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With the coverage of sensor-rich smart devices (smartphones, iPads, etc.), combined with the need to collect large amounts of data, mobile crowd sensing (MCS) has gradually attracted the attention of academics in recent years. MCS is a new and promising model for mass perception and computational data collection. The main function is to recruit a large group of participants with mobile devices to perform sensing tasks in a given area. Task assignment is an important research topic in MCS systems, which aims to efficiently assign sensing tasks to recruited workers. Previous studies have focused on greedy or heuristic approaches, whereas the MCS task allocation problem is usually an NP-hard optimisation problem due to various resource and quality constraints, and traditional greedy or heuristic approaches usually suffer from performance loss to some extent. In addition, the platform-centric task allocation model usually considers the interests of the platform and ignores the feelings of other participants, to the detriment of the platform’s development. Therefore, in this paper, deep reinforcement learning methods are used to find more efficient task assignment solutions, and a weighted approach is adopted to optimise multiple objectives. Specifically, we use a double deep Q network (D3QN) based on the dueling architecture to solve the task allocation problem. Since the maximum travel distance of the workers, the reward value, and the random arrival and time sensitivity of the sensing tasks are considered, this is a dynamic task allocation problem under multiple constraints. For dynamic problems, traditional heuristics (eg, pso, genetics) are often difficult to solve from a modeling and practical perspective. Reinforcement learning can obtain sub-optimal or optimal solutions in a limited time by means of sequential decision-making. Finally, we compare the proposed D3QN-based solution with the standard baseline solution, and experiments show that it outperforms the baseline solution in terms of platform profit, task completion rate, etc., the utility and attractiveness of the platform are enhanced.

Efficient enantioselective separation using porous materials requires tailored and diverse pore environments to interact with chiral substrates; yet, current cage materials usually feature uniform pores. Herein, we report two porous assemblies

This paper studied the trajectory tracking control of a failure satellite that has actuator jumping fault. It proposed a design method based on the jumping control input for the model reference tracking controller. By comb-ining the stochastic stability definition with model reference tracking, it gave the mathematical descriptions of the trajectory tracking control of the failure satellite. It used the linear matrix inequality method and the parametric solution method of the nonhomogeneous generalized Sylvester matrix equation to design the robust H∞ state feedback control law and the complete parametric feed-forward tracking compensator respectively, with the disturbance of the failure satellite and its thrust constraint considered simultaneously. The numerical simulation results on the model of the satellite rendezvous system show that the design method proposed in this paper is effective.

A chiral metal-organic framework (CMOF) with open chiral channels and multiple recognition sites is constructed from camphoric acid and a dipyridyl ligand. It can act as an efficient chiral solid adsorbent, capable of separating a variety of racemic alcohols and epoxides with excellent enantioselectivities.

A biomimetic metal–organic framework with cuboid inner cavities and multiple recognition sites was constructed from a phenylalanine-derived ligand. It can enantioselectively separate various racemic alcohols, diols and epoxides with ee up to 99.5%.

A novel hybrid structure of bimetallic dicyanamide decorated BiVO4 is developed via a simple method to accelerate interfacial water oxidation kinetics. Two types of bimetallic dicyanamides, CoNi(dca)2 and CoFe(dca)2, are coated on BiVO4 photoanodes and are found to exhibit far more enhanced PEC performance than Co(dca)2 or Ni(dca)2 as cocatalysts. The successful deposition of metal dicyanamides on BiVO4 photoanodes is confirmed by physical characterizations including X-ray photoelectron spectroscopy (XPS). The optimized Co0.9Ni0.1(dca)2/BiVO4 photoanode exhibits the highest photocurrent density of 2.58 mA/cm2 at 1.23 V vs. RHE under 100 mW/cm2 AM 1.5 G irradiation, which is 2.5 times that of bare BiVO4. The substantial enhancement of PEC performance can be ascribed to the advantageous interfacial charge transfer and improved charge injection efficiencies. This work presents a feasible strategy using different types of bimetallic dicyanamides to design a modified BiVO4-based photoanode system for enhanced water oxidation efficiency.

The birth of the Internet has brought great changes to people's production and life. China's Internet development has gone through more than 10 years, during which it experienced the initial stage of ignorance and rapid development. The subsequent economic bubble brought the Internet economy to a low level. After the baptism of the Internet economic bubble, the China Internet reopened its vitality and gradually moved toward the right track. Tencent and Chinese Internet companies have experienced the ups and downs of the Internet economy and become the leader of Chinese Internet enterprises after more than ten years of development. What on earth did Tencent achieve so much? What is the difference between its competitive strategy and other Internet companies? These are the problems that this paper attempts to study in depth.

To solve surface carrier recombination and sluggish water oxidation kinetics of hematite (α-Fe

Atom search optimization algorithm has good searching ability and has been successfully applied to calculate hydrogeological parameters and groundwater dispersion coefficient. Since the atom search optimization algorithm is only based on the atom force motion model in molecular dynamics, it has some shortcomings such as slow search speed and low precision during the later stage of iteration. A modified atom search optimization based on the immunologic mechanism and reinforcement learning is proposed to overcome the abovementioned shortcomings in this paper. The proposed algorithm introduces a vaccine operator to better utilize the dominant position in the current atom population so that the speed, accuracy, and domain search ability of the atom search optimization algorithm can be strengthened. The reinforcement learning operator is applied to dynamically adjust the vaccination probability to balance the global exploration ability and local exploitation ability. The test results of 21 benchmark functions confirm that the performance of the proposed algorithm is superior to seven contrast algorithms in search accuracy, convergence speed, and robustness. The proposed algorithm is used to optimize the permutation flow shop scheduling problem. The experimental results indicate that the proposed algorithm can achieve better optimization results than the seven comparative algorithms, so the proposed algorithm has good practical application value.

Many optimization algorithms have been proposed to solve hybrid flowshop scheduling problem (HFSP). However, with the development of industry and society, labor right and labor safety have become important problem to consider in production scheduling. So the green HFSP considering makespan, noise and dust pollution becomes an urgent problem to be solved. In this paper, the rider optimization algorithm (ROA) is modified into the multi-objective rider optimization algorithm (MOROA) using Pareto archive and neighborhood sorting techniques. The Pareto archive and neighborhood sorting technology make the Pareto optimal solution set of MOROA have higher coverage and more solutions. Then MOROA is discretized into discrete MOROA (DMOROA) to solve the HFSP considering makespan, noise and dust pollution. DMOROA is tested on 10, 30 and 50 jobs HFSP considering makespan, noise and dust pollution. The test results are compared with two multi-objective algorithms to verify the performance of DMOROA. And the test results verify that the DMOROA is superior to the comparison algorithms in search accuracy, number of non-dominated solutions, diversity of solution set and stability. Therefore, DMOROA is effective in solving multi-objective HFSP considering makespan, noise and dust pollution.

The optimal foraging algorithm (OFA) was proposed by summarizing the rules of the animal foraging behavior in a group. Therefore OFA also has the defects of the swarm intelligence algorithm, such as easy to trap into local optimum and low convergence accuracy. In order to overcome these defects, an optimal foraging algorithm based on differential evolution (DEOFA) is proposed. The differential evolution mechanism contains mutation and crossover operators. The mutation and crossover operators are used to accelerate the convergence speed and global search capability of the OFA. The mutation operator is adopted to perform mutation operations centered on the optimal individual of each iteration to raise the convergence accuracy of the OFA. The test results of 30 benchmark functions show that the performance of DEOFA is better than nine compared algorithms in search accuracy, convergence speed and robustness. In order to verify the effectiveness of the DEOFA in solving practical problems, DEOFA is applied to solve the 0-1 knapsack problem. The test results in the six examples of 0-1 knapsack problems indicate that the DEOFA achieves better performance in accuracy, stability and high dimension.

Metal-nitrides-based electrocatalysts for efficient oxygen-evolution have been extensively studied as one of the most promising candidates to fulfil the demand for future energy-conversion and storage. Herein, a series of NixCo1−xO- and NixCo1−xN-based nanostructures on nickel foams were reported to show excellent activities for oxygen-evolution reaction. The catalysts were prepared and modulated rationally via a facile-hydrothermal method, followed by high-temperature calcination under air or nitrogen atmosphere. The optimal bimetallic-nitride catalyst Ni0.3Co0.7N shows a small overpotential of 268 mV at 20 mA cm−2, and a Tafel slope of 66 mV dec−1 with good stability. The enhanced OER-performance is ascribed to the synergetic effect of the unique morphology and the intrinsic catalytic property of the nanostructure after nitridation.

Taking a 1000 MW turbine generator as the research object, the short-circuit fault in electrical disturbance is analyzed. Since it is very difficult to carry out fault analysis experiments and research on actual systems, simulation analysis is one of the more effective means of electrical fault diagnosis, the simulation’s results approach the actual behavior of the system and are ideal tools for power system analysis, and can provide an empirical basis for practical applications. The short-circuit fault model of the SIMULINK power system is built to analyze the two types of faults of generator terminals short-circuit and power grid short-circuit. The impact load spectrum, fault current and speed fluctuation between low-voltage rotors were extracted and analyzed. The conclusion is that the impact value of electromagnetic torque at the generator terminal is greater than that on the power grid side. The impact value of a two-phase short-circuit at the generator terminal is the largest, and that of a three-phase short-circuit on the power grid side is the smallest. The transient impulse current of a three-phase short-circuit at any fault point is greater than that of a two-phase short-circuit, the impulse current of the grid side short-circuit is much greater than that of the generator terminal short-circuit, the speed fluctuation and fluctuation difference caused by the three-phase short-circuit in the grid side are the largest. The alternating frequency of the transient electromagnetic force of the four kinds of faults avoids the natural frequency of the torsional vibration of the shaft system, and the torsional resonance of the shaft system in the time domain of the short-circuit fault will not appear. However, after the fault is removed, the residual small fluctuation torque in the system has a potential impact on the rotor system. This research shows an analysis of the structural integrity and safe operation of turbine generator units after a short-circuit fault, which can not only be applied to engineering practice, but also provide a theoretical basis for subsequent research.

This paper presents a study on wave propagation in rotating functionally graded (FG) microbeams reinforced by graphene nanoplatelets (GPLs). The graphene nanoplatelets (GPLs) are considered to distribute in the diameter direction of the micro-beam in a gradient pattern, which leads to the functionally graded structure. By using the Halpin-Tsai micromechanics model and the rule of mixture, the effective material properties of the microbeam are determined. According to the Euler-Bernoulli beam theory and nonlocal elasticity theory, the rotating microbeams are modeled. A comprehensive parametric study is conducted to examine the effects of rotating speed, GPL distribution pattern, GPL length-to-thickness ratio, GPL length-to-width ratio, and nonlocal scale on the wavenumber, phase speed and group speed of the microbeam. The research findings can play an important role on the design of rotating graphene nanoplatelet (GPL) reinforced microbeams for better structural performance.

Plates are commonly used in many engineering disciplines, including aerospace. With the continuous improvement in the capacity of high value-added airplanes, large transport aircrafts, and fighter planes that have high strength, high toughness, and corrosion resistance have gradually become the development direction of airplane plate structure production and research. The strength and stability of metal plate structures can be improved by adding reinforced materials. This paper studies graphene platelets (GPLs) reinforced with a free vibration porous composite plate. The porous plate is constructed with a multi-layer model in a metal matrix containing uniform or non-uniformly distributed open-cell internal pores. Considering the random and directional arrangement of graphene platelets in the matrix, the elastic modulus of graphene composites was estimated using the Halpin–Tsai micromechanical model, and the vibration frequencies of graphene composite were calculated using the differential quadrature method. The effects of the total number of layers, GPL distribution pattern, porosity coefficient, GPL weight fraction, and boundary conditions on the free vibration frequency of GPLs reinforced porous composite plates are studied, and the accuracy of the conclusions are verified by the finite element software.

Surface treatment is an effective method to improve the photoelectrochemical (PEC) performance of photoelectrodes. Herein, we introduced a novel strategy of surface sulfurization to modify hematite (α-Fe2O3) nanorods grown in an aqueous solution, which triggered encouraging improvement in PEC performances. In comparison to the solution-grown pristine α-Fe2O3 nanorod photoanode that is PEC inefficient and always needs high temperature (>600 °C) activation, the surface sulfurized α-Fe2O3 nanorods show photocurrent density increased by orders of magnitude, reaching 0.46 mA cm−2 at 1.23 V vs. RHE (reversible hydrogen electrode) under simulated solar illumination. This improvement in PEC performances should be attributed to the synergy of the increased carrier density, the reduced surface charge carrier recombination and the accelerated water oxidation kinetics at the α-Fe2O3/electrolyte interface, as induced by the incorporation of S ions and the formation of multi-state S species (Fe-Sx-Oy) at the surface of α-Fe2O3 nanorods. This study paves a new and facile approach to activate α-Fe2O3 and even other metal oxides as photoelectrodes for improved PEC water splitting performances, by engineering the surface structure to relieve the bottlenecks of charge transfer dynamics and redox reaction kinetics at the electrode/electrolyte interface.

Characterized by less parameter settings, easy implementation, and strong optimization capacity, the crow search algorithm has been successfully applied to solve the optimization problem. As the basic crow search algorithm is a new kind of swarm intelligent algorithm only based on the crow's memory foraging mode, it also contains defects like slow search speed and low optimization precision in later iterations, which are especially obvious for the optimization of high-dimensional functions. In order to overcome these shortcomings, a new crow search algorithm based on neighborhood search of non-inferior solution set (NICSA) is proposed. The proposed algorithm makes the crow individual choose the memory search mode or neighborhood search mode automatically in the course of evolution by the determination factor of non-inferior solution. With this strategy, the local exploitation and the global exploration of the algorithm became more balanced. In the neighborhood search, the selectivity factor is used to guide non-inferior solutions to adaptively execute neighborhood search of Levy flight or Gaussian flight, to enhance the neighborhood searchability of the algorithm and improve the optimization precision. The result of simulation experiments with 23 benchmark test functions verifies that the proposed algorithm has good optimization effect in the aspects of search veracity, convergence rate and robustness.

A chiral structure with a negative Poisson’s ratio containing a hollow circle with varying diameters was designed, and the finite element method was used to investigate the variation in the Poisson’s ratio when the hollow circle diameter was varied (d = 0, 1, 2, 3, and 4 mm). The simulation results showed that the Poisson’s ratio was sensitive to the hollow circle diameter, and the minimum Poisson’s ratio was −0.43. Three specimens with different hollow circle diameters (d′ = 0, 1, and 3 mm) were 3D-printed from thermoplastic polyurethane, and the Poisson’s ratio and equivalent elastic modulus were measured. In the elastic range, the Poisson’s ratio increased and the equivalent elastic modulus decreased as the hollow circle diameter increased. The simulation and experimental results showed good agreement. The proposed structure is expected to be applicable to protective sports gear owing to its high energy absorption and the fact that its properties can be modified as required by adjusting the geometric parameters of the unit cell.

Bearings play an irreplaceable role in various categories of high-precision mechanical equipment. To reduce the adverse impact caused by sudden bearing failures, this paper proposes a method based on improved particle swarm optimization (IPSO), empirical mode decomposition (EMD), and support vector regression (SVR) to predict the remaining useful life (RUL) of bearing. The EMD method decomposes the raw vibration signal, and the components are chosen out according to the kurtosis criterion to reconstruct the vibration signal. After filtering out the noise, the features in time-domain and frequency-domain are extracted from the reconstructed vibration signal. The IPSO method is used to optimize three important parameters of the SVR model. Then the SVR model is trained with the extracted features to predict the bearing RUL. Actual bearing failure dataset is used to verify the validity of this method. Three different methods are used to compare with this proposed method. The results indicate that this proposed method performs best among the four methods in different evaluation indexes. The proposed method makes sense for bearing failure prediction.

The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (nos. 51961165103 and 51672210) and the National Key Research and Development Program of China (2018YFB1502003 and 2017YFE0193900). S.S. is supported by the National Program for Support of Top-notch Young Professionals and “The Youth Innovation Team of Shaanxi Universities.”

The RapidIO standard is a packet-switching interconnection technology similar to the Internet Protocol (IP) conceptually. It realizes the high-speed transmission of RapidIO packets at the transport layer, but this greatly increases the probability of network blocking. Therefore, it is of great significance to optimize the RapidIO routing strategy. For this problem, this paper proposes a Double-Antibody Group Multi-Objective Artificial Immune Algorithm (DAG-MOAIA), which improves the local search and global search ability of the population by adaptive crossover and adaptive mutation of the double-antibody groups, and uses co-competition of multi-antibody groups to increase the diversity of population. Through DAG-MOAIA, an optimal transmission path from the source node to multiple destination nodes can be selected to solve the Quality Of Service (QoS) problem during data transmission and ensure the QoS of the RapidIO network. Simulation results show that DAG-MOAIA could obtain high-quality solutions to select better routing transmission paths, and exhibit better comprehensive performance in all simulated test networks, which plays a certain role in solving the problem of the RapidIO routing strategy.

Bismuth vanadate (BiVO4) is one of the most promising metal oxide semiconductors for photoelectrochemical (PEC) water oxidation. Much efforts have been dedicated on accelerating the sluggish surface water oxidation kinetics. In this study, plasma enhanced atomic layer deposition and subsequent removal of Al2O3 ultrathin overlayers on bismuth vanadate were implemented to achieve the successful passivation of surface states and significant enhancement of PEC performance. Al2O3 ultrathin overlayers were first coated on BiVO4 surface via plasma enhanced atomic layer deposition with various deposition cycles, which resulted in the decrease of PEC water oxidation activity due to the poor conductivity. The subsequent removal of surface amorphous Al2O3 passivated the surface states of the photoanodes and significantly enhanced the photocurrent densities. The passivated BiVO4 exhibited a photocurrent density of 1.34 mA·cm−2 at 1.23 V vs. RHE, which is 73% higher than that of unmodified BiVO4. This work provides a novel strategy and deep insights on surface modification of semiconductor for photoelectrochemical energy conversion.

In this study, we report a simple, effective and universal approach to fabricate homojunction structural TiO2 nanorod array photoelectrodes through doping of gradient distributed oxygen vacancies introduced by annealing in high vacuum with controlled time. The homogeneous junction structure promotes the separation and transport of photoexcited charge carriers, and the photocurrent density of TiO2 nanorod arrays annealed in high vacuum for 2 h was 20 times higher than that of the pristine TiO2 nanorod arrays. The results indicate that annealing in high vacuum with controlled time could form a homojunction structure, which is an effective approach for further enhancing the performance of UV–visible light driven photocatalytic materials for water splitting.

This paper conducts a coupled vibration analysis of a two-stage bladed disk rotor system. According to the finite element method, the bladed disk rotor system is established. The substructure modal synthesis super-element method (SMSM) with a fixed interface and free interface is presented to obtain the vibration behaviors of the rotor system. Then, the free vibration results are compared with the ones calculated by the cyclic symmetry analysis method to validate the analysis in this paper. The results show that the modes of the two-stage bladed disk not only include the modes of the first- and second-stage bladed disk, but also the coupled modes of the two-stage bladed disk.

Given the proper band gap, low cost and good stability, hematite (α-Fe2O3) has been considered as a promising candidate for photoelectrochemical (PEC) water splitting, however suffers from the sluggish surface water oxidation reaction kinetics. In this study, a simple dip-coating process was used to modify the surface of α-Fe2O3 nanorod arrays with cobalt oxide (CoOx) and carbon (C) for the improved PEC performance, with a photocurrent density at 1.6 V (vs. reversible hydrogen electrode, RHE) increased from 0.10 mA/cm2 for the pristine α-Fe2O3 to 0.37 mA/cm2 for the CoOx/C modified α-Fe2O3 nanorods. As revealed by electrochemical analysis, thanks to the synergistic effect of CoOx and C, the PEC enhancement could be attributed to the enhanced charge transfer ability, decreased surface charge recombination, and accelerated water oxidation reaction kinetics. This study serves as a good example for improving PEC water splitting performance via a simple method.

Most mechanism contains one or more joints. However, joint clearances which cannot be dislodged make accuracy analysis become complicated. In order to seek a method to investigate the impact of joint clearances on the accuracy of a parallel robot, this paper deals with the 3-SPS-1-S spatial parallel robot’s pose error predicting and sensitivity analyzing. In this paper, a nonlinear method for evaluating the sources of the pose errors is proposed on the condition that the pose errors only come from joint clearances. Firstly, based on the nonlinear contact modes inside the joints, the error equivalent method is outlined for spherical joint and sliding pair. Then the pose error distribution over its workspace is presented. Secondly, those areas where the pose errors present abnormally changing are analyzed. Thirdly, sensitivity models are defined to evaluate how much the external variable load affects the pose errors. Finally, the simulation results, which are consistent with the structural characteristics of the 3-SPS-1-S spatial parallel robot, proved the validity of the equivalent method proposed in this paper.

The risk of knee injuries in freestyle skiing athletes that perform aerials is high. The internal stresses in the knee joints of these athletes cannot easily be directly measured. In order to ascertain the mechanical response of knee joints during the landing phase, and to explore the mechanism of damage to the cartilage and ligaments, a finite element model of the knee joint was established. Three successful landing conditions (neutral, backward, or forward landing) from a triple kicker were analyzed. The results demonstrate that the risk of cruciate ligament damage during a neutral landing was lowest. A forward landing carried medium risk, while backward landing was of highest risk. Backward and forward landing carried risk of injury to the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL), respectively. The magnitude of stress on the meniscus and cartilage varied for all three landing scenarios. Stress was largest during neutral landing and least in backward landing, while forward landing resulted in a medium level of stress. The results also provide the basis for training that is scientifically robust so as to reduce the risk of injury and assist in the development of a professional knee joint protector.

In this study, Nb-doped α-Fe2O3 nanorod photoanodes were prepared via a facile solution-based process by directly adding NbCl5 in the aqueous solution. The morphology and electronic structure of Nb-doped α-Fe2O3 films depended strongly on the dopant concentrations. Compared with the undoped sample, the optimal Nb-doped α-Fe2O3 film showed an approximately 4-fold photocurrent increase under solar light at 1.0 V versus Ag/AgCl, and the incident photon-to-current conversion efficiency was increased by 2.5 times, reaching 13.7 % at 350 nm and 1.23 V versus RHE. The enhancement in PEC activity, as induced by moderate Nb doping, was attributed to the increased charge carrier density for promoted charge transfer ability as well as the smaller nanorod diameter for shortened charge transfer distance. However, superfluous Nb dopants would destroy the nanorod structure and greatly reduce the thickness of α-Fe2O3 films, leading to poor optical absorption and thus decreased photoelectrochemical performance.

Porous photoelectrodes show high efficiency in hydrogen production by water splitting. However, fabrication of porous nanorods is usually difficult. Here, we report a simple approach to fabricate a kind of novel porous rutile titanium dioxide nanorod array by an advanced ion implantation method using multiple-energy helium ion implantation and subsequent annealing. The porous nanostructure enhances the photoelectrochemical performance of the titanium dioxide nanorod array photoelectrodes under Uv-visible light illumination, where the highest photocurrent density was relatively about 10 times higher than that of the pristine titanium dioxide nanorod array. The formation of nanocavities mainly contributes to the enhancement of the photocurrent density by trapping holes inside to separate the charge carriers. The study demonstrates that ion implantation could be an effective approach to develop novel porous nanostructural photoelectrodes for the application of hydrogen production.

Engineering the interface and surface structures of semiconductor-based photoelectrodes for improved charge transfer dynamics and promoted water redox reaction kinetics is essential to achieve efficient photoelectrochemical (PEC) water splitting. In this work, α-Fe2O3 nanorods, successively coated with TiO2 and CoOx thin layers, were reported as the photoanode for solar-driven water oxidation. The obtained α-Fe2O3/TiO2/CoOx photoanode exhibits superior PEC performance as compared to bare α-Fe2O3, with a 3.3-time improvement in photocurrent density at 1.23 V vs reversible hydrogen electrode. This significant enhancement results from the formed heterojunction between α-Fe2O3 and TiO2 for the accelerated photogenerated charge separation and transfer as well as the passivated surface defects by the TiO2 overlayer for reduced charge recombination. Additionally, the existence of CoOx as the oxygen evolution catalyst significantly facilitates the surface reaction kinetics and thus reduces the overpotential for water oxidation. This study demonstrates a collaborative strategy of interface and surface engineering to design novel structures of α-Fe2O3 based photoanodes for highly efficient solar water oxidation.

Novel hybrid tetra-nitro-phthalocyanine Copper(II) (TNCuPc)/TiO2 films were successfully synthesized using a simple hydrothermal and solvothermal method. The successful deposition of TNCuPc on the TiO2 nanorods was confirmed by X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The precursor concentration for hydrothermal deposition of TiO2 was optimized for light absorption and photoelectrochemical (PEC) water splitting. The hierarchical nanostructure exhibited increased light absorption ability and enhanced PEC properties. Moreover, the concentration of the precursor solution for TNCuPc deposition was also optimized for the performance of the TNCuPc/TiO2 hybrid nanostructure. The optimal sample achieved the highest photocurrent of 1.1 mA cm−2 and the highest IPCE of 51% at 610 nm.

In this study, a ternary nanostructured α-Fe2O3/Au/TiO2 film with integrating a crystalline α-Fe2O3 core, metallic Au nanoparticles (NPs), and an amorphous TiO2 overlayer is fabricated and examined as a photoanode for photoelectrocatalytic water splitting. Under simulated solar illumination, the as-prepared photoanode exhibits a four-fold increase (1.05 mA cm−2) in photocurrent density at 1.23 V versus reversible hydrogen electrode (RHE) relative to bare α-Fe2O3. Based on systematic investigations, it is proposed that Au NPs extract photoholes from the bulk of α-Fe2O3 core and then shuttle them to the outer TiO2 overlayer, and meanwhile, TiO2 overlayer efficiently captures and stores the photoholes and facilitates the hole injection into electrolyte. Thus, the remarkably improved photoelectrocatalytic water splitting performance of α-Fe2O3/Au/TiO2 photoanode is attributed to the significantly suppressed bulk and surface charge recombination due to the relayed pumping of the photogenerated charge carriers through the photoanode/electrolyte interfaces reconstructed by Au NPs and TiO2 overlayer.

A flower pollination algorithm is proposed based on the hormone modulation mechanism (HMM-FPA) to solve the no-wait flow shop scheduling problem (NWFSP). This algorithm minimizes the maximum accomplished time. Random keys are encoded based on an ascending sequence of components to make the flower pollination algorithm (FPA) suitable for the no-wait flow shop scheduling problem. The hormone modulation factor is introduced to strengthen information sharing among the flowers and improve FPA cross-pollination to enhance the algorithm global search performance. A variable neighborhood search strategy based on dynamic self-adaptive variable work piece blocks is constructed to improve the local search quality. Three common benchmark instances are applied to test the proposed algorithm. The result verifies that this algorithm is effective.

The photoelectrochemical (PEC) water splitting activity of Nb and Ta-doped hematite (α-Fe

Solar hydrogen conversion via photoelectrochemical water splitting is an important technology for energy and environment sustainability. Since the pioneering work of Fujishima and Honda in 1972, tremendous research on semiconductor-based photoelectrochemical water splitting has yielded better understanding of the processes as well as encouraging development of high efficiency photoelectrodes for solar hydrogen generation. Given the narrow band gap enabling excellent optical absorption, increased charge carrier density and accelerated surface oxidation reaction kinetics become the key points for improved photoelectrochemical performances for water splitting over α-Fe2O3 photoanodes. In this talk, some recent progresses in surface modified α-Fe2O3 for photoelectrochemical solar water splitting in our group will be introduced. By engineering the surface structures of α-Fe2O3 nanorods with AgxFe2-xO3, TiO2 and HfO2 overlayers, the surface charge recombination was greatly inhibited and the surface water oxidation kinetics were efficiently accelerated, resulting in remarkable enhancement in PEC water splitting performances.

Hematite (α-Fe2O3) has been extensively suggested as a superior photoanode for the photoelectrochemical (PEC) water splitting, owing to its natural abundance, high chemical stability, and theoretical solar-to-hydrogen (STH) efficiency (16.8%). Nevertheless, the recalcitrant electron−hole recombination resulting in poor charge separation and injection efficiency limits its PEC performance. Herein, a simple hydrothermal/atomic layer deposition (ALD) process was used to fabricate two types of HfO2 functionalized hematite (i.e., HfO2 overlayer and nanoparticles modified α-Fe2O3, HfFe-L and HfFe-P for short) photoanodes. It was revealed that HfO2 overlayer and nanoparticles could successfully passiviate the surface trap states of hematite, resulted in enhanced PEC performances for both HfFe-L and HfFe-P. More surprisingly, the photocurrent density of the HfFe-P reached as high as 1.21 mA cm-2 at 1.23 vs. RHE, with ~4.8 and ~3.3 fold enhancement as compared to that of the bare hematite and even HfFe-L, respectively. Such great PEC performance enhancement in HfFe-P was revealed to be attributed to the multifunction of HfO2 nanoparticles distributed on the surface of hematite nanorod arrays, which not only passivated surface defects to suppress the surface charge recombination by eliminating the surface trapping states, but can also facilitated the hole extraction from bulk of hematite to hematite/electrolyte interface.

The deep volcanic reservoir in Zhungeer Basin is buried in over 4000m depth, which is characterized by complex lithology (breccia, andesite, basalt, etc.), high elastic modulus and massive natural fractures. During hydraulic fracturing, hydraulic fracture will propagate and natural fractures will be triggered by the increasing net pressure. However, the extension of fractures, especially natural fractures, would aggravate the leak-off effect of fracturing fluid, and consequently decrease the fracturing success rate. 4 out of 12 fracturing wells in the field have failed to add enough proppants due to fluid loss. In order to increase the success rate and efficiency of hydraulic fracturing for deep volcanic reservoir, based on theoretical and experimental method, the mechanism of fracturing fluid leak-off is deeply studied. We propose a dualistic proppant scheme and employ the fluid loss reducer to control the fluid leak-off in macro-fractures and micro-fractures respectively. The proposed technique remarkably improved the success rate in deep volcanic rock fracturing. It bears important theoretical value and practical significance to improve the hydraulic fracturing design for deep volcanic reservoir.

Chicken swarm optimization is a new intelligent bionic algorithm, simulating the chicken swarm searching for food in nature. Basic algorithm is likely to fall into a local optimum and has a slow convergence rate. Aiming at these deficiencies, an improved chicken swarm optimization algorithm based on elite opposition-based learning is proposed. In cock swarm, random search based on adaptive t distribution is adopted to replace that based on Gaussian distribution so as to balance the global exploitation ability and local development ability of the algorithm. In hen swarm, elite opposition-based learning is introduced to promote the population diversity. Dimension-by-dimension greedy search mode is used to do local search for individual of optimal chicken swarm in order to improve optimization precision. According to the test results of 18 standard test functions and 2 engineering structure optimization problems, this algorithm has better effect on optimization precision and speed compared with basic chicken algorithm and other intelligent optimization algorithms.

Deep volcanic reservoir in Xinjiang Zhungeer basin is buried over 4000m, the elastic modulus of reservoir rocks is high, hence it is difficult to initiate hydraulic fracture during fracturing operation; fracturing fluid filtration is serious and hard to be controlled due to the massive natural fractures in reservoir. Because of the serious heterogeneity along both horizontal and vertical direction, the optimum targets of design fracturing for different well layers are not the same. 4 out of 12 fracturing wells have not achieved the target amount of proppant. Ultimately, fracturing success rate is low and the production increase after fracturing shows a big difference among different wells. In order to improve the success rate and efficiency of deep volcanic reservoir fracturing, based on the analysis of the difficulties in previous fracturing operation, combined with the geological characteristics of reservoir, we optimized the key engineering parameters of deep volcanic rock fracturing, including perforation parameters, filtration parameters, fracture parameters and operation parameters. Results of fracturing design optimization bear an important guiding significance for improving the fracturing success rate and efficiency of deep volcanic reservoir in Zhungeer basin, Xinjiang province.

Using consumer depth cameras at close range yields a higher surface resolution of the object, but this makes more serious noises. This form of noise tends to be located at or on the edge of the realistic surface over a large area, which is an obstacle for real-time applications that do not rely on point cloud post-processing. In order to fill this gap, by analyzing the noise region based on position and shape, we proposed a composite filtering system for using consumer depth cameras at close range. The system consists of three main modules that are used to eliminate different types of noise areas. Taking the human hand depth image as an example, the proposed filtering system can eliminate most of the noise areas. All algorithms in the system are not based on window smoothing and are accelerated by the GPU. By using Kinect v2 and SR300, a large number of contrast experiments show that the system can get good results and has extremely high real-time performance, which can be used as a pre-step for real-time human-computer interaction, real-time 3D reconstruction, and further filtering.

Anisotropic nanopatterns have potentials in constructing novel plasmonic structures which have various applications in such as super-resolution microscopy, medicine, and sensors. However, it remains challenging to build big anisotropic nanopatterns that are suitable for big noble metal nanoparticles. Herein, we report a simple and reliable strategy for constructing DNA origami-based big anisotropic nanopatterns with controlled size and shape, nanoscale resolution, and fully addressability. Two kinds of basic DNA origami nanoblocks - cross-shaped and rectangular DNA origami units were used. We have demonstrated that by encoding nanoblocks' edges, anisotropic higher-order nanopatterns, such as dimer, trimer, tetramer and mini "windmill" like pentamer nanopatterns could be constructed. To show the potential use as template to direct the assembly of anisotropic nanoparticles arrays, a proof of concept work was conducted by anchoring streptavidin nanoparticles on the "windmill" template to form a chiral array. Significantly, these nanopatterns have the sizes of hundreds of nanometers, which are in principle also suitable for big noble metal nanoparticles arrays.

This paper proposes a complete parametric approach for eigenstructure assignment in second-order system Mq+Dq+kq=cu using the displacement-plus-acceleration feedback controller. The expressions of closed-loop eigenvector matrix and feedback gains are in direct closed forms in terms of the closed-loop eigenvalues and a group parameter vectors, which represents the degree of design freedom. The main advantage of the proposed method is solved directly in matrix second-order framework, without transformation into the first-order form, and the numerical stability is better because it used only right coprime factorization and simple matrix transformation. The proposed algorithm is simple and does not contain ‘go back’ procedures. Finally, computational results show its effect and simplicity.

Ta-doped hematite (α-Fe2O3) nanorod array films were successfully prepared on fluorine-doped tin dioxide (FTO) coated glass substrates via a facile solution growth process with TaCl5 as a Ta doping precursor. Under 1 sun illumination and at an applied potential of 1.0 V vs. Ag/AgCl, the Ta-doped α-Fe2O3 photoanode with optimized dopant concentration showed a photocurrent density as high as 0.53 mA cm(-2), which was about 3.5 times higher than that of the undoped sample. As demonstrated by Mott-Schottky and X-ray absorption spectroscopy measurements, considerable increase in photoelectrochemical (PEC) performance achieved for Ta-doped α-Fe2O3 nanorod films should be mainly attributed to the increased electron donor density induced by Ta doping. However, with superfluous Ta doping, the [110]-oriented nanorod structure was destroyed, which caused greatly restrained photoinduced holes transferring to the surface and retarded surface water oxidation reaction, leading to decreased PEC water splitting activity. This study clearly demonstrated that doping could be effective to enhance the PEC activity of α-Fe2O3 nanorods as photoanodes, while it is of great necessity to balance the trade-off between the electronic structure and nanostructure evolution by optimizing the dopant concentration, for increased donor density and meanwhile with the nanorod nanostructure well preserved for directed charge transfer.

Apart from providing the material for genetic information storage, DNA has also been regarded as a useful building block in the field of nanotechnology, which is known as DNA nanotechnology. Based on the Watson-Crick base-pairing and the famous double helical structure, a library of DNA 2D or 3D nanostructures has been designed, constructed and characterized, by either tile-based or origami-based self-assembly. More significantly, other molecules/nanomaterials can be organized on those DNA ensembles to achieve highly ordered arrays or specific patterns in nanometer spatial resolution. In this review, we summarize recent progress in creating DNA nanoarchitectures, and discuss potential applications in DNA-based nanofabrication.