogels. After annealing the polydopamine is converted into N-doped carbon (N-carbon) coatings to protect Si materials. The dual protection from N-carbon and graphene aerogels synergistically improves the structural stability and electronic conductivity of Si, thereby leading to the significantly improved lithium storage properties. Electrochemical tests show that the SCG with optimized graphene content delivers a high capacity (712 mAh/g at 100 mA/g) and robust cycling stability (402 mAh/g at 1 A/g after 1500 cycles). Furthermore, the full cell using SCG aerogels as anode exhibits a reversible capacity of 187.6 mAh/g after 80 cycles at 0.1 A/g. This work provides a plausible strategy for developing Si anode in LIBs.

Lithium-sulfur (Li-S) batteries are considered as one of the promising next-generation energy storage systems because of their high energy density. While the low utilization of sulfur and sluggish reaction kinetics would lead to degradation of electrochemical performance and thus hinder the practical application of Li-S batteries. Herein, a double-shelled TiO2-graphene heterostructure (H-TiO2/rGO) with abundant oxygen vacancies (OVs) and highly exposed active plane as advanced host material in Li-S batteries is designed. This rational structure not only provides sufficient active sites and lower bandgap for lithium polysulfides (LiPSs), but also builds smooth adsorption-diffusion-conversion of LiPSs on catalyst, which greatly reduces interfacial energy barrier and promotes the utilization of sulfur through suppressing the devastating shuttling effect. Combining the synergetic merits of strong anchoring ability and catalyzing the of LiPSs, the electrode (S-TiO2/rGO-1) exhibits superior rate performance and long lifespan (1000 cycles at 1C, 0.023% capacity loss per cycle) with high columbic efficiency. This work paves an alternative way to establish smooth adsorption-diffusion-conversion of polysulfides on catalyst in Li-S batteries and provides a new sight to understand catalyst design in energy storage devices.

The rational design of oxygen vacancies and electronic microstructures of electrode materials for energy storage devices still remains a challenge. Herein, we synthesize nickel cobalt-based oxides nanoflower arrays assembled with nanowires grown on Ni foam via the hydrothermal process followed annealing process in air and argon atmospheres respectively. It is found that the annealing atmosphere has a vital influence on the oxygen vacancies and electronic microstructures of resulting NiCo2O4 (NCO-Air) and CoNiO2 (NCO-Ar) products, which NCO-Ar has more oxygen vacancies and larger specific surface area of 163.48 m2/g. The density functional theory calculation reveals that more oxygen vacancies can provide more electrons to adsorb -OH free anions resulting in superior electrochemical energy storage performance. Therefore, the assembled asymmetric supercapacitor of NCO-Ar//active carbon delivers an excellent energy density of 112.52 Wh/kg at a power density of 558.73 W/kg and the fabricated NCO-Ar//Zn battery presents the specific capacity of 180.20 mAh/g and energy density of 308.14 Wh/kg. The experimental measurement and theoretical calculation not only provide a facile strategy to construct flower-like mesoporous architectures with massive oxygen vacancies, but also demonstrate that NCO-Ar is an ideal electrode material for the next generation of energy storage devices.

The development of high-performance form stable phase change materials (FSPCMs) with higher optical absorbance and phase change enthalpy is of great significance to building energy conservation. A kind of Ti3C2/pectin aerogels was prepared by self-assembly of pectin and MXene nanosheet (Ti3C2) by solution blending method. These aerogels were directly dipped in the molten dodecylamine (DDA) as the phase change material. The results show that the PCM composites with 3 wt% Ti3C2 have a phase change temperature of 25.47 °C (at which the human body feels comfortable), latent heat of phase change of 218.8 kJ kg−1, and thermal conductivity of 0.1817 W/(m K). The prepared FSPCMs have the characteristics of suitable phase change temperature, high latent heat, good melting/freezing cycle reliability, strong mechanical properties, significant photothermal energy conversion capacity (more than 92%), and good thermal insulation performance. Therefore, the corresponding pectin-based composites with better light absorption and mechanical properties are expected to have broad application prospects in energy conversion and building energy conservation.

Rock engineering is highly susceptible to cyclic loads resulting from earthquakes, quarrying or rockbursts. Acquiring the fatigue properties and failure mechanism of rocks is pivotal for long-term stability assessment of rock engineering structures. So far, significant progress has been gained on the mechanical characteristics of rocks subjected to cyclic loading. For providing a global insight of typical results and main features of rocks under cyclic loading conditions, this study comprehensively reviews the state-of-the-art of deformation and failure mechanism and fatigue constitutive relationship of rocks subjected to cyclic loading in the past 60 years. Firstly, cyclic tests on rocks are classified into different types based on loading paths, loading parameters, loading types and environment conditions. Secondly, representative results are summarized and highlighted in terms of the fatigue response of rocks, including the deformation degradation, energy dissipation, damage evolution and failure characteristics; both laboratory testing and numerical results are presented, and various measurement techniques such as X-ray micro-computed tomography (micro-CT) and digital image correlation (DIC) are considered. Thirdly, the influences of cyclic loads on the mechanical characteristics of rocks are discussed, including the cyclic stress, frequency, amplitude and waveform. Subsequently, constitutive relationships for rocks subjected to cyclic loading are outlined, in which typical fatigue constitutive models are compared and analyzed, regarding the elastoplastic model, the internal variable model, the energy-based damage model and the discrete element-based model. Finally, some ambiguous questions and prospective research are interpreted and discussed.

Semi-competing risks data, including probably correlated non-terminal event and terminal event times, are frequently encountered in medical research. Work on semi-competing risks data has mainly focused on the situations without or only with low-dimensional covariates. However, high and ultra-high dimensional data have been very common in modern scientific research. In this article, we propose a model-free feature screening procedure for ultra-high dimensional semi-competing risks data to discover features contributing separately or jointly to non-terminal and terminal event times via Kolmogorov–Smirnov statistics. This new approach could be used for contexts with discrete, categorical and continuous covariates, which is achieved through the technique of slice-and-fuse. It enjoys several desirable advantages inherited in the Kolmogorov–Smirnov statistics. Under rather mild conditions, we show that the newly suggested method possesses sure screening property. Monte-Carlo simulation studies are conducted to investigate the finite sample properties of our proposed procedure and make comparisons with existing methods, while a real data example is also offered for illustration.

For the first time, a group of CaB6-typed cubic rare earth high-entropy hexaborides have been successfully fabricated into dense bulk pellets (>98.5 % in relative densities). The specimens are prepared from elemental precursors via in-situ metal-boron reactive spark plasma sintering. The sintered bulk pellets are determined to be single-phase without any detectable oxides or other secondary phases. The homogenous elemental distributions have been confirmed at both microscale and nanoscale. The Vickers microhardness are measured to be 16−18 GPa at a standard indentation load of 9.8 N. The nanoindentation hardness and Young’s moduli have been measured to be 19−22 GPa and 190−250 GPa, respectively, by nanoindentation test using a maximum load of 500 mN. The material work functions are determined to be 3.7–4.0 eV by ultraviolet photoelectron spectroscopy characterizations, which are significantly higher than that of LaB6.

In theory, the industrial agglomeration is a double-edged sword as there are both positive and negative externalities. China’s cities, with great disparities on degrees of the industrial agglomeration, often face different energy and carbon dioxide emission problems, which raise the question whether the industrial agglomeration promotes or inhibits energy efficiency and carbon dioxide emission. This paper explored the effects of the industrial agglomeration on carbon efficiency in China. Spatial econometric methods were implemented using panel data (2007–2016) of 285 cities above the prefecture level. The results revealed that industrial agglomerations have significant impacts on the urban carbon efficiency with significant spatial spillover effects. The agglomerations of the manufacturing and high-end productive service industries take positive effects on carbon efficiency while the low-end productive and living service industries take negative effects. As a comparison, we found that the agglomeration effects at the level of the megalopolis are greater than those at the national level, especially for the living services industry, in which the higher levels of agglomeration make the effects on carbon efficiency change from negative to positive. The divisions of labor for the central and common cities in the megalopolises are integrated into the industrial agglomeration. Furthermore, the fractional-order grey forecasting model is used in this paper. By the virtue of its advantage in dealing with small sample data which lack statistical rules, this paper makes an out-of-sample prediction of carbon efficiency and industrial agglomeration degree of Chinese cities. By adding the predicted results to the spatial correlation test, new evidence on the spatial correlation of carbon efficiency and spatial division of labor between cities is obtained. Based on the empirical results of the present study, we have proposed some policy recommendations.

In this article, the predictive horizon of model predictive current control (MPCC) is extended for achieving better operational performance. However, the computational burden of MPCC exponentially increases with its predictive steps, and thus, the predictive step is usually chosen as one. In order to explore the potential advantage of multistep MPCC (M-MPCC), one simplified search method is proposed so that the M-MPCC can be executed in practice with greatly reduced complexity. In the proposed search method, a large number of possible voltage vector sequences can be excluded in advance with the guide of the defined reference voltage vector sequence. Then, one simplified M-MPCC is applied to two 3 kW arc induction machines with a large radius, which can make a full demonstration on the drive performance of linear induction machine in practice. The comprehensive simulation and experiments have clearly indicated the relationship between the predictive step and the performance of the proposed M-MPCC. It has persuasively verified the feasibility of low complexity and decreasing time consumption based on the proposed search method in this work.

The brushless doubly-fed induction generator (BDFIG) in standalone mode is sensitive to unusual working situations, particularly unbalanced and nonlinear loads. The unbalanced and nonlinear loads can cause significant unbalance and distortion for voltage and current of the power winding (PW). In PW voltage under nonlinear and unbalanced loads, the component of negative sequence represents the unbalance influence, and the 5th and 7th harmonics components represent the nonlinear influence. To address these issues, the dual-resonant controller (DRC) is employed to reduce the unbalance and nonlinear influences of PW voltage via generating the reference command of control winding (CW) voltage which compensate the negative sequence component and 5th and 7th harmonic components of PW voltage through the machine side converter (MSC). The experimental and simulation tests are applied to check the effectiveness of the proposed strategy.

The synthesis of carbyne has remained an elusive goal for decades. One of the significant reasons is that high-purity and high-concentration hydrogen end-capped polyynes (C2nH2) as the most important model molecule and precursors for carbyne have been not widely prepared. Herein, we develop a facile and universal strategy to obtain high-purity and high-concentration C8-18H2 molecules using solid linear carbon chains with silver atom ending-capped (Ag2C8-18) as reaction precursors. The purified and concentrated C8-18H2 solution and Ag2C8-18 powder are evaluated by a combination of X-ray photoelectron spectroscopy, nuclear magnetic resonance spectroscopy, Raman spectroscopy, UV–vis–NIR spectroscopy and transmission electron microscope. These results confirm that the high-purity and high-concentration C2nH2 are obtained through the reaction of metal carbides solid and hydrogen chloride molecule. Our strategy for investigating unprotected linear carbon chains in solid and the successful preparation of high-concentration C2nH2 from solid carbides provide a new avenue for the research of linear carbon chains.

Microseismic (MS) event locations are vital aspect of MS monitoring technology used to delineate the damage zone inside the surrounding rock mass. However, complex geological conditions can impose significantly adverse effects on the final location results. To achieve a high-accuracy location in a complex cavern-containing structure, this study develops an MS location method using the fast marching method (FMM) with a second-order difference approach (FMM2). Based on the established velocity model with three-dimensional (3D) discrete grids, the realization of the MS location can be achieved by searching the minimum residual between the theoretical and actual first arrival times. Moreover, based on the calculation results of FMM2, the propagation paths from the MS sources to MS sensors can be obtained using the linear interpolation approach and the Runge–Kutta method. These methods were validated through a series of numerical experiments. In addition, our proposed method was applied to locate the recorded blasting and MS events that occurred during the excavation period of the underground caverns at the Houziyan hydropower station. The location results of the blasting activities show that our method can effectively reduce the location error compared with the results based on the uniform velocity model. Furthermore, the obtained MS location was verified through the occurrence of shotcrete fractures and spalling, and the monitoring results of the in-situ multipoint extensometer. Our proposed method can offer a more accurate rock fracture location and facilitate the delineation of damage zones inside the surrounding rock mass.

Bilayer graphene (BLG) grown via chemical vapor deposition (CVD) tends to exhibit twisted stacking. The twist angle θ t in twisted BLG (tBLG) provides a new degree of freedom for engineering its electronic and optical properties. In this paper, we investigate the θ t-dependent optical absorption in tBLG and deeply understand the electronic structure-optical properties correlations. New absorption peaks, whose wavelengths are modified by θ t, are observed on the feature of optical contrast (OC) in tBLG. Under the corresponding energy excitation, the Raman G mode in tBLG exhibits a significant enhancement. Furthermore, the results of θ t obtained by OC absorption peak are verified to be consistent with those by the Raman R mode. All these properties are proved to be related to the energy difference between low-energy Van Hove singularities (E VHS) in the density of states of tBLGs. This work builds a relation between optical absorption and twist angle, providing a viable method to identifying twist angles in tBLGs.

Structural reforms are currently the key way to achieve emissions reduction targets. A comprehensive investigation of the relationship between structural changes and carbon emissions is essential for further policy formulation. This paper aimed to discuss the impact of structural changes on per capita carbon emissions from the four aspects of energy, trade, society and economy, while considering the effects of economic growth and energy intensity. The ordinary least squares, fully modified ordinary least squares regression analysis and Granger causality test were used to analyze the situation of 147 countries and four income groups from 1990 to 2015. The results showed that at the global level, economic growth and economic structure were respectively the most significant positive and negative factors affecting carbon emissions. There was the bidirectional granger causality relationship between global per capita carbon emissions and economic growth, and between global per capita carbon emissions and economic structure. At the income group level, consistent with the global results, economic growth and energy intensity increase promoted the increase in carbon emissions, whereas increasing renewable energy consumption helped to reduce carbon emissions. The influence direction and degree of the remaining three factors differed among different income groups. In addition, the causal relationships among the variables of the income groups except the low income group were relatively complicated. Finally, policy recommendations were offered to reduce per-capita carbon emission through adjusting economic, energy, social, and trade structure.

Understanding the inconsistent rock fracture toughness (KIc) measurement results from different test specimen geometries helps provide suitable fracture parameters for engineering applications, predict rock fracture load, and assess the safety of flawed rock engineering structures. In this study, fracture experiments using full- or half-disc specimens with chevron notches or straight-through notches were conducted. Experimental results show that the notch types and loading methods (Brazilian-type diametric compression and three-point bending) significantly affect the KIc measurements. It is indicated that only considering the T-stress or fracture process zone (FPZ) alone cannot explain the test results well, while a good agreement is found between the experimental results and the interpretation based on the combined effects of T-stress and FPZ. Moreover, Brazilian-type compression and three-point bending under a short support span can make the full- or half-disc specimens have higher negative T-stress and larger FPZ, thus producing lower KIc values than three-point bending under a relatively long support span. Compared with KIc measurements using the straight-through notch specimens, those utilizing the chevron-notched ones are less affected by FPZ and yield higher KIc results, providing that the loading method is the same. The notch types have little impact on the T-stresses of the specimens. This study sheds light on the combined influence of T-stress and FPZ on rock fracturing.

PurposeThis study is aimed at better understanding the evolution of inequality in carbon emission in intraincome and interincome groups in the world, and then to uncover the driving factors that affect inequality in carbon emission.Design/methodology/approachThe approach is developed by combining the Theil index and the decomposition technique. Specifically, the Theil index is used to measure the inequality in carbon emissions from the perspective of global and each income group level. The extended logarithmic mean Divisia index was developed to explore the driving factors.FindingsThis study finds that the inequality in carbon emissions of intraincome group is getting better, whereas the inequality in carbon emission of interincome group is getting worse. And the difference in global carbon emissions between income groups is the main source of global carbon emission inequality, which is greater than that within each income group. In addition, the high-income group has transferred their carbon emissions to upper-middle income group by importing high-carbon-intensive products to meet the domestic demand, while lower-middle-income group do not fully participate in the international trade.Practical implicationsTo alleviate the global carbon inequality, more attention should be paid to the inequality in carbon emission of interincome group, especially the trade between high-income group and upper-middle income group. From the perspective of driving factors, the impact of import and export trade dependence on the per capita carbon emissions of different income groups can almost offset each other, so the trade surplus effect should be the focus of each group.Originality/valueIn order to consider the impact of international trade, this study conducts a comprehensive analysis of global carbon emissions inequality from the perspective of income levels and introduces the import and export dependence effect and the trade surplus effect into the analysis framework of global carbon emission inequality drivers, which has not been any research carried out so far. The results of this paper not only provide policy recommendations for mitigating global carbon emissions but also provide a new research perspective for subsequent inequality research.

This paper provides the dynamic model of an angular-contact ball bearing–elastic rotor system to study its dynamic characteristics when an asymmetric support mode is used. After defining global and local coordinate systems, necessary vectors (such as position, velocity, force and moment vector) are calculated according to the geometric relationship between each part (ball, cage and ring) of the bearing. The interactive forces between each part are obtained based on lubrication theory and Hertz contact theory. A typical rotor is discretized by finite element method (FEM) and each node of the rotor has 5 degrees of freedom (DOFs). Some constraint equations are built to form a coupled dynamic model of angular-contact ball bearing–elastic rotor system. The validity of this coupled model is verified by comparing the numerical results and experimental data. After analyzing the coupled model, it is found that the vibration spectrum of rotor includes the VC (varying compliance) frequencies of two bearings, the bending resonance frequency of rotor and the rotating frequency when the system has asymmetric ball bearings. Moreover, when the preloading forces of bearings increase, the support stiffness becomes larger and the rotor displacement decreases; moreover, the motions of balls and cage become more stable. Generally, the presented coupled model can be applied to analyze the vibration features of all parts in any ball bearing–rotor system comprehensively.

The unique metal to insulator transition (MIT) of vanadium dioxide (VO2) makes it receiving extensive attention in the application of smart window. As for VO2-based smart window, the critical transition temperature (Tc) is required to be reduced to near room temperature for practical applications. In this paper, we fabricated VO2 films on ITO glass by hydrothermal method and applied voltage to ITO, therefore, the joule heat generated by ITO triggered the complete MIT of VO2 at room temperature in very short time ~3 s with applied voltage of 12 V. The VO2 film on ITO substrate shows obviously widened hysteresis behavior in the reversible transition process with a thermal hysteresis width of ~33 °C. The widened hysteresis loop makes it possible to stabilize the rutile phase (R) of VO2 at room temperature via applying a low holding voltage of 6 V. The proposed VO2/ITO film exhibits promising application in active smart window, and possesses advantages of simple structure, easy-fabricated and low-cost.

Due to air quality significantly affects human health, it is becoming increasingly important to accurately and timely predict the Air Quality Index (AQI). To this end, this paper proposes a new federated learning-based aerial-ground air quality sensing framework for fine-grained 3D air quality monitoring and forecasting. Specifically, in the air, this framework leverages a light-weight Dense-MobileNet model to achieve energy-efficient end-to-end learning from haze features of haze images taken by Unmanned Aerial Vehicles (UAVs) for predicting AQI scale distribution. Furthermore, the Federated Learning Framework not only allows various organizations or institutions to collaboratively learn a well-trained global model to monitor AQI without compromising privacy, but also expands the scope of UAV swarms monitoring. For ground sensing systems, we propose a Graph Convolutional neural network-based Long Short-Term Memory (GC-LSTM) model to achieve accurate, real-time and future AQI inference. The GC-LSTM model utilizes the topological structure of the ground monitoring station to capture the spatio-temporal correlation of historical observation data, which helps the aerial-ground sensing system to achieve accurate AQI inference. Through extensive case studies on a real-world dataset, numerical results show that the proposed framework can achieve accurate and energy-efficient AQI sensing without compromising the privacy of raw data., IEEE Internet of Things

Purpose The purpose of this paper is to study the influence of surface precision on the lubrication state of the roller chain under adequate and rare oil supply conditions, respectively. Design/methodology/approach The straightness error and roughness error of the pin generatrices were measured and the influence of surface precision on the lubrication behavior under steady state and reciprocating motion was studied through optical interference experiments. Findings The lubrication state is strongly influenced by the surface precision of the roller surface both under adequate oil supply and rare oil supply conditions. Originality/value In industrial applications, the machining errors of parts cannot be completely eliminated. Studying the influence of the surface precision on the lubrication behavior of pin–bush pairs can provide the experimental basis for the optimal design of the bush roller chains.

Two kinds of π-conjugated macrocycles with aggregation-induced emission (AIE) properties were investigated by scanning tunneling microscopy (STM) to elucidate their self-assembly behaviors and interaction with C60 on a highly oriented pyrolytic graphite (HOPG) surface. Both TPEMC and TPEMCS could self-assemble into orderly cavity structures. However, C60 guest molecules could only successfully enter the cavity of TPEMC to form a stable TPEMC + C60 host-guest coassembly structure. Density functional theory (DFT) calculations were also used to interpret the assembly mechanisms. This work disclosed the assembly characteristic of these new types of conjugated macrocyclic compounds, which was helpful to develop new structural porous luminescent materials.

Based on the complex network theory, we construct a weighted network evolution model with limited point weight considering node attractiveness and shipping distance. After this the evolution simulation is carried out based on the data of 18 coastal ports mentioned in the Belt and Road Initiative, and the validity of the model is verified by comparing the net-work eigenvalues between evolving network and real network. The results show that the shipping network has the characteristics of small world and scale-free network, and the evolutionary network has shorter average path, stronger agglomeration, greater degree difference, and more frequent and efficient network connection. Based on the evolving network, the position of Lianyungang as a hub needs to be strengthened. For ports with small network values, such as Shantou, Qin-zhou and Sanya, it is necessary to expand trade between ports. Finally, we also provide strategies for improving China’s key coastal port networks from the perspective of port enterprises, shipping enterprises and government.

Utilization of lower dose to generate CT images (LDCT) can reduce X-ray radiation damage to human body, but the resulting noise and artifacts will hinder its applications for clinical diagnosis. In order to solve the difficulty in separating the image artifacts from the normal tissue structure texture, we proposed a GAN network based on frequency division and encoder-dual decoder for LDCT image noise reduction. First, based on the fact that the artifact or noise is mainly distributed to high frequency band, we extracted the high frequency component of the image and used a multi-scale U-Net network for preliminary noise reduction. Second, we designed an encoder-dual decoder artifact extraction sub-network in the backbone noise reduction network. One of the decoders uses the residual structure constrained by confidence loss to perform secondary noise reduction, and the other decoder is used to generate the high-frequency edges and textures of the normal tissue structure, which would be added to the secondary noise reduction results. In addition, a multi-scale inception structure is designed to improve the multi-scale feature extraction and discrimination capabilities of the discriminator. The proposed method performs independent denoising on the high-frequency channel, according to the characteristics of noise and artifacts. In addition, the structure of a double decoder was specially designed to compensate for the component of the normal tissue edge and texture information loss during the denoising process; hence, the noise and artifacts are more targetedly suppressed. The computer experimental results show that, compared with the current popular denoising algorithms, the proposed denoising network can achieve better denoising effects while preserving the important information of CT images.

Displacement is the most intuitive reflection of the structural behaviour of concrete dams, and it is of great significance to predict future displacement for dam health diagnosis. The mathematical models used to predict displacement are mostly established with the only regression objective of minimizing the mean square error between the measured and fitted displacements, whereas the spatial associations between the displacements of multiple monitoring points of an arch dam are ignored. To increase the prediction accuracy of machine learning technique-based mathematical models, a spatial association-coupled support vector machine model is proposed in this article to predict the displacement of high arch dams. This approach is conducted by performing an incremental distance-based spatial clustering for dam displacement field in the first step. The displacement spatial association is quantified by the integrated shape similarity index between the measured time series of multiple monitoring points and is then coupled with the fitting mean square error to optimize the parameters of the support vector machine model. A case study of an engineering example indicates that the prediction accuracy and generalization ability of the proposed double objective support vector machine model have been greatly improved compared to the traditional single objective support vector machine model. For the total 34 plumb line monitoring points on the dam body of the Jinping-I arch dam, when using the hydraulic, seasonal and time- and hydraulic, hysteretic, seasonal and time-based double objective support vector machine models, the prediction accuracy of 25 and 21 monitoring points increases with an average rate of 50.8% and 47.4%, and the degrees of overfitting are evenly reduced by 44.3% and 70.9%, respectively.

In high-speed impact loading experiments, localized deformation is readily taken place, which may result in differences in assessment of strain, strain rate, and further related deformation behaviors of a material in high rate deformations. In this paper, double-notch shear experiments of pure iron specimens were carried out by an improved split Hopkinson pressure bar (SHPB) device with impact speed ranging 16-64 m/s. The development of shear localization and fracture in shear deformation of the specimens was captured by a high-speed camera. Microstructures of localized shear band (LSB) in the shear zone of the specimens at different strain rate were analyzed by metallographic microscope. The nominal strain and strain rate in the deformation zone and the strain and strain rate in LSB were calculated based on the video frames and metallographic photomicrographs. Fracture strains of the shear bands at different impact speed were obtained. Results show that the deformation process of the specimens at different impact speeds includes uniform deformation, localized formation, microscopic crack, and macroscopic fracture; the formation of the LSB results in the decrease of the effective width of the shear band and causes the strain and strain rate to increase rapidly comparing with the nominal strain and strain rate.

With the rapid expansion of the natural gas consumption market worldwide, methanation of coal- or biomass-derived syngas for production of synthetic natural gas (SNG) is gaining considerable interest. In order to solve the problem of natural gas “peak shaving”, adjusting product distribution of the SNG plant is an efficient method to meet the demand fluctuation of natural gas in peak and off season. Herein, the conversion of syngas to SNG (CH4) and co-production of liquid fuels (C5+) over bimetallic Ni-Co catalysts was investigated at industrially relevant conditions. The effects of integration manner of the Ni-Co components, Ni/Co mass ratio, and the operating conditions on the catalytic performance were investigated. Due to the synergistic interaction between Ni and Co, silica supported Ni-Co bimetallic catalyst shows higher activity and total yield of methane and liquid fuels compared to the physically mixed sample. In addition, a good balance between Ni and Co content is crucial for the high efficiency co-production of SNG and liquid fuels. It is found that the optimum operating range in the present study is 550–578 K, H2/CO = 3, 3.0 MPa and W/F = 5 gcat h mol−1, in which more than 80 % total yield of methane and liquid fuels can be obtained on the 2Ni-1Co/SiO2 bimetallic catalyst. Moreover, it shows good thermal stability during the 55 h reaction time. All catalysts were examined by XRD, TEM, H2-TPR and XPS.

Electrocatalytic water splitting is a promising route for the generation of clean hydrogen. However, the anodic oxygen evolution reaction (OER) suffers greatly from low reaction kinetics and thereby hampers the energy efficiency of alkaline water electrolysers. In recent years, tremendous efforts have been dedicated to the pursuit of highly efficient, low cost and stable electrocatalysts for oxygen evolution reaction. Herein, an amorphous FeOOH roughened capillary-liked CoAl layered double hydroxide (LDH) catalyst grown on nickel foam (denoted as FeOOH–CoAl LDH/NF) was reported for OER electrolysis. The developed FeOOH–CoAl LDH/NF electrode shows excellent OER activity with overpotentials of 228 mV and 250 mV to deliver a current density of 50 mA cm−2 and 100 mA cm−2 in 1.0 M KOH solution, respectively, ranking it one of the most promising OER catalysts based on transition-metal-based LDH. This is owed to the formed capillary-liked hierarchy structure with high-porosity as well as the strong electronic interaction between FeOOH and CoAl LDH. The developed morphological engineering approach to build hierarchal porous structures together with facile amorphous FeOOH modification may be extended to other layered double hydroxide catalyst for enhanced OER activities.

In this paper, pinning control and delta operator skills are applied to study couple-group consensus for heterogeneous MASs (multi-agent systems) with switched topology in cooperative-competitive networks. A new couple-group consensus agreement has been designed for this heterogeneous MASs with time delay. On the basis of delta operator and stability theory, couple-group consensus of the continuous or discrete systems can be transformed to analyze stability of a system with time lag. By using stability theory and LMI (Linear matrix inequality) technique, some meaningful results are put forward to obtain couple-group consensus of the heterogeneous MASs. In addition, these conclusions are also suitable for MASs whose switched topologies networks can’t meet the equilibrium of in-degree or can’t meet the requirements of any sub-topology with a spanning tree. In the end, some digital experiments are listed to prove the validity of the obtained achievements.

In order to improve the energy level of fuel air explosive(FAE) with delayed secondary igniters, high energetic metal powders were added to liquid fuels mainly composed of ether and isopropyl nitrate. Metal powders’ explosive properties and reaction mechanisms in FAE were studied by high-speed video, pressure test system, and infrared thermal imager. The results show that compared with pure liquid fuels, the shock wave overpressure, maximum surface fireball temperature and high temperature duration of the mixture were significantly increased after adding high energetic metal powder. The overpressure values of the liquid-solid mixture at all measuring points were higher than that of the pure liquid fuels. And the maximum temperature of the fireball was up to 1700 °C, which was higher than that of the pure liquid fuels. After replacing 30% of aluminum powder with boron or magnesium hydride, the shock wave pressure of the mixture was further increased. The high heat of combustion of boron and the hydrogen released by magnesium hydride could effectively increase the blast effect of the mixture. The improvement of the explosion performance of boron was better than magnesium hydride. It shows that adding high energetic metal powder to liquid fuels can effectively improve the explosion performance of FAE.

A novel sliding-mode-based extended state observer (SMESO) is proposed to improve the disturbance rejection ability and enhance the dynamic performance of permanent magnet synchronous motor drive systems. First, an extended state observer based on the fast terminal sliding-mode control (FTSMC) method is developed for better comparison, which can improve the robustness against load disturbances, finite time convergence, and get effective reduction of the chattering phenomenon. The SMESO-based FTSMC is then developed by using the SMESO to estimate the system total disturbance, and input the signal to a feed-forward compensation controller to further improve the system dynamic performance. The closed-loop stability analysis is conducted by using the Lyapunov stability function. The superior effectiveness of the proposed method is confirmed by comprehensive simulation and experiments.

The electrocatalytic oxygen evolution reaction from H2O (OER) is essential in a number of areas like electrocatalytic hydrogen production from H2O. A Ni oxyhydroxide nanosheet (NiNS) is among the most widely studied OER catalysts but still suffers from low activity, sluggish kinetics, and poor stability. Herein, we incorporate MoO3 patches into NiNS to form a nanosheet with an intimate Ni-Mo interface (NiMoNS) for the OER. The overpotential at 10 mA cm-2 and Tafel slope on NiMoNS (260 mV, 54.7 mV dec-1) are lower than those on NiNS (296 mV, 89.3 mV dec-1), implying that higher activity and faster kinetics are achieved on NiMoNS. There is no change in electrocatalytic efficiency of NiMoNS after 18 h of OER, but the electrocatalytic efficiency of NiNS decreases by 56% after only 8 h of OER. Thus, NiMoNS has better stability. The intimate Ni-Mo interface promotes two-dimensional lateral growth of NiMoNS to form a surface area 1.5 times larger than that of NiNS, and facilitates electron transfer from Ni to Mo. This makes the Ni3+/Ni2+ ratio on the NiMoNS surface (1.32) higher than that on the NiNS surface (0.68). Moreover, the Ni3+/Ni2+ ratio on NiMoNS surface increases to 1.81 after 18 h of OER but the Ni3+/Ni2+ ratio on the NiNS surface decreases to 0.51 after 8 h of OER. Therefore, the NiMoNS surface has more abundant and stable Ni3+ sites which are catalytically active toward OER. This could be the reason for the enhanced activity, kinetics, and stability of NiMoNS. The results are very valuable for fabricating more efficient catalysts for electrocatalysis.

Data protection across organizations is limiting the application of centralized learning (CL) techniques. Federated learning (FL) enables multiple participants to build a learning model without sharing data. Nevertheless, there is very few research works on FL in intelligent manufacturing. This paper presents the results of an empirical study on failure prediction in the production line based on FL. This paper (1) designs Federated Support Vector Machine and federated random forest algorithms for the horizontal FL and vertical FL scenarios, respectively; (2) proposes an experiment process for evaluating the effectiveness between the FL and CL algorithms; (3) finds that the performance of FL and CL are not significantly different on the global testing data, on the random partial testing data, and on the estimated unknown Bosch data, respectively. The fact that the testing data is heterogeneous enhances our findings. Our study reveals that FL can replace CL for failure prediction.

Purpose The purpose of this study is to develop a normal contact stiffness (NCS) model among three disks of the assembled rotor system, which systematically considers the friction coefficient, the asperities interaction and the elastoplastic contact regime. Design/methodology/approach Based on the revised fractal theory, considering the friction effect, the elastoplastic contact regime and the asperities interaction in a simple way, the total NCS among three disks of the rod-fastening rotor bearing system is established. Effects of fractal dimension and roughness, friction coefficient, asperities interaction and material properties on the normal stiffness are investigated by simulations and the relevant comparisons are given for examining the reasonability of the proposed model. Findings NCS will decrease when asperities interaction and friction are included. As the load increases, the influences of asperities interaction and friction on stiffness become serious. NCS will be enhanced when the elastoplastic regime is considered. Originality/value A comprehensive NCS model is developed. It provides a theoretical basis for the modeling of the NCS for multi-interfaces.

In this paper, we simulate the electrical characteristics of the n-type metal-oxide-semiconductor (NMOS) transistor in a 65-nm complementary metal-oxide-semiconductor (CMOS) inverter under the actions of heavy ions with different linear energy transfers (LET). We analyze the influence of incident ions with different LETs on a device using technology computer-aided design (TCAD) software, and aim to establish an HSPICE sub-circuit model containing the relationship between the electrical properties of a device and the LET of an incident ion for circuit-level HSPICE simulation. Based on the SEE funnel mechanism, we propose an analytical model to describe the relationship between the charge collected by the NMOS drain and the LET of the incident ion, and build an HSPICE model based on this analytical model. With such a model, the influence of incident ions with different circuit-level LETs can be determined from HSPICE simulation. In addition, good agreement with simulation results is reached, proving the reasonableness of the proposed model.

As a part of the earthquake ground motion, large velocity pulses are probably one of the important factors leading to serious rock structural damage and geological disasters. It is vitally important to identify the response characteristics of large-scale structures under near-field pulse-like ground motions for earthquake prevention and disaster reduction. In this study, the pulse parameters from the 1999 Chi-Chi and 2018 Hualien earthquakes are extracted using the wavelet transform method, and the potential consequences of velocity pulses on the seismic response of the buildings are assessed. Our results show that the near-field ground motions affected by the directivity effect contain some rich large pulse contents in the velocity time histories. The Chi-Chi earthquake presents a more obvious directivity effect than the Hualien earthquake, and the near-field velocity pulses are closely related to the severely damaged structures. The potential damage of both earthquakes to high-rise buildings can be evaluated by the relationship between the characteristic period of the velocity pulse and the fundamental natural period of the engineering structure. By comparing the periods, it can be revealed that some long-period spectral values in the range of 0.8–3.0 s exceed the seismic design values in the vicinity of the causative faults, and the vulnerability of high-rise buildings against pulse-like ground motions in the Chi-Chi earthquake is stronger than that in the Hualien earthquake. Interestingly, the ratio of peak ground velocity to acceleration (PGV/PGA) and maximum pseudo response velocity (PSV) are suitable as seismic intensity indicators of pulse-like ground motions, which can reflect the rupture direction of source characteristic and site amplification of near-surface soft deposition area around the causative fault. This study provides some references for seismic hazard assessment and post-earthquake structural design.

The adsorption by biochar can effectively alleviate the problem of ammonia inhibition in biogas engineering. Based on batch adsorption experiments, the effect of acid modifier on physicochemical and adsorption NH4+-N properties of biochar was explored, and anaerobic digestion (AD) with addition of modified biochar (MB) was designed and carried out. The results showed that after modification, the adsorption capacity of biochar was significantly improved, and the maximum adsorbance of MB was 1.57 times higher than that of original biochar. Acid modifier had demineralization and increased the number of acidic oxygen-containing functional groups. Chemical adsorption was the dominant adsorption mechanism, mainly including surface electrostatic adsorption and the interaction between ammonium ions and surface functional groups of biochar. With the addition of MB, gas production rate of the AD of chicken manure was increased and the effective gas production period was shortened to 18 days. This research has guidance significance for alleviation ammonia inhibition during the AD by adding MB.

Electrical energy storage (EES) systems consisting of multiple process components and containing intensive amounts of energy present inherent hazards coupled with high operational risks. Although the thermal hazards of batteries have aroused widespread attention, the safety issues of emerging large scale EES technologies persist. This study aims to begin to fill this gap by examining the hazards of typical 100 MWh or more EES systems which are used for grid applications. These systems include compressed and liquid air energy storage, CO2 energy storage, thermal storage in concentrating solar power plants, and Power-to-Gas. Hazard assessments are performed using a hybrid method to consider and evaluate the EES systems’ potential hazards from three novel aspects: storage, operability, and connectivity. Results reveal that for a similar energy storage capacity, cryogenic liquid systems have the least severe accident consequences while thermal energy storage using synthetic oil exhibits the largest. Concerning the operations in many cases, extreme operating conditions, complicated heat exchanger networks involving multiple flammable working fluids, and system operation intermittency present the major challenges to the safer operation of EES systems. Lastly, these systems themselves form one of many components of the power supply, each of which needs to accommodate fluctuations in supply and demand but also should be prevented from transmitting hazards to each other. Considering both engineering and administrative controls, this paper concludes with a discussion on the four grouped strategies from inherent to procedural for the elimination and mitigation of the identified hazards. Representative solutions and research perspectives including inherently safer design, operation uncertainty management, resilience analysis, energy barriers design, and life cycle safety assessment are suggested for the overall safety enhancement of industrial EES systems.

Rationale: Precise treatment of tumors is attracting increasing attention. Molecular probes simultaneously demonstrating the diagnostic signal and pharmacological effect in response to tumor microenvironment are highly desired. γ-glutamyl transpeptidase (GGT) is a biomarker with significantly up-regulated expression in the tumor area. We developed a GGT responsive near-infrared (NIR) nanoassembly for tumor-specific fluorescence imaging-guided photothermal therapy. Methods: The GGT responsive NIR probe was constructed by conjugating GGT-specific substrate γ-glutamic acid (γ-Glu) with cyanine fluorophore (NRh-NH2) via amide reaction. The resulting NRh-G spontaneously assembled into nanoparticles (NRh-G-NPs) around 50 nm. The NPs were characterized and the properties evaluated in the presence or absence of GGT. Subsequently, we studied fluorescence imaging and photothermal therapy of NRh-G-NPs in vitro and in vivo. Results: NRh-G-NPs, upon specific reaction with GGT, turned into NRh-NH2-NPs, showing a ~180-fold fluorescence enhancement and excellent photothermal effect recovery. NRh-G-NPs could selectively light up U87MG tumor cells while their fluorescence was weak in L02 human normal liver cells. The NPs also showed excellent tumor cell ablation upon laser irradiation. After intravenous injection into tumor-bearing mice, NRh-G-NPs could arrive in the tumor area and specifically light up the tumor. Following laser irradiation, the tumor could be completely erased with no tumor reoccurrence for up to 40 days. Conclusions: NRh-G-NPs were specifically responsive to GGT overexpressed in U87MG tumor cells and selectively lit up the tumor for imaging-guided therapy. Besides, the recovery of photothermal property in the tumor area could improve cancer therapy precision and decreased side effects in normal tissues.

Bilateral rehabilitation allows patients with hemiparesis to exploit the cooperative capabilities of both arms to promote the recovery process. Although various approaches have been proposed to facilitate synchronized robot-assisted bilateral movements, few studies have focused on addressing the varying joint stiffness resulting from dynamic motions. This paper presents a novel bilateral rehabilitation system that implements a surface electromyography (sEMG)-based stiffness control to achieve real-time stiffness adjustment based on the user's dynamic motion. An sEMG-driven musculoskeletal model that incorporates the muscle activation and muscular contraction dynamics is developed to provide reference signals for the robot's real-time stiffness control. Preliminary experiments were conducted to evaluate the system performance in tracking accuracy and comfortability, which showed the proposed rehabilitation system with sEMG-based real-time stiffness variation achieved fast adaption to the patient's dynamic movement as well as improving the comfort in robot-assisted bilateral training.

In the modern society, there are a rich number of low-carbon enterprises that the explicitly/implicitly collaborated. Effectively understanding the mechanism of their complex cooperative relationships is becoming an urgent and significant problem in information processing and management. Traditionally, these cooperation behavior are analyzed in a holistic and non-quantitative way, where the complicated relationships among various enterprises cannot be well represented. In this work, we propose to understand the low-carbon entrepreneurs’ cooperation by leveraging a massive-scale dense subgraph mining technique, based on which an evolutionary graphical model is built to dynamically represent such complex relationships. More specifically, given million-scale low-carbon enterprises, we first extract multiple biologically-aware features (e.g., production value and carbon emission) to represent each of them. Based on this, a massive-scale affinity network is constructed to characterize the relationships among these enterprises. Based on this, an efficient subgraph mining algorithm (called graph shift) is deployed to discover the neighbors for each enterprise. Finally, based on the discovered neighbors of each enterprise, we can build a graphical model to represent the relationships among explicitly/implicitly-connected enterprises. The flows of multiple attributes (benefit exchange and resources swap) can be modeled effectively. To demonstrate the usefulness of our method, we manually label the attributes of 20,000 enterprises, based on which a classification model is trained by encoding the neighboring attributes of each enterprise. Comparative results have clearly demonstrated the competitiveness of our method. Moreover, visualization results can reveal the effectiveness of our method in uncovering the intrinsic distributions/correlations of million-scale enterprises.

Transition-metal sulfides (TMSs) were demonstrated to be heartening anodes for sodium-ion batteries (SIBs) because of their alterable nanostructures, large theoretical capacity and environmental friendliness. Whereas, the relatively poor rate and cycling capability of TMSs still hinder the rapid development of their practical applications. Herein, a novel CuS nanocable self-assembled by hierarchical nanosheet is designed as SIB anodes, which delivers a large capacity (367 mAh g−1 at 5 A g−1), excellent rate capacity and cycle performance (213 mAh g−1 after 2000 cycles at 15 A g−1). The uniquely hierarchical nanostructure can both contribute more effective and durable active sites and shorter diffusion length of sodium ions/electrons. Besides, ex situ XRD, HRTEM and SAED reveal the phase transformation during sodiation process and the reaction mechanism of as-synthesized CuS nanocables. These results can offer new clues and inspirations to understand the relationship between the designed nanostructures and sodium storage behaviors of other TMSs.

In recent years, building change detection methods have made great progress by introducing deep learning, but they still suffer from the problem of the extracted features not being discriminative enough, resulting in incomplete regions and irregular boundaries. To tackle this problem, we propose a dual-task constrained deep Siamese convolutional network (DTCDSCN) model, which contains three subnetworks: a change detection network and two semantic segmentation networks. DTCDSCN can accomplish both change detection and semantic segmentation at the same time, which can help to learn more discriminative object-level features and obtain a complete change detection map. Furthermore, we introduce a dual attention module (DAM) to exploit the interdependencies between channels and spatial positions, which improves the feature representation. We also improve the focal loss function to suppress the sample imbalance problem. The experimental results obtained with the WHU building data set show that the proposed method is effective for building change detection and achieves state-of-the-art performance in terms of four metrics on the WHU building data set: precision, recall, F1-score, and intersection over union.

The strengthening method of multi-element M-site solid solution is a common approach to improve mechanical properties of MAX phase ceramic. However, the research on capability of multi-element A-site solid solution to improve mechanical properties has rarely been reported. Thereupon, quasi-high-entropy MAX phase ceramic bulks of Ti2(Al1−xAx)C and Ti3(Al1−xAx)C2 (A = Ga, In, Sn, x = 0.2, 0.3, 0.4) were successfully synthesized by in situ vacuum hot pressing via multi-elements solid solution. The multi-elements solid solution in single-atom thick A layer was confirmed by X-ray diffraction and X-ray photoelectron spectroscopy as well as by energy dispersive X-ray spectroscopy mappings. Effects of doped multi-elements contents on the phase, microstructure, mechanical properties, and high temperature tribological behaviors were studied. Results demonstrated that the Vickers hardness, anisotropic flexural strength, fracture toughness, and tribological properties of Ti–Al–C based MAX ceramics could be remarkably improved by constitution of quasi-high-entropy MAX phase in A layers. Moreover, the strengthening and wear mechanisms were also discussed in detail. This method of multi-element solid solution at A-site provides new way to enhance mechanical properties of other MAX phase ceramics.

The effect of granular activated carbon (GAC) on batch dry anaerobic digestion of swine manure was studied under different temperatures and ammonia concentrations. At 20 °C, 35 °C and 55 °C, the digester was inhibited when the initial total ammonia nitrogen (TAN) concentration reached 2500, 3500 and 3500 mg/L, respectively. The degradation of protein at 20 °C decreased as ammonia concentration increased, but the process was little effected by ammonia at 35 °C and 55 °C. Results showed that when the initial TAN increased from 500 to 3500 mg/L, the TAN produced at 20 °C decreased by 526 mg/L, but it only decreased by 20 and 145 mg/L at 35 °C and 55 °C, respectively. Adding GAC improved the methane production rate by 8.4%–45.6%. Under adverse condition (20 °C and TAN = 3500 mg/L), GAC has the most positive effect on methane production. In which the maximum methane potential and maximum methane production rate increased by 38.8%, 34.1% respectively, the lag time shortened by 23.1%. The dominant bacteria at 20 °C and 35 °C were Tricibacter, Terrisporobacter and Clostridium_sensu_stricto_1, and Methanosaeta was the dominant archaea. At 55 °C, the dominant bacteria were Hydrogenispora and Ruminiclostridium_1, and the dominant archaea were Methanosaeta, Methanosarcina and Methanoculleus.

Inhibition of protein fibrillation process with nanomaterials is a promising strategy to combat neurodegenerative diseases. Copper-based nanomaterials have been seldom utilized in fibrillation inhibiting research due to Copper ions are generally considered as accelerators of fibrosis. Here, we proposed ultra-small Zn doped Cu2S (Zn:Cu2S) QDs as inhibitors of human insulin (HI) fibrosis. ThT, DLS, CD and TEM confirm that Zn:Cu2S QDs effectively inhibited insulin fibrosis in a dose-dependent manner with lag phase time extended (beyond 13-time by Zn:Cu2S QDs of 1 mg·mL−1), final fibril formation and the conversion from α-helix to β-sheet reduced. Additionally, thermodynamics analyzed results reveal that the HI fluorescence quenching process is static quenching dominated, and the Zn:Cu2S QDs inhibit HI fibrosis mainly through specific electrostatic interaction with oligomers. The positively charged amino acid residues of oligomers bind to the negatively charged Zn:Cu2S QDs, which prevents the self-assembly of the oligomers from growing into mature fibers to enhance the stability of the protein. Unlike free Copper ions, the as-prepared QDs show an excellent inhibition in HI fibrillation, breaking through the bottleneck of copper-based materials in inhibiting protein fibrosis and providing a potential strategy to inhibit protein fibrosis in-situ by biosynthesizing copper-based fibrosis inhibitors.

There continues to be debate regarding the timing of the collision between the Indian and Eurasian plates and the uplift of the Tibetan Plateau. This study presents zircon U–Pb geochronology, whole-rock geochemistry, and Lu–Hf isotopic data for the Saiduopugangri granite of the Qiangtang Terrane, located within the core of the Tibetan Plateau. These data provide the basis for the geodynamic setting, petrogenesis, and characteristics of its magma source. Zircons from the Saiduopugangri granite yield a weighted-mean 206Pb/238U age of 62.72 ± 0.06 Ma, indicating that these rocks formed during the early Palaeocene. The rocks are members of the highly calc-alkaline to shoshonitic series, with weak peraluminous characteristics. Trace elements are characterised by high Sr (483–616 ppm), and low Y (6–10 ppm) and Yb (1 ppm) content, typical of a high Sr and low Yb granite. The εHf(t) of zircon ranges from −2.14 to 2.35, with two-stage Hf model ages (TDM2) ranging from 1182 to 895 Ma. These data suggest that the Saiduopugangri granite magma was derived from the melting of lower-crustal clastic meta-sedimentary rocks and mantle-derived basalts. The high Sr and low Yb granite characteristics and experimental results indicate that melting occurred at >1.2 GPa and >750 °C, consistent with a crustal thickness greater than 50 km. Magmatism occurred from the Late Cretaceous to the early Palaeogene and is broadly synchronous with the collision timing between the Indian and Eurasian plates. The Saiduopugangri granite provides evidence of crustal thickening of the Tibetan Plateau and its age and petrogenesis constrain the timing of the initial uplift.

The development of Ni-based single crystal superalloys relies heavily on the composition design with the addition of critical alloying elements, e.g., Re and Ru. Understanding the role of alloying effects require to know the configurations of the alloying element distribution between γ-Ni and γ′-Ni3Al phases and among various non-equivalent sites. This work employed first-principles density functional theory calculations to study the preference of phase and site occupancy of 11 alloying elements including Al and transition metal elements: 3d (Ti, Cr, Co, Ni), 4d (Mo, Ru), and 5d (Hf, Ta, W, Re) in Ni and Ni3Al. We calculated the substitution energies of 1298 triple-site doping configurations including 286 NiNiNi site doping of Ni, 726 AlNiNi site doping, and 286 NiNiNi site doping of Ni3Al with alloying elements Ni, Co, Ru, Cr, Re, Mo, W, Al, Ti, Ta, and Hf. In the dual-site and triple-site doping of Ni and Ni3Al, all studied alloying elements preferred to occupy Ni phase rather than Ni3Al phase. We found that the most stable defect complexes often contained the favorable substitutions of Al, Ti, Ta, and Hf for the Ni sites that stabilized the alloying elements doping at the other one or two nearest neighbor sites. The co-substitutions of various alloying elements at multiple sites are critical to understanding the strengthening mechanism of alloying elements in Ni-based single crystal superalloys.

Interval-valued intuitionistic fuzzy set (IVIFS) is a potent tool to capture the vagueness and uncertainty of information. Archimedean copula and co-copula (ACC) are crucial implement utilized to generate operational rules of interval-valued intuitionistic fuzzy numbers (IVIFNs). Meanwhile, Bonferroni mean (BM) has a distinct merit that it can take into consideration the interconnection of diverse attributes. In the paper, generalized BM operators based on ACC are utilized to aggregate IVIFNs. Firstly, several novel operational rules based on ACC are proposed. Secondly, the interval-valued intuitionistic fuzzy copula BM (IVIFCBM) operator and the interval-valued intuitionistic fuzzy weighted copula BM (IVIFWCBM) operator are propounded. Moreover, several desired properties and particular instances of these operators are investigated in detail. Thirdly, a new methodology based upon the IVIFWCBM operator is presented to tackle multi-attribute decision making (MADM) problems under interval-valued intuitionistic fuzzy context. Ultimately, the efficacy of the proposed approach is substantiated through an empirical example and a comparison is implemented to display the predominance of the approach.