Structural,electrical, and linear/nonlinear optical characteristics of thermally evaporated molybdenum oxide thin films

Homogeneous thin films of Molybdenum oxide (MoO₃) were grown on quartz and glass substrates using the thermal evaporation method. XRD results showed that the MoO₃ powder has a polycrystalline structure with an orthorhombic crystal system whereas the MoO₃ thin films have amorphous nature. SEM images showed that the MoO₃ thin films have a nearly uniform surfaces with worm-like shape grains. The film thickness influences on the linear and nonlinear optical characteristics of MoO₃ thin films that were examined using spectrophotometric measurements and from which, the linear optical constants of the MoO₃ thin films were estimated. The electronic transition type was determined as a direct allowed one. The values of the optical band gap were obtained to be in the range of 3.88–3.72 eV. The dispersion parameters, third-order nonlinear optical susceptibility, and the nonlinear refractive index of the MoO₃ thin films were determined and interpreted in the light of the single oscillator model. The temperature dependence of the DC electrical conductivity and the corresponding conduction mechanism for the MoO₃ films were investigated at temperatures ranging from 303 to 463 K.     

Various density light field image coding based on distortion minimization interpolation

In recent years, the light field (LF) as a new imaging modality has attracted wide interest. The large data volume of LF images poses great challenge to LF image coding, and the LF images captured by different devices show significant differences in angular domain. In this paper we propose a view prediction framework to handle LF image coding with various sampling density. All LF images are represented as view arrays. We first partition the views into reference view (RV) set and intermediate view (IV) set. The RVs are rearranged into a pseudo sequence and directly compressed by a video encoder. Other views are then predicted by the RVs. To exploit the four dimensional signal structure, we propose the linear approximation prior (LAP) to reveal the correlation among LF views and efficiently remove the LF data redundancy. Based on the LAP, a distortion minimization interpolation (DMI) method is used to predict IVs. To robustly handle the LF images with different sampling density, we propose an Iteratively Updating depth image based rendering (IU-DIBR) method to extend our DMI. Some auxiliary views are generated to cover the target region and then the DMI calculates reconstruction coefficients for the IVs. Different view partition patterns are also explored. Extensive experiments on different types LF images also valid the efficiency of the proposed method.     

Evolution of linear edge dislocation in atmospheric turbulence and free space

In accordance with the extended Huygens–Fresnel principle, the evolution of linear edge dislocation propagating through atmospheric turbulence is studied, and the effects of waist width and the slope of linear edge dislocation are investigated. It is shown that when linear edge dislocation beams propagate through atmospheric turbulence, if the waist width is not equal and the slope is not zero, then the linear edge dislocation vanishes and transforms into an optical vortex with a topological charge of ?1 or +1. The optical vortex and an optical vortex that is created annihilate when the transmission distance is far enough. The linear edge dislocation vanishes when the slope is zero. If the waist width is equal, then the linear edge dislocation will vanish regardless of the slope value. For linear edge dislocation beams in free space, when selecting specific parameters, linear edge dislocation always exists.     

Transverse magnetoresistance peculiarities of thermoelectric Lu-doped Bi2Te3 compound due to strong electrical disorder

The n-type thermoelectric Bi_1.9Lu_0.1Te₃ was prepared by microwave-solvothermal method and spark plasma sintering. The magnetic field and temperature dependences of transverse magnetoresistance measured within temperature 2–200 K interval allow finding the peculiarities characteristic for strongly disordered and inhomogeneous semiconductors. The first peculiarity is due to appearance of linear-in-magnetic field contribution to the total magnetoresistance reflected in a crossover from quadratic magnetoresistance at low magnetic fields to linear magnetoresistance at high magnetic fields. The linear magnetoresistance can result from the Hall resistance picked up from macroscopically distorted current paths due to local variations in stoichiometry of the compound studied. The second peculiarity is that both linear magnetoresistance magnitude and crossover field are functions of carrier mobility which is in agreement with the Parish and Littlewood model developed for disordered and inhomogeneous semiconductors. An increase in the mobility due to a decrease in temperature is accompanied by an increase in the magnetoresistance magnitude and a decrease in the crossover field. Finally, the third peculiarity is related to the remarkable deviation of the total magnetoresistance measured at various temperatures from the Kohler's rule. Presence of strong inhomogeneity and disorder in the Bi_1.9Lu_0.1Te₃ structure concluded from the magnetoresistance peculiarities can be responsible for the remarkable reduction in the total thermal conductivity of this compound.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

Application of full order sliding mode control based on different areas power system with load frequency control

In the traditional sliding mode control method, there always exist the singularity due to the reduced order of the control method. In order to eliminate the singularity, I propose a new full order sliding mode control method in this article, which has been firstly applied to load frequency control. The full order sliding mode control method includes the terminal sliding mode control (TSM) and the linear sliding mode control (LSM). TSM has the good characteristic of eliminating the singularity due to the avoidance of derivative of terms with fractional power factors. While the LSM is easy to design and has fast time convergence comparing to TSM. The model is based on the system with different kinds of turbine or the same kind of turbine, which contains the nonlinearities. The control purpose is to adjust the frequency deviation to zero. Through the simulation results, it is shown that the frequency deviation can be kept to zero in the condition of different load disturbances by the two approaches, which approves the robustness of the proposed methods. In addition, we compare the two methods with the traditional sliding mode control (SMC), which proves the superiority of the two methods in terms of chattering and response time.     

Silicon-silver dendritic nanostructures for the enhanced photoelectrochemical splitting of natural water

We report on the photoelectrochemical (PEC) splitting of natural water (pH 7) using silicon (Si) nanowires fitted with silver (Ag) dendrites (dendritic nanostructures) as working electrodes (photoanodes). A detailed study of the PEC water splitting process was carried out using linear sweep voltammetry, electrochemical impedance spectroscopy (EIS) and Mott-Schottky (M-S) measurements. The measured photocurrent density of 1.7 mA/cm² at an external voltage of ?0.6 V under white light illumination demonstrates the efficient decomposition of natural water using dendritic nanostructures as working electrodes. This decomposition is mainly attributed to a significant strengthening of the effective interface between working electrode surface/water and to a decline in the recombination of photoinduced carriers in the presence of Ag dendrites. We propose that the Schottky barrier between Si and Ag dendritic nanostructures favors enhanced photoinduced charge carrier separation. Photoinduced holes in Si are transferred to Ag dendrites (nano branches and leaves) that serve as a charge sink to effectively carry out the PEC oxidation of water. Photoinduced charge carrier separation enhancement was corroborated by the kinetics of our carrier recombination study. We obtained a reasonably long transient period of 80 s for the photoinduced carriers. EIS results show that the charge transfer resistance (150 Ω) of the dendritic nanostructure surface is low enough to promote interfacial charge transfer. This resistance generated a large carrier concentration of ～1.1 × 10²⁰ cm^?3 at the working electrode/water interface according to an M-S analysis. An applied bias-photon-to-current-conversion efficiency level of roughly 4% is reported, demonstrating the efficient PEC splitting of natural water.     

Temporal information based GoP adaptation for linear video delivery schemes

An original wireless video transmission scheme called SoftCast has been recently proposed to deal with the issues encountered in conventional wireless video broadcasting systems (e.g. cliff effect). In this paper, we evaluate and optimize the performance of the SoftCast scheme according to the transmitted video content. Precisely, an adaptive coding mechanism based on GoP-size adaptation, which takes into account the temporal information fluctuations of the video, is proposed. This extension denoted Adaptive GoP-size mechanism based on Content and Cut detection for SoftCast (AGCC-SoftCast) significantly improves the performance of the SoftCast scheme. It consists in modifying the GoP-size according to the shot changes and the spatio-temporal characteristics of the transmitted video. When hardware capacities, such as buffer or processor performance are limited, an alternative method based only on the shot changes detection (AGCut-SoftCast) is also proposed. Improvements up to 16 dB for the PSNR and up to 0.55 for the SSIM are observed with the proposed solutions at the cut boundaries. In addition, temporal visual quality fluctuations are reduced under 1dB in average, showing the effectiveness of the proposed methods.     

Contributions of oxygen vacancies to the hydrogen evolution catalytic activity of tungsten oxides

The tungsten trioxide attracts less attention due to the low electron transfer kinetics that hinders the interaction of electrons and ions during the hydrogen evolution reaction (HER). But the oxygen vacancy strategy can inspire its electrocatalytic activity for HER because it has a positive effect on improving the charge transfer and compensating for the weak hydrogen adsorption of the tungsten trioxide. By synthesizing a series of substoichiometric tungsten oxides, we reveal the linear relationship between the catalytic activity and the content of oxygen vacancies, which indicates that the oxygen vacancy strategy is an achievable route to enhance the HER for metal oxides.