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Ultraviolet (UV) detector based on β-Ga2O3/p-GaN was fabricated in this paper. The growth process involved deposition of amorphous Ga2O3 layer by means of magnetron sputtering and conversion of β-Ga2O3. The obtained detector displays excellent UV sensing properties which covers Ultraviolet A(UVA)/Ultraviolet C(UVC) region with fast response. It will provide a new route to fabricate β-Ga2O3/p-GaN heterostructure for applications in broadband ultraviolet sensing.

The combination of graphene oxide (GO) and iron oxide (Fe2O3) may induce property enforcement and application extension. Herein, GO/Fe2O3 nanocomposites were synthesized via the vacuum-freeze-drying method and used for the thermal decomposition of ammonium perchlorate (AP). A series of characterization techniques were applied to elucidate the as-obtained nanomaterial's physicochemical properties. These results show that the treated GO is consistent with the pristine GO after the freeze-drying treatment. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) analyses show that iron oxide nanoparticles are anchored on and between the GO sheets. The catalytical effect investigation on AP with different Fe2O3: GO ratios indicates that the high-temperature decomposition temperature of AP could be decreased by a temperature as high as 77 °C compared to pure AP accompanied by 3 wt % GO/Fe2O3 nanocomposite which proves the high catalytic performance of the nanocomposites. The first-principles calculation was employed to elaborate the synergistic effect, and the findings demonstrate that the presence of graphene in the catalyst can enhance the catalytic effect via reducing the activation energy barrier by ∼17% in the reaction of AP thermal decomposition.

Powder bed fusion (PBF) process is expeditely moving towards its maturity for the direct manufacturing of intricated and sophisticated metallic parts. The typical process is instead complex and yet challenging to interpret experimentally. Modeling and simulation strategy has been widely implemented to comprehend and optimize the process. Therefore, an integrated simulation approach incorporating stochastic powder deposition and subsequently selective melting is developed to understand the consolidation mechanism in a multilayer process of electron beam PBF additive manufacturing. Simulation results of a thin-walled cross section are validated with the published experimental data to demonstrate the effectiveness of the proposed model. The simulation results of the multilayer process revealed that the layer thickness keeps on slight changes until reaching a steady state during the multilayer additive process. The stable powder layer thickness is systematically analyzed, which proved that the influence of the wall effect should be considered in smaller nominal layer thickness and denser powder bed. Finally, the printing quality in the multilayer process is dependent on adequate inter- and intra-layer bonding when the layer thickness reaches its maximum value, where agglomeration and balling effect in melt pool dynamics predominant by surface tension play crucial roles.

Modeling and simulation in meso-scale have been used to investigate the complicated physics involving powder behaviors during the forming process in electron beam selective melting. But it is difficult to quantitatively predict the forming quality of parts due to the huge calculation amount for multi-layer and multi-pass cases. In this paper, we presented a novel frame for investigating the side surface roughness of fabricated components based on single-track simulation. An integrated model of selective beam melting with considering the random distribution powder particles was developed. The surface morphologies of simulated tracks were used to calculated the surface roughness, and the calculated results were validated by experiment data from independent literature. The effects of heat input were discussed in detail. It reveals that the side roughness increases with a lower heat input. The mechanism behind is the fluctuation of tracks induced by the asymmetry of molten pool, which is related to the coalescence of melting particles and unevenness of powder distribution.

By maintaining high piezoelectric coefficients (d33), increasing the depolarization temperature is the key to constructing high-performance high-temperature piezoceramics. Unfortunately, so far, no piezoceramic has been found that still has a d33 value above 700 pC N−1 by in situ testing at a high-temperature of 400 °C. For popular 0.36BiScO3-0.64PbTiO3 ceramics with a MPB structure, the in situ quasi-static d33 value at 400 °C is only 405 pC N−1. Herein, a new strategy to enhance perovskite lattice distortion to obtain oxides with excellent high-temperature piezoelectricity has been proposed. By introducing Bi(Zn0.5Hf0.5)O3 to enhance lattice distortion of a (1 − x)BiScO3-xPbTiO3 matrix, a ternary system zBiScO3-xPbTiO3-yBi(Zn0.5Hf0.5)O3 (zBS-xPT-yBZH) was designed. A record-high in situ quasi-static d33 value of 726 pC N−1 at 400 °C is achieved in a 0.355BS-0.635PT-0.01BZH composition. Structural analysis confirmed that the introduction of highly tetragonal Bi(Zn0.5Hf0.5)O3 can enhance the lattice distortion and the sample annealed at 400 °C still maintains a stable domain configuration. Moreover, a high-temperature piezoelectric energy harvester is manufactured from the optimal material, and exhibits excellent high-temperature power generation capacity, and a 10 μF commercial electrolytic capacitor can be easily charged to 0.9 V in 40 s at 400 °C. This work demonstrates that zBS-xPT-yBZH ceramics have great potential for application in extreme high temperature environments, and pave the way for obtaining high-quality high-temperature piezoelectric materials.

The self-assembly of plasmonic nanoparticles into highly ordered superlattices could pave the way toward novel nanomaterials for surface-enhanced Raman scattering (SERS). Here, we propose the formation of large-area superlattices of elongated rhombic dodecahedra in a vertical orientation via a controlled droplet evaporation process. Expectedly, the constant humidity of the experimental condition could control the evaporation speed of droplets and this procedure promotes the balance between driven depletion attraction and electrostatic repulsion in the system, leading to the generation of well-organized three-dimensional (3D) superlattices. The unique geometry of elongated rhombic dodecahedra could establish the tetragonal superlattices, which breaks the conventional hexagonal symmetry of gold nanorods. Specifically, the influence of the type and concentration of surfactants, the concentration of nanoparticles, and the amount of droplets on the preparation results were systematically investigated to find the optimal assembly parameters. Remarkably, such close-packed tetragonal arrays of vertically aligned elongated rhombic dodecahedra exhibit more excellent SERS performance compared with the traditional hexagonal superstructure of gold nanorods. Benefiting from the high sensitivity and reproducibility of elongated rhombic dodecahedron superlattices, their applications in the determination of pesticide residues in apple and grape peels were successfully demonstrated. As a result, this study may advance the production of innovative plasmonic nanomaterials for a broad range of fields.

In this article, ultra-broadband photoluminescence in near-infrared is achieved in KZnF3 glass ceramics doped with Er3+and Ni2+ ions. Er3+-Ni2+ co-doped fluorosilicate glass and glass ceramics embedded with perovskite nanocrystals were fabricated and efficient energy transfer (ET) from Er3+ to Ni2+ ions was confirmed by luminescence spectra and decay curves. In the glass ceramic samples, Ni2+ ions were effectively sensitized by Er3+, and ultra-broadband photoluminescence from 1400 to 2300 nm was observed when a 980 nm laser was used as a pump, as shown in Fig. 1. The temperature and humidity stability of the glass ceramic samples was characterized from the measured transmittance. These results demonstrated that Ni2+-Er3+ co-doped glass ceramics have significant potential for application in optical communication and broadband amplifiers.

Location estimation of underwater sensor networks &#x0028 USNs &#x0029 has become a critical technology, due to its fundamental role in the sensing, communication and control of ocean volume. However, the asynchronous clock, security attack and mobility characteristics of underwater environment make localization much more challenging as compared with terrestrial sensor networks. This paper is concerned with a privacy-preserving asynchronous localization issue for USNs. Particularly, a hybrid network architecture that includes surface buoys, anchor nodes, active sensor nodes and ordinary sensor nodes is constructed. Then, an asynchronous localization protocol is provided, through which two privacy-preserving localization algorithms are designed to estimate the locations of active and ordinary sensor nodes. It is worth mentioning that, the proposed localization algorithms reveal disguised positions to the network, while they do not adopt any homomorphic encryption technique. More importantly, they can eliminate the effect of asynchronous clock, i.e., clock skew and offset. The performance analyses for the privacy-preserving asynchronous localization algorithms are also presented. Finally, simulation and experiment results reveal that the proposed localization approach can avoid the leakage of position information, while the location accuracy can be significantly enhanced as compared with the other works.

With the development of cloud computing and the advent of the Web 2.0 era, composing a set of Web services as a service process is becoming a common practice to provide more functional services. However, a service process involves multiple service invocations over the network, which incurs a huge time cost and could become a bottleneck to performance. To accelerate its execution, we propose an engine-side cache-block-based service process caching strategy (CBPCS). It is based on, and derives its advantages from, three key ideas. First, the invocation of Web services embodies semantics, which enables the application of semantic-based caching. Second, cache blocks are identified from a service process, and each block is equipped with a separate cache so that the time overhead of service invocation and caching can be minimized. Third, a replacement strategy is introduced taking into account time and space factors to manage the space allocation for a process with multiple caches. The algorithms and methods used in CBPCS are introduced in detail. Moreover, how CBPCS can be applied to multiple service process models is also investigated. Finally, CBPCS is validated via comparison experiments, which shows the considerable improvements of CBPCS over other strategies.

A new organic–inorganic hybrid, namely [Ni2(en)4(C2H3NO2)(H2O)][Ni(en)3][Ni(en)2][P2W18O62]·6H2O (1, en = 1,2-ethylenediamine), was synthesized hydrothermally by mixing the ligands of 1,2-ethylenediamine and glycine. Notably, compound 1 exhibits the first example of coordination polymer derived from the Wells–Dawson polyoxoanions and di-nuclear nickel(II)-glycine cations. As a result, an intriguing 3D supramolecular architecture was fabricated with the [P2W18O62]6− fragments and the nickel counter-cations via hydrogen bonds. Furthermore, the compound with this unique structure exhibited outstanding electrocatalytic properties in terms of the reduction of iodate and nitrite. This work brings a new inspiration for the design and synthesis of new hybrids with functional behaviors towards various fields of catalysis.

Monitoring the dynamic humidity requires sensors with fast response and anti-electromagnetic interference, especially for human respiration. Here, an ultrafast fiber-optic breath sensor based on the humidity-sensitive characteristics of gelatin film is proposed and experimentally demonstrated. The sensor consists of a microknot resonator superimposed on a Mach-Zehnder (MZ) interferometer produced by a tapered single-mode fiber, which has an ultrafast response (84 ms) and recovery time (29 ms) and a large dynamic transmission range. The humidity in dynamic ambient causes changes in the refractive index of gelatin coating, which could trigger spectral intensity transients that can be explicitly distinguished between the two states. The sensing principle is analyzed using the traditional transfer-matrix analysis method. The influence of coating thickness on the sensor's trigger threshold is further investigated. Experiments on monitoring breath patterns indicate that the proposed breath sensor has high repeatability, reliability, and validity, which enable many other potential applications such as food processing, health monitoring, and other biomedical applications.

Graphene and carbon nanotube (CNT) are representative carbon nanomaterials which have aroused numerous research interest due to their extraordinary material properties and promising application potentials, especially in the energy storage and conversion areas. However, the agglomeration happening in these materials has largely blocked their applications. Hybridization of CNT with graphene can, on one hand, prevent the agglomeration behavior, on the other hand, generate a synergistic effect between them with enhanced physical and chemical properties. There have been many studies conducted to find out the suitable approaches to synthesize graphene/CNT composites, and realize the application potentials of these structures. Based on the recent advances, this paper reviews the current research progress that has been achieved in synthesizing graphene/CNT composites, and the energy-related applications. Through this review, we aim at stimulating more significant research on this subject.

In this paper, we base our research on a fictional collective programming scenario: A group of physically-distributed programmers try to collaboratively solve a programming problem in a web-based development environment, through a continually executing loop, consisting of three concurrent activities: exploration, integration, and feedback. In exploration, a programmer is freely to submit a sequence of gradually improved solutions until achieving a correct one. All programmers’ latest submissions are integrated into a collective artifact through integration. And through feedback, any programmer who hasn’t achieved a correct solution is continuously pushed with personalized feedback information from the collective artifact, to help the programmer improve her/his submission. In order to facilitate the realization of this fictional scenario, we narrow the target problems to those introductory programming problems, design a genetic algorithm to integrate a set of syntax-correct programs into a collective program dependence graph (CPDG), and propose an automatic feedback generation method based on the CPDG and a programmer’s latest submission. The key idea is to generate feedback from mutual inspiration: Any programmer’s submission (even not correct) may possess information that could provide inspiration for others. We evaluate the proposed approach through a set of simulated experiments, as well as a set of real experiments. The results show that our approach has a precision of 90% and a recall of 80% in randomly generated data sets on average, and a precision of 69% and a recall of 77% in real student submissions on average.

Constrained groove pressing (CGP) process is a severe plastic deformation (SPD) method that can create ultrafine-grained microstructure in the sheet metals. In this study, residual stresses of the CGP process and the effect of the friction coefficient on the residual stresses were investigated. The residual stresses were measured in two directions using a multi-cut contour method and a mathematical-finite element model was developed to estimate the uncertainty of results of the multi-cut contour method. In order to study the effect of the friction coefficient on the residual stresses, a 3D finite element model was employed and the results of it were validated with the experimental results of the CGP process. According to the results, residual stresses in the first pass of CGP are compressive on the surface and gradually change to tension at the center of the thickness. Investigation of the effect of the first cut on the residual stresses and uncertainty of the second cutting plane showed that the effect of the first cut is only confined to regions near the intersection of the two cuts. Distancing from the intersection of two cuts causes the effect of the first cut to be ineffective on the second cut. Also, evaluation of the effect of friction coefficient on the residual stress illustrated that friction has a direct relationship with the residual stresses.

Microstructure and mechanical properties of 6061-T6 aluminum alloy/304 stainless steel (Al/steel) joints welded by inertia friction (IFW) and continuous drive friction (CDFW) were studied comparatively. Morphology, microstructure, interfacial composition, and mechanical properties of Al/steel joints were investigated. Results showed that an intermetallic compound (IMC) reaction layer was formed at the welding interface in the CDFWed joint, and wider and clearer than that of the IFWed joint. The high concentration Si was observed at the welding interface. The grain of fully dynamic recrystallized zone (FDRZ) was below 0.1 μm in both joints, and the average width of FDRZ in the IFWed joint and CDFWed joint was about 5 μm and 2 μm, respectively. FDRZ had the high hardness, and the hardness value of IFWed joint was higher than that of CDFWed joint. The maximum tensile strength of IFWed joint was higher than that of CDFWed joint, and the reason should be related to the thickness of IMC at the welding interface.

Electron beam melting (EBM®) is a metallic printing process that has become increasingly sophisticated over the past decade. The formation of residual stress due to a high-energy electron beam is considered a primary hindrance in the maturation of the process itself and, subsequently, the quality of the printed parts. Contrary to hit and trial, the finite element method (FEM) has become a prevalent technique for estimating residual stresses and subsequent distortion in additive manufacturing chunks. Since the EBM® is a powder bed fusion (PBF) process, powder material properties are substantially different from those of solid and undoubtedly important for efficient simulation. Several reviews have been published on FEM applications in additive manufacturing so far; however, a straightforward solution for material modeling from EBM® viewpoint is still needed. This critical review paper is an attempt to propose a material modeling approach to establish an adequate FEM model for EBM® process simulation.

Ho3+ doped and Ho3+/Tm3+ co-doped fluoroindate glass samples were prepared and their emission properties were compared. Under 888 nm laser excitation, the emission at 2 μm of Ho3+ ions with co-doping 2 mol% Tm3+ ions had a 2.9-fold improvement compared with that of Ho3+ doped. The absorption and emission spectra, and energy level lifetime of Ho3+/Tm3+ co-doped glass samples were measured to analyze the energy transfer processes and enhancement mechanisms. The luminescence intensity at 2 μm can be greatly increased due to the bidirectional energy transfer between Tm3+ and Ho3+ ions.

The continuous drive friction welding of aluminum alloy to stainless steel was investigated in this paper. Microstructural characterization, intermetallic compound (IMC), and mechanical properties of the friction welded Al/Fe joint were studied. Results showed that thermal mechanically affected zone (TMAZ) at the Al side was subjected to both thermal cycling and mechanical force, and grain size was 1–3 μm, and streamlines were more dramatically than at the steel side. In fully dynamic recrystallized 127 zone (FDRZ), microstructure became the fine equiaxed grains, and its width at the steel side was about 5 μm. The local Si enrichment IMC layer was formed at the interface area of Al/Fe joint, and its average thickness was about 300 nm. IMC layer was relatively flat at the steel side, while uneven at the Al side. The hardness reached to the maximum value (395.8 HV) at the steel side in FDRZ, and the average hardness was only 76 HV in heat-affected zone (HAZ) at the Al side. When forge pressure was below 220 MPa, the tensile strength of joint was approximately linearly related to the forge pressure.

In this study, the multifunctional carbon nitride based composite graphitic-C3N4 (g-C3N4)/TiO2/Ag was prepared through a simple and efficient vacuum freeze-drying route. TiO2 and Ag nanoparticles were demonstrated to decorate onto the surface of g-C3N4 sheet. In the ultraviolet–visible absorption test, a narrower band gap and red-shift of light absorption edge were observed for g-C3N4/TiO2/Ag compared to pristine g-C3N4 and single-component modified g-C3N4/TiO2. The photodegradation property of g-C3N4/TiO2/Ag was investigated toward the degradation of methylene blue (abbreviated as MB) under the irradiation of visible light. These results indicated that the degradation performance of organic dyes for g-C3N4/TiO2/Ag was obviously improved compared with g-C3N4/TiO2 and g-C3N4. The reaction rate constant of MB degradation for g-C3N4/TiO2/Ag was 4.24 times higher than that of pristine g-C3N4. In addition, such rationally constructed nanocomposite presented evidently enhanced antibacterial performance against the Gram-negative Escherichia coli. Concentration dependent antibacterial performance was systematically investigated. And 84% bacterial cell viability loss had been observed at 500 μg/mL g-C3N4/TiO2/Ag within 2 h visible light irradiation.

peer-reviewed Up-conversion luminescence and C-band microsphere laser output is reported for an Er3+-doped ZrF4-BaF2-YF3-AlF3 (ZBYA) fluorozirconate glass microsphere. The microsphere was fabricated by heating a ZBYA glass filament using a CO2 laser beam. The fabrication process accurately and repeatably produces microspheres of 68 μm diameter. The input and output laser light was coupled to the microsphere using a tapered optical fiber. The coupling position between the tapered fiber and microsphere was adjusted using a sophisticated three-dimensional translation stage. The up-conversion luminescence emission, single-mode and multi-mode laser at C-band (1530 to 1565 nm) were observed when pumped using a 980 nm laser.

Improving the operating characteristics of piezoelectric devices in high temperature environments urgently requires the development of piezoceramics with both high piezoelectric coefficient and excellent temperature stability. However, it is difficult for existing piezoceramics to take care of both at the same time. Generally, high piezoelectricity can be obtained at morphotropic phase boundary (MPB) in the binary systems, such as PbZrO3–PbTiO3 and Pb(Mg1/3Nb2/3)O3–PbTiO3, but the temperature stability is unsatisfactory, which seriously restricts the practical application. Here, an optimum composition having excellent comprehensive properties is constructed by designing multiple MPBs in the novel xPb(In1/2Nb1/2)O3-yBiScO3–zPbTiO3 ternary system. When x = 0.04, y = 0.345 and z = 0.615, the specimen has a high piezoelectric coefficient d33 of 478 pC/N at 200 °C, meanwhile, the fluctuation of d33 is less than ± 10% over an ultra-broad temperature range of 50–350 °C. Combined with a variety of in situ analysis techniques, it can be determined that the temperature-insensitive high piezoelectric coefficient is related to the multiple MPBs design, which is beneficial to the optimization of the hierarchical domain configuration. The developed phase boundary design strategy paves a new way to building next generation high performance high temperature piezoceramics.

Individuals’ decision-making depends on reference points in prospect theory. This research considers the bounded rationality of decision makers and constructs a dynamic hybrid multiple attribute decision-making (DHMADM) model. Unlike existing models, the DHMADM model focuses on dynamic reference point, which has been proven in prospect theory. This research presents the effects of reference point adaptation on decision-making through model calculation. The optimal choice of decision makers changed with the change of the reference point in the DHMADM model. By experiment, we found that the DHMADM model considering reference point adaptation can more accurately express the final choice of decision makers than models only considering the static reference point.

Polyimide microfluidic devices (MFDs) have been attached enormous significance because of its excellent organic-solvent inertness, biocompatibility, and thermal stability. In this paper, a novel fabrication method based on the thought of additive manufacturing, which is adding materials layer by layer from bottom to top, was used to construct a multilayer polyimide MFD. The MFD has sophisticated three-dimensional (3D) microchannels with adjustable cross-sectional geometries and high bonding strength, which leads to good reagent mixing performance, large surface-to-volume ratio, and great durability. Starting from a single polyimide film, ultraviolet (UV) laser was utilized to ablate microchannels on the film. Due to the studies over the influence of UV laser on the channel width, the microchannel edge shape is under control, varying from trapezoid to rectangle. From monolayer to multilayer MFDs, thermal bonding with fluorinated ethylene propylene (FEP) nanoparticle dispersion as the adhesive was adopted to stack polyimide films tightly with precise alignment. In this way, microchannels can be connected vertically between layers to form 3D structures. Besides, a homogeneous adhesive interlayer and polyimide-FEP mixing regime were formed, which can provide high bonding strength. Results of computational fluid dynamics simulation of 3D microchannel structures and organic synthesis experiment revealed that our device has great reagent mixing efficiency and promising application prospects in diverse research fields, especially organic chemical and biological studies.

Fe2O3 short nanorods, nanorods and nanowires were prepared by a facile hydrothermal method by using different flexible ligands (oxalic acid, succinic acid, adipic acid) as templates to adjust the L/D (length/diameter) ratios of the one-dimensional (1D) Fe2O3–nanostructures for the first time. The growth mechanism of Fe2O3 nanorods and nanowires were proposed. Their potential applications as anodes for lithium ion batteries were investigated by electrochemical analysis. This novel straightforward strategy to fabricate 1D metal oxide with different L/D ratios may provide a promising method to make advanced Fe2O3-based nanostructures for Li-ion battery applications.

In modern software development, developers rely on version control systems like Git to collaborate in the branch-based development workflow. One downside of this workflow is the conflicts occurred when merging contributions from different developers: these conflicts are tedious and error-prone to be correctly resolved, reducing the efficiency of collaboration and introducing potential bugs. The situation becomes even worse, with the popularity of refactorings in software development and evolution, because current merging tools (usually based on the text or tree structures of source code) are unaware of refactorings. In this paper, we present IntelliMerge, a graph-based refactoring-aware merging algorithm for Java programs. We explicitly enhance this algorithm's ability in detecting and resolving refactoring-related conflicts. Through the evaluation on 1,070 merge scenarios from 10 popular open-source Java projects, we show that IntelliMerge reduces the number of merge conflicts by 58.90% comparing with GitMerge (the prevalent unstructured merging tool) and 11.84% comparing with jFSTMerge (the state-of-the-art semi-structured merging tool) without sacrificing the auto-merging precision (88.48%) and recall (90.22%). Besides, the evaluation of performance shows that IntelliMerge takes 539 milliseconds to process one merge scenario on the median, which indicates its feasibility in real-world applications.

An efficient and facile strategy for producing core-shell Au@Ag nanorods (NRs) with controllable width and length as excellent surface enhanced Raman scattering (SERS) substrate was proposed. Au nanodipyramids (NDPs) of three various widths were prepared by overgrowth along the radial orientation, and together with Au NDPs as seed, silver was deposited in the axial orientation to successfully obtain core-shell Au@Ag NRs with diverse length (73 nm–157 nm) and width (25 nm–43 nm). The morphology, optical properties and SERS performance of the as-synthesized Au@Ag NRs were investigated systematically. The broadly tunable UV-Vis absorption range for Au@Ag NRs as far as the near-infrared (NR) region was able to be obtained. Furthermore, the SERS property of Au@Ag NRs two-dimensional monolayer was explored by using crystal violet (CV) as Raman probe. The optimal SERS enhancement effect with enhancement factor (EF) as high as 6.13✕105 could be achieved for Au@Ag NRs with wider width and longer length, which was confirmed by the simulation results of electromagnetic (EM) field distribution by FDTD method. Our novel approach provides some facinating insights into adjusting the width of Au@Ag NRs, which also significantly influences the SERS behaviors of the Au@Ag NRs. It allows to fabricating SERS substrate with superior SERS performance compared to previously reported Au@Ag NRs only with tunable length via direct overgrowth. Besides, this as-compounded Au@Ag NRs are expected to have promising application and significant value in other fields.

The Pre-Caspian basin is one of the most prolific in terms of oil and gas exploration and hydrogen and carbon compounds energy production around the world. The major hydrogen and carbon compounds reservoirs are Carboniferous reef and platform hydrogen-carbonate rocks. The original fluids under subsurface conditions contain 15% hydrogen sulfide and 4% carbon dioxide. Acid hydrogen and carbon compounds reinjection is not only an environmentally friendly solution for disposal of produced greenhouse gases but also enhances oil recovery and supplies more fuel energy. On the other hand, the presence of fractures makes hydrogen-carbonate reservoir characteristics nature more complicated than conventional sandstone reservoirs, which leads to a tremendous challenge to evaluate the gas injection process. In this work, a dual-porosity dual-permeability formulation was used to model the dual-medium nature incorporating matrix system with high porosity and low permeability and fracture network with low porosity and high permeability. After matching PVT experiments, a ten pseudo-components fluid model was generated for running compositional simulation. The miscible hydrogen and carbon compounds injection was simulated as an effective enhanced oil recovery approach. Sensitivity analysis such as timing of injection gas, injection rate, well spacing and completion interval have proposed the optimal condition for the miscible hydrogen and carbon compounds flooding. The recommended optimum hydrogen and carbon compounds injection scenario is twice higher oil recovery compared with natural depletion. The results of this study illustrate further the practicability of pseudo-components splitting and lumping for compositional simulation to evaluate the performance of hydrogen and carbon compounds injection processes, and are of great importance using the dual-porosity dual-permeability method performing numerical simulation of naturally fractured hydrogen-carbonate reservoirs.

Mechanical properties of aluminum alloy/stainless steel joint including tensile strength, bending angle, impact toughness, and fatigue property were evaluated, and the effects of friction pressure and rotational speed were also discussed in this work. Results showed that the intermetallic compound (IMC) layer was formed at the bonding interface of the joint, and a thicker IMC layer was observed in the outer region of the joint, and the thickness decreased slightly in the edge region. The thickness of the IMC layer increased with increasing rotational speed. As friction pressure increased, the tensile strength of the joint gradually increased. Joint strength reached to the maximum tensile strength of 323 MPa when the rotational speed and friction pressure were 1100 rpm and 180 MPa, respectively. With the increase of friction pressure, the bending angle of the joint first increased and then decreased. The bending angle reached to 94°, and the welded joint had the excellent bending ductility. The average impact-absorbing energy of joints was 14.47 J, and the maximum fatigue cycle number of joints could reach to 1.25 × 105.

The lead-free (1−x)(0.8Na0.5Bi0.5TiO3-0.2 K0.5Bi0.5TiO3)-xBi(Mg2/3Nb1/3)O3 ceramics were prepared using pressureless solid-state sintering for compositions x ≤ 0.4. At 120 °C, the recoverable energy storage density (Wrec) of x = 0.2 sample reached as high as 0.80 J/cm3 under the electric field of 90 kV/cm, significantly better than the other literature reported Na0.5Bi0.5TiO3 based samples. The fine-grained sample maintained high insulation resistivity (1011 Ω·m order) from 25 °C to 200 °C, which contributes to large breakdown electric field at high temperatures and leads to the excellent energy storage characteristics. This work could broaden the applications of Na0.5Bi0.5TiO3 based materials in building high-temperature multi-layer energy storage capacitor.

This work reports a microsphere laser at ∼2.0 μm in a Tm3+-doped ZrF4-BaF2-YF3-AlF3 (ZBYA) fluoride glass. The ZBYA glass microsphere was fabricated by reflowing the tip of a 1.0 mol% Tm3+-doped ZBYA glass fiber with a CO2 laser. By using a fiber taper for input and output coupling in the Tm3+-doped ZBYA microsphere, single and multi-mode laser outputs at around 2.0 μm were observed under 808 nm laser excitation. The radiation lifetime and emission cross-section of Tm3+ ions in ZBYA glass were calculated to be 6.42 ms and 5.86 × 10−21 cm2, respectively. Our results indicate that the Tm3+-doped ZBYA fluoride glass has potential applications for 2.0 μm lasers.

A new type of electrochemical sensor based on multi-walled carbon nanotubes(MWCNTs), K2H4SiW11CuO39·6H2O(SiW11Cu) and gold nanoparticles(AuNPs) was prepared for the simultaneous detection of bisphenol A and acetaminophen. Differential pulse voltammetry(DPV), cyclic voltammetry(CV) and electrochemical impedance spectroscopy(EIS) were used for electrochemical characterization, and Fourier transform infrared spectroscopy(FTIR) was used to characterize the structure of polyoxometalates. Electrochemical experimental results show that the composite modified electrodes have good electrochemical activity as well as current response values of bisphenol A and acetaminophen when pH=7.0. At the same time, the modified electrode exhibits good stability and reproduction, and has good anti-interference ability to other substances. In practical application, the sensor obtained satisfactory results.

A new type of three-dimensional (3D) serpentine microchannel reactor was fabricated by thermally bonding stacked polyimide films to greatly improve the mixing efficiency by transversal vortices at ...

Localization and tracking are basic services for the applications of autonomous underwater vehicles (AUVs). Although they are closely related, the localization or tracking is usually studied independently. This paper addresses a joint localization and tracking issue for an AUV, subject to asynchronous clocks in physical channel and state disturbances in control channel. We first develop an asynchronous localization algorithm to estimate the position of an AUV, wherein the clocks on AUV and buoys are not required to be synchronized. With the estimated position, a model-free tracking controller is designed for an AUV to track the reference trajectory. Particularly, the time-delay estimation and dynamic gain strategies are adopted to reduce the influence of state disturbances. Moreover, the convergence conditions and Cramer–Rao lower bounds for the localization algorithm are derived. For the tracking controller, Lyapunov functions are constructed to analyze the stability, through which the sufficient conditions for asymptotic stability are presented. Finally, simulation and experiment results are given to show the effectiveness of the proposed method. It is demonstrated that the asynchronous localization algorithm in this paper can effectively eliminate the impact of the clock skew and offset. Meanwhile, the tracking accuracy can be significantly improved.

This letter is concerned with an asynchronous localization issue for underwater acoustic sensor networks (UASNs), subject to asynchronous clocks and stratification effects in physical channels. A novel unscented transform-based localization algorithm is proposed to estimate the positions of sensor nodes. Instead of linearizing the measurement equations, the proposed algorithm employs the unscented transform to compute the Jacobian matrix to reduce the linearization errors. Particularly, the ray-tracing approach is adopted to model the stratification effect. Moreover, the convergence analysis and Cramer-Rao lower bound for the algorithm are also provided. Simulation results show that the proposed algorithm can effectively improve the estimation accuracy as compared with the existing works.

Directional antenna-based aerial networking (DAAN) is referred as a promising technology to meet the dynamic data demands for unmanned aerial vehicles (UAVs). However, the narrow radiation pattern of directional antennas and the mobility of UAVs make it challenging to form a robust DAAN. This paper presents a heading control strategy for UAV-carried directional antennas to establish a robust long-range aerial communication channel. The heading control process is mainly divided into two phases, i.e., position estimation and angle adjustment. In the first phase, a proportional-derivative-based tracking controller is designed for each UAV to ensure the consistency of heights, pitch, and roll angles. Particularly, the received signal strength indicator is adopted as an auxiliary measuring component, and then a consensus-based unscented Kalman filtering algorithm is developed to estimate the position of UAVs. With the estimated position information, a feedback-based heading controller is designed for directional antenna in the second phase to enable robust long-range aerial communication channel. Moreover, the convergence conditions and Cramer–Rao lower bounds are also provided. Finally, simulation results are presented to demonstrate the effectiveness of the proposed strategy. It is shown that the influence of malicious measurements can be reduced, and the signal strength can be significantly improved as compared with the omni-directional antenna-based works.

In this research, the effect of stress relief annealing heat treatment on mechanical properties, microstructure, and residual stresses of a severe plastic deformation technique, known as constrained groove pressing (CGP), was investigated. For this purpose, the CGP process was performed on the commercial pure copper sheet with 3-mm thickness. The hardness, strength, homogeneity, microstructure, and residual stresses before and after stress relief annealing heat treatment were evaluated. Hardness and homogeneity on the surface and thickness were investigated and strength in both of groove direction and transverse groove direction were determined. Also, microstructure was studied along the thickness of CGPed samples, and the contour method was used for 2D residual stress measurement. The results indicate, with increasing number of CGP passes, hardness, strength, and homogeneity increase, while the mean grain size and residual stress decrease. Stress relief annealing reduces the mean grain size in the first pass but increases the mean grain size in the subsequent passes, causing a decrease of mechanical properties. Also, stress relief annealing increases residual stresses due to increasing microstructure heterogeneity.

There is a nonlinear coupling relationship between the vehicle in the longitudinal, lateral, and vertical directions, which brings great difficulties to the design of the controller. To tackle the chattering problem, a hierarchical integrated controller for distributed electric vehicle is proposed to improve driving safety, handling stability, ride comfort, and road tracking capabilities. The proposed algorithm has been developed to overcome a major challenge of the conventional method, which can improve only partial dynamic performance of the vehicle. The optimal pre-pointing lateral acceleration model is used to simulate the operator's expected reaction to the vehicle. The body control layer decouples complex problems to achieve multi-target independent tracking through a nonlinear sliding-mode control algorithm, and calculates the expected total body force to meet the upper level instructions. The tire force distribution layer is designed to optimize the function by reducing the tire load ratio and balancing the vertical dynamic load coefficient to improve the vehicle's driving stability and ride comfort. The lower actuator control layer controls the corresponding actuator to achieve the optimal tire force output from the middle layer. Finally, the effectiveness of the chassis integrated control system is verified in CarSim and MATLAB co-simulation.

Thermal depolarization is an insurmountable obstacle to the application of piezoceramics and there is still controversy about its physical origin. In this work, taking four representative piezoceramics (0.94(Na0.5Bi0.5)TiO3-0.06BaTiO3, 0.2Pb(Zn1/3Nb2/3)O3-0.8Pb(Zr0.5Ti0.5)O3, 0.36BiScO3-0.64PbTiO3 and Ba0.85Ca0.15Ti0.9Zr0.1O3) as an example, by using a designed in-situ Berlincourt-type high-temperature d33 meter, combined with variable temperature X-ray diffraction and dielectric temperature spectrum test, it was confirmed the depolarization behavior is directly related to the structural phase transition, meanwhile it is reasonable to apply the peak value of piezoelectric coefficient with temperature, Tdp, as the depolarization characteristic temperature. More importantly, the original in-situ varied temperature d33 meter design helps to investigate the temperature dependent piezoelectric mechanism of various piezoceramics.

This paper presents a novel braking torque distribution strategy for electric vehicles with four in-wheel motors equipped with the regenerative braking system. Safety and regeneration efficiency are the two major themes in the design of a regenerative braking system. Based on model predictive control (MPC) theory, the issues of multiple objectives and constraints of the regenerative braking system is well addressed. This proposed torque distribution controller can maximize the regeneration efficiency by determining the hydraulic braking torque and motor braking torque, which subject to the actuator constraints. Total braking torque of the four wheels tracks the braking requirement. Furthermore, in the case of ensuring brake safety, the braking torque of front and rear wheels are optimized to improve the possibility of energy recovery. The simulations have been conducted in Simulink environment based on an electric vehicle model established in AMESim software to verify the advantage of the proposed model predictive controller. In addition, the real-time test also demonstrates the effectiveness of the presented optimal control strategy.

Corrosion tests were conducted in a high-temperature high-pressure (HTHP) autoclave to simulate the conditions of CO2 auxiliary steam drive in gas injection wells. Weight loss tests were performed with the sheets of N80 and 9Cr steels under the testing conditions. The morphology and composition of corrosion products were explored by SEM, EDS, XRD and XPS. The corrosion resistance of 9Cr steel was better than that of N80 steel under the testing conditions. The corrosion rates of N80 and 9Cr met the application requirements in CO2 auxiliary steam drive. The results broke the constraint in ISO-15156 standards. The corrosion process of N80 steel was mainly affected by the flow velocity. However, the corrosion process of 9Cr steel was mainly affected by temperature. The corrosion resistance of 9Cr steel depended on the FeCO3 content of Cr-rich layer, which was closely related to temperature. The low flow velocity influenced the diffusion process of N80 steel corrosive ions, whereas the high flow velocity influenced the integrity of corrosion scales. Considering the influence of flow velocity on the corrosion of tubing and casing, in the gas injection well, 9Cr steel and N80 steel were, respectively, selected as the materials of tubing and casing.

Target tracking has been considered as one of the most important applications of underwater acoustic sensor networks. However, the long propagation delay, high-energy consumption, and strong noise properties of the underwater environment make target tracking more challenging as compared with terrestrial sensor networks. This article is concerned with an energy-efficient tracking issue for underwater targets, subject to an asynchronous clock, power restriction, and noise measurement constraints. The tracking process can be divided into two phases, i.e., position acquisition and persistent tracking. In the first phase, we establish the relationship between propagation delay and position, through which an asynchronous localization algorithm is developed for sensor nodes to estimate the position of target. Based on the estimated position, a consensus-based Bayesian filter is designed for sensor nodes in the second phase to enable persistent tracking. In particular, the consensus fusion strategy and duty-cycle mechanism are jointly adopted to improve the tracking accuracy and prolong the network lifetime. Moreover, the convergence analyses for the proposed approach are also presented. Finally, simulation and experimental results reveal that the proposed tracking approach can reduce the influence of malicious measurements, while the energy efficiency can be significantly improved as compared with the other works. Note to Practitioners —Underwater target tracking is aimed to acquire precise location and achieve sustainable monitoring for a target. It has important practical significance to enhance marine observing ability. Currently, the most favorable carrier for underwater communication is still the acoustic wave. However, due to the unique characteristics of acoustic communication, the tracking schemes developed for the terrestrial environment cannot be directly applied to underwater acoustic sensor networks. With this as motivation, we develop an energy-efficient tracking approach for underwater targets. The tracking approach developed in this article exploits timestamp measurement, consensus fusion strategy, and duty-cycle mechanism to capture the unique characteristics of acoustic communication. To better use this approach for target tracking, two factors should be highlighted: 1) the clocks between target and sensors are not required to be synchronized and 2) the sensor nodes are not always demanded to retain the active mode. Simultaneously, it is more meaningful from the view of marine engineering to design the control and communication platforms. Simulation and experimental results suggest that the proposed tracking method is feasible and has superior performance as compared with the existing methods. Hopefully, our tracking strategy can provide valuable theoretical and technical support guidance to the practicing marine engineer for the co-design of control and communication.

Coauthorship prediction is challenging yet important for academic collaboration and novel research topics discovery. The challenges lie in the dynamics of social or organizational relationships, changing preferences of suitable collaborators, and the evolution of research interests or topics. However, most current approaches and systems developed so far are mainly based on past coauthorships from a static viewpoint and do not capture the above evolving characteristics in coauthoring. Accordingly, this paper proposes a time-aware approach to capture the evolving coauthorships from online academic databases in terms of capturing the dynamics of social relationships and research interests. In particular, in order to understand the underlying factors influencing researchers to make choices of coauthors, we incorporate choice modeling based on utility theory. More specifically, our model conducts a series of pairwise choices over a poset induced by a utility function so as to learn the preference over all candidate coauthors. To complete the model inference, a gradient-based algorithm is devised to efficiently learn the model parameters for large-scale data. Finally, extensive experiments conducted on a real-world dataset show that our approach consistently outperforms other state-of-the-art methods.

In this paper, a slip ratio controller based on model predictive control (MPC) considering road roughness is proposed for electric vehicle (EV) to improve the driving/braking performance under low adhesion coefficient road. A half vehicle dynamic model is derived in which pitching, wheel rolling, and tire vertical movement is taking into account. The influence of vertical force variation caused by road unevenness and tire load transfer is analyzed to design slip ratio controller. In order to ensure vehicle safety, wheel slip stable zone is considered as time-domain constraints of the nonlinear-MPC. Besides, the motor output torque is limited by the motor maximum torque, which is considered as system time-varying constraints. The control objectives include vehicle safety, good longitudinal acceleration and braking performance, preservation of driver comfort, and lower power consumption. The proposed slip ratio controller is verified on a 13-degree-of-freedom (13DOF) EV model in MATLAB/Simulink. Simulation results of different maneuver on roughness surfaces show the benefits of the controller.

Based on the strong requirement for self-powered devices, energy harvesting by utilizing piezoelectric materials has recently attracted extensive attention. Transduction coefficient (d33·g33) is the core parameter of the piezoelectric energy harvesting materials, which is directly determined by the ratio of the piezoelectric charge constant (d33) to the dielectric constant (er). Unfortunately, traditional solid solution design method generally causes a simultaneous increase or decrease in both d33 and er, making it difficult to obtain a high d33·g33. In this work, a composite design strategy was proposed to separate the synergistic change of d33 and er. This was achieved by introducing lower-er ZnAl2O4 secondary phase into the popular 0.2Pb(Zn1/3Nb2/3)O3–0.8Pb(Zr1/2Ti1/2)O3 (PZN–PZT) perovskite matrix. Encouragingly, the er value rapidly decreased, while d33 value improved within a certain range compared to those of pure PZN–PZT. This was ascribed to the formation of fine domain structures in composites caused by the heterogeneous interfacial effect. Subsequently, the cantilever beam type piezoelectric energy harvesters (PEHs) made from the optimal composites exhibited a high power density of 4.0 μW mm−3 at 1 g acceleration. More importantly, PEHs could harvest vibrational energy from the operating motor to charge a capacitor and instantly drive wireless micro-sensors, demonstrating their potential application in self-powered electronics. Under the guide of the composite design strategy proposed in this work, more high performance piezoelectric energy harvesting materials can be built in the future.

In this work, both Finite element simulated method and contour method experimental measurement are used to obtain residual stresses of different Titanium welded alloys, the results show that the maximum of the residual stress is mainly related to the internal restraint degree which formed inside of the thickness, the distribution of the residual stress depends primarily on the shape of weld shape. The heating stage plays a major role in relaxing the residual stress in this research. 95% of the residual stress is relieved in the temperature rising period, and about 75% of it is relieved in the temperature rising period when the temperature is above 500°C.

© 2018 IEEE. Classic recommender systems (RSs) often repeatedly recommend similar items to user historical profiles or recent purchases. For this, session-based RSs (SBRSs) are extensively studied in recent years. Current SBRSs often assume a rigid-order sequence, which does not fit in many real-world cases. In fact, the next-item recommendation depends on not only current session context but also historical sessions which are often neglected by current SBRSs. Accordingly, an SBRS over relaxed-order sequences with both intra- and inter-context is more pragmatic. Inspired by the successful experience in modern language modeling, we design an efficient neural architecture to model both intra- and inter-context for next item prediction.

Drug resistance arising from overexpressed efflux transporters increases the efflux of drugs and accordingly restricts the efficacy of chemotherapy. Advances in nanocarriers have provided potential strategies to cope with drug resistance. Herein, endogenous stimuli-responsive nucleus-targeted nanocarrier is developed for intracellular multidrug resistance protein 1 (MRP1) mRNA imaging and drug delivery. This nanocarrier (AuNP-mRS-DSs) is composed of three parts: (i) gold nanoparticle (AuNP), for loading DNA and quenching fluorescence; (ii) mRNA recognition sequence (mRS) modified on the surface of gold nanoparticle by gold-thiol bond, for the specific recognition of MRP1 mRNA; (iii) detachable subunit (DS), hybridized with Cy5-labeled DNA linker and nucleolin recognition motif and grafted onto mRS via the DNA linker for loading doxorubicin (Dox), binding to nucleolin, and reporting signal. First, nucleolin recognition motif of this nanocarrier targets nucleolin, which is overexpressed on cancer cells surface; subsequently, the whole nanocarrier enters the cell via nucleolin-mediated internalization. Subsequently, mRS will specifically recognize overexpressed MRP1 mRNA, leading to the release of trapped DS and followed by AuNP-quenched Cy5 fluorescence recovery. Finally, by translocation of nucleolin from cytoplasm to nucleus, the DS targets nucleus to delivery Dox. By intracellular fluorescence imaging, the differentiation of drug-resistant and nondrug-resistant cells could be achieved. Compared with free Dox (IC50 > 8.00 μM), Dox-loaded AuNP-mRS-DSs (IC50 = 2.20 μM) performed superior suppression efficacy toward drug-resistant cancer cells. Such a nanocarrier provides an effective strategy to synergistically sense and circumvent drug resistance, which may be exploited as a candidate for personalized medicine.

Investigation and evaluation of dyes play a vital role in the process of introduction novel labels and their corresponding sensing methods, which signify opportunities for the development of biosensors. This chapter introduces applications of various dyes as labels in biosensing. Bio-recognition molecules with dyes transduce biological information into measurable optical, electrochemical, magnetic or other kinds of signals for quantification. The dyes used in this field were summarized and reviewed according to their signal types, namely colorimetric, fluorescent and electrochemical. Some dyes can transduce signals between multiple physical signals. For some most important dyes, detailed descriptions were given focused on their unique properties, labeling methods and sensing mechanisms.

Ochratoxin A (OTA), a toxic secondary metabolite produced via various fungus, poses a serious threat to the health of human beings and animals. In this paper, an aptasensor for OTA detection based on gold nanoparticles decorated molybdenum oxide (AuNPs-MoOx) nanocomposites, hybridization chain reaction (HCR) and a restriction endonuclease (Nb.BbvCI)-aided walker DNA machine was successfully constructed. In this electrochemical platform, the HCR was also used to embed more electrical signal molecules of methylene blue (MB) on silver nanoparticles (AgNPs) to achieve signal amplification. Under the optimum conditions, after adding OTA and Nb.BbvCI in turn and responding adequately under appropriate conditions, aptamer-DNA (6-DNA) carries the OTA away from the electrode surface, and walker DNA was hybridized autonomously with 5-DNA, releasing a large amount of 5′-DNA with the help of Nb.BBVCI. Finally, the electrochemical signal obtained by differential pulse voltammetry (DPV) was weakened. As an artificial and popular signal amplification technique, the DNA walking machine greatly improved the sensitivity. The proposed biosensor exhibited excellent analytical performance in the range of 0.01–10000 pg mL−1 with a detection limit as low as 3.3 fg mL−1. Furthermore, direct comparison with ultraperformance liquid chromatography (UPLC) indicates excellent agreement to actual samples such as apple juice, orange juice, red wine and serum.

Asset allocation is one of the key elements in financial market. The rationale is to invest on various assets that are different from each other. Lots of methods have been proposed to classify assets into different sub groups. But most of the ideas are either too macroscopic or too mathematical. These methods use lots of financial ideas that may contain human biases such as Merrill Lynch investment clock, or use some close-formed mathematical measurement that cannot easily incorporate financial insights. In this paper, we create diversified portfolios using clustering analysis. We use a nonlinear metric learning algorithm called ITML, which combines financial knowledge with mathematical metrics. It controls the amount of prior information used in the model and can be customized based on different scenarios. Back-testing results show that portfolios generated by our algorithm significantly outperform portfolios from random-selected ETF. ETF is Exchange Traded Fund, which can be traded easily like stocks. The indicators we used to evaluate the portfolios include return, correlation, volatility, Sharpe Ratio and maximum drawdown. The tests are based on Monte Carlo simulations and we allocate the assets based on risk parity. We use 149 most typical ETFs from global market including high/low risk bond ETFs, stock ETFs on Chinese, HK, Germany and US markets in different industry sectors, silver/gold ETFs and energy commodity ETFs. Moreover, features observation gives satisfying explanation for clustering results and shows our model offers good interpretability.