Most Cited
2016, 65 (21): 217502.
doi: 10.7498/aps.65.217502
Abstract +
Magnetocaloric effect（MCE) is the intrinsic property of a magnetic material near transition temperature and the magnetic refrigeration based on MCE has been demonstrated as a promising alternative to the conventional gas compression or expansion refrigeration due to its high energy efficiency and environmental friendliness. The development of magnetic refrigeration technology depends on the research progress of magnetic refrigerant materials with large MCEs. Lots of researches of material exploration and material optimization have promoted the progress of magnetic refrigeration technology in recent decades. In this paper, we introduce the basic theory of MCE and the development of refrigeration technology, review the research progress of large MCE materials both in low temperature range and in room temperature range, and specifically focus on the latest progress of some MCE materials. Low temperature MCE materials mainly include those rare earth based materials with low transition temperatures, such as binary alloys（RGa, RNi, RZn, RSi, R3Co and R12Co7), ternary alloys（RTSi, RTAl, RT2Si2, RCo2B2 and RCo3B2), and quaternary alloys（RT2B2C), where R denotes the rare earth and T represents the transition metal. Those materials mainly possess the second-order phase transitions and show good thermal hysteresis, magnetic hysteresis, and thermal conductivities. Room temperature MCE materials are mainly Gd-Si-Ge intermetallic compounds, La-Fe-Si intermetallic compounds, MnAs-based compounds, Mn-based Heusler alloys, Mn-based antiperovskite compounds, Mn-Co-Ge intermetallic compounds, Fe-Rh compounds, and perovskite-type oxides. The above materials usually have the first-order phase transitions and most of these materials possess the large MCEs in room temperature range, therefore they have received much attention home and abroad. Among those room temperature MCE materials, the La-Fe-Si series is considered to be the most promising magnetic refrigerant materials universally and our country has independent intellectual property rights of them. The further development prospects of MCE materials are also discussed at the end of this paper.
2016, 65 (18): 186801.
doi: 10.7498/aps.65.186801
Abstract +
Nature always supplies inspirations to scientists and engineers. Many newfangled materials have been fabricated by learning from and mimicking nature. In daily life and industrial processes these bioinspired novel materials have been widely used. The special wettability of natural organisms is significant to their life and attractive to researchers, which inspires us to fabricate the functional interfacial materials with high performances. In the last decade, the bioinspired multiscale interfacial materials exhibiting superwettability have emerged as a new type of functional material. Superwettable materials offer great chances to solve numerous issues ranging from fundamental research to practical exploration, and from bionic philosophy to fabricating technology. Inspired by nature's example, researchers developed a series of scientific strategies of new materials and fabricating methods, technologies, and applications. Based on the requirement of developing advanced materials in the fields of energy, environment, healthcare and resource, superwettable materials possessing binary cooperative nanostructure have been widely investigated to solve scientific and technical problems. In this review, we firstly present the development history of bioinspired multiscale interfacial materials with superwettability and the theoretical basis of the wettability of solid surfaces. Secondly, the principles of superwettable functional surfaces in nature is revealed and the bionic designs of bioinspired materials are discussed in detail. Meanwhile the typical applications of superwettable materials such as self-cleaning, oil-water separation and green printing are introduced. Finally, the perspectives of the future development of bioinspired superwettable materials are proposed for further studying the superwettable materials.
2016, 65 (1): 018102.
doi: 10.7498/aps.65.018102
Abstract +
Recently, two-dimensional (2D) layered molybdenum disulfide (MoS2) has attracted great attention because of its graphene-like structure and unique physical and chemical properties. In this paper, physical structure, band gap structure, and optical properties of MoS2 are summarized. MoS2 is semiconducting and composed of covalently bonded sheets held together by weak van der Waals force. In each MoS2 layer, a layer of molybdenum (Mo) atoms is sandwiched between two layers of sulfur (S) atoms. There are three types of MoS2 compounds, including 1T MoS2, 2H MoS2, and 3R MoS2. As the number of layers decreases, the bad gap becomes larger. The bad gap transforms from indirect to direct as MoS2 is thinned to a monolayer. Changes of band gap show a great potential in photoelectron. Preparation methods of 2D MoS2 are reviewed, including growth methods and exfoliation methods. Ammonium thiomolybdate (NH4)2MoS4, elemental molybdenum Mo and molybdenum trioxide MoO3 are used to synthesize 2D MoS2 by growth methods. (NH4)2MoS4 is dissolved in a solution and then coated on a substrate. (NH4)2MoS4 is decomposed into MoS2 after annealing at a high temperature. Mo is evaporated onto a substrate, and then sulfurized into MoS2. MoO3 is most used to synthesize MoS2 on different substrates by a chemical vapor deposition or plasma-enhanced chemical vapor deposition. Other precursors like Mo(CO)6, MoS2 and MoCl5 are also used for MoS2 growth. For the graphene-like structure, monolayer MoS2 can be exfoliated from bulk MoS2. Exfoliation methods include micromechanical exfoliation, liquid exfoliation, lithium-based intercalation and electrochemistry lithium-based intercalation. For micromechanical exfoliation, the efficiency is low and the sizes of MoS2 flakes are small. For liquid exfoliation, it is convenient for operation to obtain mass production, but the concentration of monolayer MoS2 is low. For lithium-based intercalation, the yield of monolayer MoS2 is high while it takes a long time and makes 2H MoS2 transform to 1T MoS2 in this process. For electrochemistry lithium-based intercalation, this method saves more time and achieves higher monolayer MoS2 yield, and annealing makes 1T MoS2 back to 2H MoS2. The applications of 2D MoS2 in field-effect transistors, sensors and memory are discussed. On-off ratio field effect transistor based on MoS2 has field-effect mobility of several hundred cm2V-1-1 and on/off ratio of 108 theoretically.
2016, 65 (1): 010502.
doi: 10.7498/aps.65.010502
Abstract +
Recently, the research on traffic flow system based on some classical models, such as cellular automata and car-following models, has attracted much attention. Some meaningful achievements have been obtained in the past few years by scholars from various fields. This paper starts with literature review on traffic flow theory studies. Car-following models, including the initial model proposed by Newell in 1961 (Newell G F 1961 Oper. Res. 9 209) and some later modified ones (e.g. full velocity difference model, or FVD model for short) have been deeply investigated. Based on Newell's car-following model, an extension of car-following model with consideration of vehicle-to-vehicle (V2V) communication is then developed. The vehicle-to-vehicle communication technology, which was proposed in the early 2000s, enable vehicles to collect traffic condition information from other vehicles (e.g. speed, headway, position, acceleration, etc.) and provide them for drivers in almost real time. Compared with those without V2V devices, drivers with information from V2V devices can react to traffic flow fluctuation timelier and more precisely. To represent the pre-reaction of drivers to traffic flow information provided by V2V devices, a parameter, , is newly introduced into Newell's car-following model. Then by second-order Taylor series expansion, a new car-following model with the influence of V2V (called V2V model) is proposed. Neutral stability condition of V2V model as well as phase diagram is derived theoretically with linear analysis method. The phase diagram of linear stability condition is divided into stable and unstable regions. By analyzing stability performance of the proposed model, it is evident that V2V communication technology can improve the stability of traffic flow system. Numerical simulation is demonstrated to study the influence of V2V devices on traffic flow on the one hand, and to acquire density waves as well as hysteresis loops under different values of parameter on the other hand. The sensitive analysis method are adopted as well.The numerical simulation results indicate that: 1) when compared with FVD model, V2V model can make vehicles react to traffic flow fluctuation earlier and reduce the speed changes under start-up, brake and incident conditions; this indicates that the consideration of V2V devices can improve the safety and ride comfort of traffic flow system; 2) the V2V model is sensitive to the value changes of parameter and T; the stability of traffic flow can be improved if the value of parameter increases, or parameter T decreases; this outcome precisely agrees with the above theoretical analysis; 3) the characteristics of traffic flow can influence the performance of V2V technology: compared with under low density condition, V2V communication technology can significantly increase the average speed of traffic flow under high density condition.
2016, 65 (19): 190502.
doi: 10.7498/aps.65.190502
Abstract +
To study the application of memristor in chaotic system, we employ the smooth continuous nonlinear flux-controlled memristor model and feedback control technique to design a hyperchaotic system based on the simplified Lorenz system. By using memristor as a positive feedback of the simplified Lorenz system, the dimensionless mathematical model is derived. The differences between the memristor-based chaotic system and ordinary chaotic system are then further studied. Firstly, the stable equilibrium and unstable equilibrium point sets of the system are analyzed theoretically, and it is found that the system has infinite equilibrium points including stable and unstable equilibrium points. The stable and unstable ranges of the system with different parameters are also determined. Theoretical analysis shows that the system has the same symmetry as the simplified Lorenz system. Thus the system has rich dynamical behaviors, such as limit cycle, chaotic attractor, and hyper-chaotic attractor. Secondly, by the methods of bifurcation diagram, Lyapunov exponent spectrum, Poincar section, and Spectral Entropy algorithm, the dynamical behaviors of the system are analyzed in detail. By calculating the Lyapunov exponent spectrum, the dynamical behaviors are studied and they change with system parameters and the initial conditions of memristor respectively. The maximum positive Lyapunov exponent of the memristor-based Lorenz hyperchaotic system is higher than that of the simplified Lorenz system, which indicates the memristor-based Lorenz hyperchaotic system is more complex. Further, we find all the complex dynamical behaviors to be coexisting with the infinite equilibrium sets, which is quite different from those of many ordinary hyper-chaotic systems. Meanwhile, we observe the attractors coexisting and state transition phenomenon in this system, caused by changing the initial conditions of the memristor. State transition phenomenon is then further studied by means of phase portraits and spectral entropy algorithm for the first time. Finally, by using operational amplifiers, diodes and other discrete components, we design an equivalent circuit of the smooth continuous nonlinear flux-controlled memristor model, and the equivalent circuit is used to design and realize the analog electronic circuit of the memristor-based Lorenz hyper-chaotic system. By using an analog oscilloscope, the phase portraits of hyper-chaotic attractor are observed clearly. The state transition phenomenon can also be seen using the oscilloscope. It is found that the circuit experimental results are in agreement with those of the theoretical analysis and numerical simulation. It verifies that the system is physically realizable, and lays a strong foundation for its applications in engineering. Next, we will try to investigate the chaotic secure communication based on this hyper-chaotic system.
2016, 65 (3): 030101.
doi: 10.7498/aps.65.030101
Abstract +
Wireless sensor network (WSN) is a basic component of internet and it plays an important role in many application areas, such as military surveillance, environmental monitoring and medical treatment. Node localization is one of the interesting issues in the field of WSN. Now, most of the existing node localization algorithms can be divided into two categories. One is range-based measurement and the other is range-free measurement. The localization algorithm of range-based measurement can achieve better location accuracy than the localization algorithm of range-free measurement. However, they are generally very energy consuming. Therefore, the range-free measurements are most widely used in practical applications. According to the application of localization algorithm in WSN by range-free measurements, an improved centroid localization algorithm based on iterative computation for wireless sensor network is proposed. In this algorithm, the position relationship of the closed area surrounded by the anchor nodes inside the unknown node's communication range and the unknown node is obtained by approximate point-in-triangulation test at first. Different position relationships determine different stopping criteria for iteration. Then, the centroid coordinates of the closed area surrounded by the anchor nodes inside the unknown node's communication range and the received signal strength (RSSI) between the centroid node and the unknown node are calculated. The anchor node with the weakest RSSI would be replaced by the centroid node. By this method, the closed area surrounded by the anchor nodes inside the unknown node's communication range is reduced. The location accuracy is increased by the cyclic iterative method. With the change of the anchor node ratio, the communication radius of the unknown node and the effect of RSSI error, the algorithm performance is investigated by using simulated data. The simulation results validate that although the improved centroid localization algorithm performance will be lost when the number of the anchor nodes inside the unknown node communication range decreases, the new approach can achieve good performance under the condition of few anchor nodes inside the unknown node communication range and this method is of strong robusticity against RSSI error disturbance.
2016, 65 (6): 064602.
doi: 10.7498/aps.65.064602
Abstract +
A multi-frequency locally resonant (LR) phononic plate is proposed in this paper. The phononic plate consists of periodic arrays of multiple double-cantilevered thin beams attached to a thin homogeneous plate. This proposed phononic plate is simplified and modeled using a plane wave expansion method to enable the calculation of flexural wave band structures. The band gap behavior of the phononic plate is analyzed comprehensively. In addition, an experimental specimen is fabricated using a square aluminum plate with a thickness of 0.9 mm and an area of 840 mm840 mm, and attached to the specimens as periodic arrays of two types of double-cantilevered thin beams made of the same material as the host plate. And the specimen is measured by using a scanning laser Doppler vibrometer to verify the theoretical predictions of band gaps. Investigations of this paper yield the following findings and conclusions: (1) Due to the interaction of low-frequency vibrational modes of attached multiple double-cantilevered beams and flexural vibration of the host plate, the proposed multi-frequency LR phononic plate can exhibit multiple low-frequency flexural wave band gaps (stop bands). It is also found that the band gaps of a multi-frequency LR phononic plate, especially those appearing in a lower frequency range, are generally narrower than that of a single-frequency LR phononic plate with the same type of double-cantilevered beams. (2) The frequency location of band gaps moves to higher frequency range when the thickness of the double-cantilevered beams is increased, or when the length of the double-cantilevered beams is decreased. It is also shown that a very small variation of the thickness (e. g., 0.1 mm) may lead to significant changes of frequency position of the band gaps. (3) When the width of the double-cantilevered beams is enlarged or the number of the double-cantilevered beams is increased, the lower band gap edge will move to a lower frequency range, while the upper band gap edge will move to a higher frequency range. This implies that the bandwidth of the band gaps is broadened. However, at the same time, it is shown that the central frequencies of the band gaps remain almost unchanged. (4) Experimental measurements of the fabricated specimen evidence the existence of two low frequency band gaps, and confirm that the flexural plate vibrations are significantly reduced in the predicted band gaps.
2016, 65 (13): 130501.
doi: 10.7498/aps.65.130501
Abstract +
Since wind has an intrinsically complex and stochastic nature, accurate wind power prediction is necessary for the safety and economics of wind energy utilization. Aiming at the prediction of very short-term wind power time series, a new optimized kernel extreme learning machine (O-KELM) method with evolutionary computation strategy is proposed on the basis of single-hidden layer feedforward neural networks. In comparison to the extreme learning machine (ELM) method, the number of the hidden layer nodes need not be given, and the unknown nonlinear feature mapping of the hidden layer is represented with a kernel function. In addition, the output weights of the networks can also be analytically determined by using regularization least square algorithm, hence the kernel extreme learning machine (KELM) method provides better generalization performance at a much faster learning speed. In the O-KELM, the structure and the parameters of the KELM are optimized by using three different optimization algorithms, i.e., genetic algorithm (GA), differential evolution (DE), and simulated annerling (SA), meanwhile, the output weights are obtained by a least squares algorithm just the same as by the ELM, but using Tikhonovs regularization in order to further improve the performance of the O-KELM. The utilized optimization algorithms of the O-KELM are respectively used to select the set of input variables, regularization coefficient as well as hyperparameter of kernel function. The proposed method is first applied to the direct six-step prediction for Mackey-Glass chaotic time series, under the same condition as the existing optimized ELM method. From the analysis of the simulation results it can be verified that the prediction accuracy of the proposed O-KELM method is increased by about one order of magnitude over that of the optimized ELM method. Furthermore, the DE-KELM algorithm can achieve the lowest root mean square error (RMSE). The O-KELM method is then applied to real-world wind power prediction instance, i.e., the Western Dataset from NERL. The 10-minute ahead single-step prediction as well as 20-minute ahead, 30-minute ahead, 40-minute ahead multi-step prediction for wind power time series are respectively implemented to evaluate the O-KELM method. Experimental results of each of the short-term wind power time series predictions at different time horizons confirm that the proposed O-KELM method tends to have better prediction accuracy than the optimized ELM method. Moreover, the GA-KELM algorithm outperforms other two O-KELM algorithms at future 10-minute, 20-minute, 40-minute ahead prediction in terms of the RMSE value. The DE-KELM algorithm outperforms other algorithms at future 30-minute ahead prediction in terms of the normalized mean square error (NMSE) and the RMSE value. The results from these applications demonstrate the effectiveness and feasibility of the proposed O-KLEM method. Therefore, the O-KELM method has a potential future in the field of wind power prediction.
2016, 65 (11): 118701.
doi: 10.7498/aps.65.118701
Abstract +
The functional corticomuscular coupling (FCMC) is defined as the interaction, coherence and time synchronism between cerebral cortex and muscle tissue, which could be revealed by the synchronization analyses of electroencephalogram (EEG) and electromyogram (EMG) firing in a target muscle. The FCMC analysis is an effective method to describe the information transfer and interaction in neuromuscular pathways. Forthermore, the multiscaled coherence analyses of EEG and EMG signals recorded simultaneously could describe the multiple spatial and temporal functional connection characteristics of FCMC, which could be helpful for understanding the multiple spatial and temporal coupling mechanism of neuromuscular system. In this paper, based on the adaptively decomposing signal into frequency band characteristis of variational mode decomposition (VMD) and the quantitatively detecting the directed exchange of information between two systems of transfer entropy (TE), a new methodvariational mode decomposition-transfer entropy (VMD-TE) is proposed. The VMD-TE method could quantitatively analyze the nonlinear functional connection characteristic on multiple time-frequency scales between EEG over brain scalp and surface EMG signals from flexor digitorum surerficialis, which are recorded simultaneously during grip task with steady-state force output.In this paper, application of VMD-TE method consists of two steps. Firstly, the EEG and EMG signals are adaptively decomposed into multi intrinsic mode functions based on variational mode decomposition method, respectively, to describe the information on different time-frequency scales. Then the transfer entropies between the different timefrequency scales of EEG and EMG are calculated to describe the nonlinear corticomuscular coupling characteristic in different pathways (EEGEMG and EMGEEG), to show the functional coupling strength (namely VMD-TE values). finally, the maximum VMD-TE values between the different time-frequency scales of EEG and EMG signals among the eight subjects are selected, to describe the discrepancies of FCMC interaction strength between all time-frequency scales. The results show that functional corticomuscular coupling is significant in both descending (EEGEMG) and ascending (EMGEEG) directions in the beta-band (15-35 Hz) in the static force output stage. Meanwhile, the interaction strength between EEG signal and the gamma band (50-72 Hz) of EMG signal in descending direction is higher than in ascending direction. Our study confirms that the beta oscillations of EEG travel bidirectionally between sensorimotor
2016, 65 (16): 168901.
doi: 10.7498/aps.65.168901
Abstract +
Influential nodes in large-scale complex networks are very important for accelerating information propagation, understanding hierarchical community structure and controlling rumors spreading. Classic centralities such as degree, betweenness and closeness, can be used to measure the node influence. Other systemic metrics, such as k-shell and H-index, take network structure into account to identify influential nodes. However, these methods suffer some drawbacks. For example, betweenness is an effective index to identify influential nodes. However, computing betweenness is a high time complexity task and some nodes with high degree are not highly influential nodes. Presented in this paper is a simple and effective node influence measure index model based on a triangular structure between a node and its neighbor nodes (local triangle centrality (LTC)). The model considers not only the triangle structure between nodes, but also the degree of the surrounding neighbor nodes. However, in complex networks the numbers of triangles for a pair of nodes are extremely unbalanced, a sigmoid function is introduced to bound the number of triangles for each pair of nodes between 0 and 1. The LTC model is very flexible and can be used to measure the node influence on weighted complex networks. We detailedly compare the influential nodes produced by different approaches in Karata network. Results show that LTC can effectively identify the influential nodes. Comprehensive experiments are conducted based on six real complex networks with different network scales. We select highly influential nodes produced by five benchmark approaches and LTC model to run spreading processes by the SIR model, thus we can evaluate the efficacies of different approaches. The experimental results of the SIR model show that LTC metric can more accurately identify highly influential nodes in most real complex networks than other indicators. We also conduct network robustness experiment on four selected networks by computing the ratio of nodes in giant component to remaining nodes after removing highly influential nodes. The experimental results also show that LTC model outperforms other methods.
2016, 65 (17): 178701.
doi: 10.7498/aps.65.178701
Abstract +
Predicting 3D structure of proteins from the amino acid sequences is one of the most important unsolved problems in computational biology and biophysics. This review article attempts to introduce the most recent effort and progress on this problem. After a brief introduction of the background and basic concepts involved in protein structure prediction, we went through the specific steps that have been taken by most typical structural modeling approaches, including fold recognition, model initialization, conformational search, model selection, and atomic-level structure refinement. Several representative structure prediction methods were introduced in detail, including those from both template-based modeling and ab initio folding approaches. Finally, we overview the results shown in the community-wide Critical Assessment of protein Structure Prediction (CASP) experiments that have been developed for benchmarking the state of the art of the field.
2016, 65 (24): 240701.
doi: 10.7498/aps.65.240701
Abstract +
In recent years,the modeling and application of biological neurons have gained more and more attention.By now, the research on neuron models has become one of the most important branches of neuroscience.Neuron models can be used in various areas,such as biomimetic applications,memory design,logical computing,and signal processing. Furthermore,it is significant to study the dynamic characteristics of neural system by using neuron models.In this paper,the historical development of neuron models is reviewed.The neuron models have experienced three development stages.In the pioneering stage,a group of scientists laid the experimental and theoretical foundation for later research. Then,the whole study started to blossom after the publication of Hodgkin-Huxley model.In the 1970s and 1980s,various models were proposed.One of the research focuses was the simulation of neural repetitive spiking.Since the 1990s, researchers have paid more attention to setting up models that are both physiologically meaningful and computationally effective.The model put forward by Izhikevich E M has been proved to solve the problem successfully.Recently,IBM presented a versatile spiking neuron model based on 1272 ASIC gates.The model,both theoretically understandable and physically implementable,has been used as a basic building block in IBM's neuro-chip TrueNorth.In the paper, seventeen neuron models worth studying are listed.To give a more explicit explanation,these models are classified as two groups,namely conductance-dependent and conductance-independent models.The former group's goal is to model the electrophysiology of neuronal membrane,while the latter group is only to seek for capturing the input-output behavior of a neuron by using simple mathematical abstractions.The complexity and features of each model are illustrated in a chart,while the prominent repetitive spiking curves of each model are also exhibited.Five of the models are further detailed,which are the Hodgkin-Huxley model,the Integrate-and-fire model,the Fitzhugh-Nagumo model,the Izhikevich model,and the most recent model used by IBM in its neuro-chip TrueNorth.Finally,three questions are put forward at the end of the paper,which are the most important problems that today's researchers must consider when setting up new neuron models.In conclusion,the feasibility of physical implementation remains to be a challenge to all researchers. Through the aforementioned work,the authors aim to provide a reference for the study that follows,helping researchers to compare those models in order to choose the properest one.
2016, 65 (9): 094501.
doi: 10.7498/aps.65.094501
Abstract +
With the development of space technology, flexible appendages such as lightweight manipulators and satellite antennas, often appear in spacecrafts. Usually, the large overall motion of the flexible appendage will bring about large deformation problem. And there is a strong nonlinear coupling between the large overall motion and deformation of the flexible appendage, which brings about a large challenge to the precise control of the spacecraft. Dynamics of a rotating flexible planar beam with large deformation is investigated in this paper. A new nonlinear dynamic model of a flexible beam with large deformation is established based on an absolute node coordinate formulation (ANCF). The longitudinal and bending deformations of the flexible beam are both considered in the model. The longitudinal strain energy and bending strain energy of the beam can be calculated by using Green-Lagrangian strain tensor and the exact expression of the flexible beam curvature, respectively. A new concise expression of the bending deformation energy can be obtained by using the Lagrange identical equation. The new elastic force model is derived from the new expression of the deformation energy. The dynamic equations of the present model can precisely deal with the large deformation problem of flexible beams. Then, simulation results from three dynamic models, including the ANCF model, the high order coupling model (HOC model), and the BEAM188 model in ANSYS, are compared to prove the validity of the ANCF model proposed in this paper. And we can also find the deficiency of the HOC model from the simulation. Further study shows that the new generalized elastic force model can be simplified properly. Two simplified models are presented in this paper. The applicabilities of the simplified models are pointed out from the viewpoints of computational efficiency and accuracy. A dimensionless parameter denoted as is introduced to describe the extent to which a flexible beam pendulum undergoing free falling motion is deformed. The deformation of the flexible beam increases as increases. Considering the calculating efficiency of the dynamic model, when is small, simplified model I is chosen preferentially; when is big, simplified model Ⅱ is adopted preferentially.
2016, 65 (23): 237902.
doi: 10.7498/aps.65.237902
Abstract +
Recently, all-solid state hybrid solar cells based on organic-inorganic metal halide perovskite (ABX3) materials have received much attention from the academic circle all over the world due to their unique physical and chemical properties. The perovskite materials exhibit advantages of high extinction coefficient, high charge mobility, long carrier lifetime, and long carrier diffusion distance. Furthermore, they are low cost and easily synthesized. The power conversion efficiency (PCE) has exceeded 20.8% since the PCE of 3.8% was first reported in 2009, making the perovskite solar cells the best potential candidate of the new generation solar cells to replace the high-cost and highly polluting silicon solar cells in the future. Meanwhile, because of the well-known special bipolar properties of the perovskite materials, various structures are designed such as the all-solid state mesoscopic heterojunctions, planar-heterojunctions, meso-superstructures, and HTM-free structures. In this review, we first introduce the development of the perovskite solar cells and then focus on the cell structure and its influence on the cell performance. Besides, the synthesis methods of the perovskite films and the performance characteristics and advantages of the perovskite solar cells with different cell structures are also discussed. It is found that although the perovskite crystals prepared by a one-step spin-coating method have bigger grain sizes, their morphologies are rougher and uncontrollable, which may suppress the charge carrier extraction efficiency and lead to a relatively low power conversion efficiency. Meanwhile, vapor-assisted method needs vaccum conditions, which significantly increases the manufacture cost of PSC. Compared with these methods mentioned above, solution-based sequential deposition method can not only enhance the reproducibility of PSC, but also obtain a higher PCE with a lower cost. Afterwards, the photogenerated carrier transport mechanism of the perovskite solar cells is discussed. The possible atomic interaction model and the electron structure between perovskite film and electron transport layer are proposed. There are two possible interface atomic structures at the interface of perovskite CH3NH3PbI3 and TiO2. It is supposed that the interaction between iodine atoms and titanium atoms dominates the atomic structure at the interface of CH3NH3PbI3 and TiO2, while the lead atoms are believed to bond to oxygen atoms. As is well known, charge extraction, transfer and recombination mainly occur at the interface of a cell. Therefore, the interface engineering including the design for energy level matching is important and necessary to enhance the charge transport efficiency, suppress the charge recombination and eventually improve the performance of perovskite solar cells. Moreover, the properties of the main electron transport layer (ZnO, TiO2, PCBM, Al2O3) and hole transport layer (spiro-OMeTAD, P3 HT, NiO, PTAA) and their influences on the PCE of the perovskite solar cells are discussed. The main challenges of the all-solid state hybrid perovskite solar cells such as environment pollution, the extremely small working areas and the instability are introduced. Finally, the development prospects of perovskite solar cells in the future are proposed in order to have a better understanding of the perovskite solar cells.
2016, 65 (2): 028902.
doi: 10.7498/aps.65.028902
Abstract +
From the study of multilayer networks, scientists have found that the properties of the multilayer networks show great difference from those of the traditional complex networks. In this paper, we derive strictly the spectrum of the super-Laplacian matrix and the synchronizability of two-layer star networks by applying the master stabi- lity method. Through mathematical analysis of the eigenvalues of the super-Laplacian matrix, we study how the node number, the inter-layer and the intra-layer coupling strengths influence the synchronizability of a two-layer star net-work. We find that when the synchronous region is unbounded, the synchronizability of a two-layer star network is only related to the intra-layer coupling strength between the leaf nodes or the inter-layer coupling strength of the entire network. If the synchronous region of a two-layer star network is bounded, not only the inter-layer coupling strength of the network and the intra-layer coupling strength between the leaf nodes, but also the intra-layer coupling strength between the hub nodes and the network size have influence on the synchronizability of the networks. Provided that the same inter-layer and intra-layer coupling strengths are concerned, we would further discuss the opti-mal ways of strengthening the synchronizability of a two-layer star network. If the inter-layer and intra-layer coupling strengths are far less than unity, changing the intra-layer coupling strength is the best way to enhance the synchronizability no matter what the synchronous region is. While if the coupling strengths are the same as, less than or more than unity, there will be different scenarios for the network with bounded and unbounded synchronous regions. Besides, we also discuss the synchronizability of the multilayer network with more than two layers. And then, we carry out numerical simulations and theoretical analysis of the two-layer BA scale-free networks coupled with 200 nodes and obtain very similar conclusions to that of the two-layer star networks. Finally, conclusion and discussion are given to summarize the main results and our future research interests.
2016, 65 (4): 048401.
doi: 10.7498/aps.65.048401
Abstract +
In this paper, we investigate the transmission mechanism and eddy-current loss of the contact-less power transmission (CPT) system in seawater environment. Contact-less power transfer could be achieved in the three following ways: magnetic coupling, magnetic resonance coupling, and microwave radiation. When the primary and secondary coils are in resonance, a channel of low resistance in the magnetic resonance coupling system is formed. Therefore, it is used for medium-distance power transmission and it has less restrictions on orientation, which means that it has wide applications in many scenarios. Moreover, contact-less power transfer is safer and more concealed than traditional plug power supply, especially in underwater vehicles. Firstly, the mathematical model based on the mutual inductance model is proposed for the CPT system in the air, then the frequency analysis of the CPT model as well as theoretical explanation of the splitting phenomenon is conducted, after that we consider the seawater effect on the mutual inductance coefficient. Secondly, we build a mathematical model of the eddy-current loss in seawater circumstance according to the Maxwell's equations, where we introduce an average magnetic induction in cross section, then derive an approximate formula through Taylor expansion, and analyze the relations between eddy-current loss and the physical parameters including coil radius, resonance frequency, transmission distance, and magnetic induction. According to the theoretical results, we optimize these physical parameters and then design a 754 kHz CPT system, thereafter we validate the CPT system both in the air and in seawater and find the difference between these two circumstances, and verify the relations between eddy-current loss and the physical parameters which are proposed in our theory. It can be learned from the experiment that when transmission distance is 50 mm and transmission power is 100 W in the air, the transmission efficiency is over 80%, and when transmission distance is 50 mm and transmission power is 100 W in seawater, the transmission efficiency is over 67%. Apparently, our magnetic-resonance-coupling-based CPT system has potentials serving as an underwater vehicle.
2016, 65 (1): 014704.
doi: 10.7498/aps.65.014704
Abstract +
The objective of this present study is to address the cavitating flow patterns and regimes in the water-entry cavity. For this purpose, an experimental study of vertical water-entry cavity of an end-closed cylindrical shell is investigated by using high-speed video cameras and visualization technique. According to the cavitating flows as observed in the experiments, two flow pattern forms of fluctuation cavitation and cloud cavitation are found around the body. A further insight into the characteristics of the cavity shape and the variation in the cavity fluctuations parameters is gained by analyzing the image data. Furthermore, the experiments at different impact velocities are conducted to analyze the effects of impact velocity on the flow patterns and parameters. Finally, the formation mechanisms of cavitation fluctuations and cavitation clouds are studied based on the basic theory of fluid mechanics. The obtained results show that the cavitation flow pattern form of fluctuation cavitation occurs under the impact velocity condition of low speed, and the cloud cavitation occurs under the velocity condition of high speed. As fluctuation cavitation, the maximal extension diameters of cavitation fluctuate periodically along the water depth, and the speeds of extension and shrinkage are both proportional to the extension diameter. The collapses are different for the two flow pattern cavitations, i.e., the fluctuation cavitation, which is of deep closure and closed at the trough of wave cavitation more than once, and the cloud cavitation, which falls off and forms the leading edge of the cylindrical shell. The frequency fluctuation is independent of the impact velocity, the corresponding pinch-off time decreases with increasing the impact velocity, and the pinch-off time decreases in a nearly linear relation with Froude number. The water poured to the cylindrical shell causes the internal air to compress and expand, and as a consequence of these effects, periodic disturbances of pressure distribution and velocity field occur around the leading edge of the cylindrical shell, then the extended intensity of the cross section of the cavity shows variation in this process, which can be defined as fluctuation cavitation pattern. It appears that the re-entrant flow after the pinch-off at the trailing edge of cavity, then the laminar-turbulent transition is waken as a consequence of the re-entrant flow moving upstream, which flow pattern involved in this structure occurs as cloud cavitation.
2016, 65 (18): 180501.
doi: 10.7498/aps.65.180501
Abstract +
The classical attractors, defined as self-excited attractors, such as Lorenz attractor, Rssler attractor, Chua's attractor and many other well-known attractors, are all excited from unstable index-2 saddle-foci, namely, an attractor with an attraction basin corresponds to an unstable equilibrium. A new type of attractors, defined as hidden attractors, was first found and reported in 2011, whose attraction basin does not intersect with small neighborhoods of the equilibria of the system. Due to the existences of hidden attractors, some particular dynamical systems associated with line equilibrium, or no equilibrium, or stable equilibrium have attracted much attention recently. Additionally, by introducing memristors into existing oscillating circuits or substituting nonlinear resistors in classical chaotic circuits with memristors, a variety of memristor based chaotic and hyperchaotic circuits are simply established and has been broadly investigated in recent years. Motivated by these two considerations, in this paper, we present a novel memristive system with no equilibrium, from which an interesting and striking phenomenon of coexistence of the behaviors of hidden multiple attractors and the corresponding multistability is perfectly demonstrated by numerical simulations and experimental measurements.
According to a newly proposed circuit realization scheme, a new type of four-dimensional memristive self-oscillated system is easily implemented by directly replacing a linear coupling resistor in an existing three-dimensional self-oscillated system circuit with a voltage-controlled memristor. The proposed system has no equilibrium, but can generate various hidden attractors including periodic limit cycle, quasi-periodic limit cycle, chaotic attractor, and coexisting attractors and so on. Based on bifurcation diagram, Lyapunov exponent spectra, and phase portraits, complex hidden dynamics with respect to a system parameter of the memristive self-oscillated system are studied. Specially, when different initial conditions are used, the system displays the coexistence phenomenon of chaotic attractors with different topological structures or quasi-periodic limit cycle and chaotic attractor, as well as the phenomenon of multiple attractors of quasi-periodic limit cycle and chaotic attractors with multiple topological structures. The results imply that some coexisting hidden multiple attractors reflecting the emergences of multistability can be observed in the proposed memristive self-oscillated system, which are well illustrated by several conventional dynamical analysis tools. Based on PSIM circuit simulation model, the memristive self-oscillated system is easily made in at a hardware level on a breadboard and two kinds of dynamical behaviors of coexisting hidden multiple attractors are captured in hardware experiments. Hardware experimental measurements are consistent with numerical simulations, which demonstrates that the proposed memristive self-oscillated system has very abundant and complex hidden dynamical characteristics.
2016, 65 (13): 138401.
doi: 10.7498/aps.65.138401
Abstract +
Since the rotorcraft can easily be recognized by using the micro-Doppler (m-D) signature of rotor blades, the m-D effect induced by micro-motion dynamics plays an important role in target recognition and classification. However, the existing researches on the rotor blades pay little attention to the mechanism of the time-domain and time-frequency-domain flash phenomena. To comprehensively explain the flash phenomena from physics, the modeling of the rotor blades and the mechanism of the flash phenomena are studied in this paper. Firstly, for the rotor blades, the target cannot be represented as a rigid, homogeneous line nor several points. Taking the scattering coefficients and the interval of adjacent scattering points (the scattering point distribution on the blade) into consideration, the scattering point model of the rotor blade echo is established, and the influence of the scattering point distribution on the radar echo is analyzed as well. The detailed mathematic analysis and comparison results show that the conventional integral model of the rotor blade is only a special case of the scattering point model. Furthermore, In the case where the scattering point model is approximately equivalent to the conventional integral model, the critical interval of adjacent scattering points is deduced by mathematic analysis. Secondly, on the basis of the proposed model above, the physical mechanism of the time-domain and time-frequency-domain flash phenomena is studied from the viewpoint of the electromagnetic (EM) scattering. On the one hand, considering the EM scattering and scattering point distribution, the mechanism of the time-domain flashes is analyzed. Ideally, when the rotor blade is at the vertical position relative to the radar line of sight, i.e., at the flash time, the blade has the strongest echo. At this moment, the radar echo consists of echoes of all scattering points, thus inducing the time-domain flashes. At the non-flash time, the scattering points at the tip of blade and hub of rotor have stronger scattering intensities, so the echo is much weaker than that at the flash time. On the other hand, the time-frequency analysis and the cross range resolution are simultaneously used to analyze the mechanism of the time-frequency-domain flashes in the m-D signature. The m-D signature of the rotor blades consists of three parts: the time-frequency-domain flashes, the sinusoidal Doppler curves, and the zero-frequency band. At the flashes time, the Doppler frequency of adjacent scattering points cannot be distinguished, thus the m-D signature has the frequency band caused by all scattering points, i.e., the time-frequency-domain flashes appear. At the non-flash time, the sinusoidal Doppler curves and the zero-frequency band are caused by the scattering points at the tip of blade induced by the scattering points at the hub of rotor respectively. Finally, the simulation results about the scattering point model with the different intervals of adjacent scattering points show that the effectiveness of the proposed model and the correctness of theoretical analysis.
2016, 65 (4): 047201.
doi: 10.7498/aps.65.047201
Abstract +
VO2 is a metal oxide that has a thermally-induced phase-transition. In the vicinity of 341 K, VO2 undergoes a reversible transition from the high-temperature metal phase to the low-temperature insulator phase. Associated with the metal-insulator transition (MIT), there are drastic changes in its optical, electrical and magnetic characteristics. These make VO2 an attractive material for various applications, such as optical and/or electrical switches, smart glass, storage media, etc. Thus, the reversible metal-insulator phase transition in VO2 has long been a research hotspot. However, the metal-insulator transition mechanism in VO2 has been a subject of debate for several decades, and yet there is no unified explanation. This paper first describes changes of the crystal structure and the energy band structure during VO2 phase transition. With regard to the crystal structure, VO2 transforms from the low-temperature monoclinic phase VO2(M) into the high-temperature stable rutile phase VO2(R), and in some special cases, this phase transition process may also involve a metastable monoclinic VO2(B) phase and a tetragonal VO2(A) phase. In respect of the energy band structure, VO2 undergoes a transition from the low-temperature insulator phase into a high-temperature metal phase. In the band structure of low-temperature monoclinic phase, there is a band gap of about 0.7 eV between d// and * bands, and the Fermi level falls exactly into the band gap, which makes VO2 electronically insulating. In the band structure of high-temperature rutile phase, the Fermi level falls into the overlapping portion of the * and d// bands, which makes VO2 electronically metallic. Next, this paper summarizes the current research status of the physical mechanism underlying the VO2 MIT. Three kinds of theoretical perspectives, supported by corresponding experimental results, have been proposed so far, which includes electron-correlation-driven MIT, Peierls-like structure-driven MIT, and MIT driven by the interplay of both electron-correlation and Peierls-like structural phase transition. It is noted that recent reports mostly focus on the controversywhether VO2 is a Mott insulator, and whether the structural phase transition and the MIT accurately occur simultaneously in VO2. Finally, the paper points out the near-future development direction of the VO2 research.
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