Control of Halogen Atom in Inorganic Metal-Halide Perovskites Enables Large Piezoelectricity for Electromechanical Energy Generation

Regulating the strain of inorganic perovskites has emerged as a critical approach to control their electronic and optical properties. Here, an alternative strategy to further control the piezoelectric properties by substituting the halogen atom (I/Br) in the CsPbX₃ perovskite (X = Cl, Br) structure is adopted. A series of piezoelectric materials with excellent piezoelectric coefficients (d₃₃) are unveiled. Iodine-incorporated CsPbBr₂I demonstrates the record intrinsic piezoelectric response (d₃₃ ≈47 pC N⁻¹) among all inorganic metal halide perovskites. This leads to an excellent electrical output power of ≈ 0.375 mW (24.8 µW cm⁻² N⁻¹) in the piezoelectric energy generator (PEG) which is higher than those of the pristine/mixed perovskite references with CsPbX₃ (X = I, Br, Cl). With its structural phase remaining unchanged, the strained CsPbBr₂I retains its superior piezoelectricity in both thin film and nanocrystal powder forms, further demonstrating its repeatability and versatility of applications. The origin of high piezoelectricity is found to be due to halogen-induced anisotropic lattice strain in the unit-cell along the c-axis, and octahedral distortion. This study reveals an avenue to design new piezoelectric materials by modifying their halide constituents and paves the way to design efficient PEGs for improved electromechanical energy conversion.     

Shielding analysis at the upper section of the accelerator-driven system

The proton beam duct of the accelerator-driven system (ADS) acts as a streaming path for spallation neutrons and photons and causes the activation of the magnets and other devices above the subcritical core. We have performed a streaming analysis at the upper section of the lead-bismuth target/cooled ADS (800 MWth). MCNPX was used to calculate the radiation dose from streamed neutrons and photons through the beam duct. For the secondary photon production calculation, cross sections for several actinides were substituted with plutonium because of the lack of gamma production cross section. From the results of this analysis, the neutron dose from the beam duct is seen to be about 20 orders higher than that of the bulk shield. The magnets and shield plug are heavily irradiated by streaming neutrons according to the DCHAIN-SP analysis.     

Electron microscopy and microanalysis of the fiber-matrix interface in monolithic silicone carbide-based ceramic composite material for use in a fusion reactor application

A composite material made from continuous monolithic silicone carbide (SiC) fibers and a SiC-based matrix (SiC(f)/SiC), was prepared using a novel technique, i.e. adapted dip coating and infiltration of SiC fibers with a water suspension containing SiC particles and a sintering additive. This kind of material could be used in the first-wall blanket of a future fusion reactor. Using magnetron sputtering, the SiC fibers were coated with various thin layers (TiC, CrN, CrC, WC, DLC-diamond-like carbon) of the interface material by physical vapor deposition (PVD). Using scanning and transmission electron microscopy and microanalysis, detailed microstructural studies of the fiber-matrix interface were performed. Both samples, with coated and uncoated fibers, were examined under a load. The microcracks introduced by the Vickers indenter continued their path through the fibers, and thus caused the failure of the composite material, in the case of the uncoated fibers or deviated from their primary direction at the fiber-matrix interface in the case of the coated fibers.     

Diabetes Prediction Algorithm Using Recursive Ridge Regression L2

At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a predictive model with high accuracy. In this work, a wrapper-based feature selection method called recursive feature elimination is combined with ridge regression (L2) to form a hybrid L2 regulated feature selection algorithm for overcoming the overfitting problem of data set. Overfitting is a major problem in feature selection, where the new data are unfit to the model because the training data are small. Ridge regression is mainly used to overcome the overfitting problem. The features are selected by using the proposed feature selection method, and random forest classifier is used to classify the data on the basis of the selected features. This work uses the Pima Indians Diabetes data set, and the evaluated results are compared with the existing algorithms to prove the accuracy of the proposed algorithm. The accuracy of the proposed algorithm in predicting diabetes is 100%, and its area under the curve is 97%. The proposed algorithm outperforms existing algorithms.     

Bottom‐Up Grown 2D InSb Nanostructures

Low‐dimensional high‐quality InSb materials are promising candidates for next‐generation quantum devices due to the high carrier mobility, low effective mass, and large g‐factor of the heavy element compound InSb. Various quantum phenomena are demonstrated in InSb 2D electron gases and nanowires. A combination of the best features of these two systems (pristine nanoscale and flexible design) is desirable to realize, e.g., the multiterminal topological Josephson device. Here, controlled growth of 2D nanostructures, nanoflakes, on an InSb platform is demonstrated. An assembly of nanoflakes with various dimensions and morphologies, thinner than the Bohr radius of InSb, are fabricated. Importantly, the growth of either nanowires or nanoflakes can be enforced experimentally by setting growth and substrate design parameters properly. Hall bar measurements on the nanostructures yield mobilities up to ≈20 000 cm² V^?1 s^?1 and detect quantum Hall plateaus. This allows to see the system as a viable nanoscale 2D platform for future quantum devices.     

从低层次到高层次表示的情感模型研究

情感模型的建立可以使计算机具备基本的情感识别和表达能力,在和谐人机交互方面有着广泛的应用。文中借助于Picard教授关于情感计算的理论,将线性系统理论和数字信号处理方法应用到情感信号与系统建模上,用信号很好地表示了人类的内在情感和情绪,并通过MATLAB仿真实验分析证明了模型的正确性。最后结合情感的高层次认知推理机制,将情感模型应用到情感虚拟人当中,形象地实现了情感对人脸表情变化的控制。     

Reduction in polarization dependent loss of a planar lightwave circuit by ion-implantation-induced birefringence

Reduction in polarization dependent loss of a planar lightwave circuit was achieved by asymmetric birefringence formed by ion implantation, in which oxygen ions were implanted along a diagonal of a cross-section of the planar lightwave circuit. The induced birefringence has a slow axis along the line perpendicular to the diagonal. In the present research, a decrease in polarization dependent loss of up to 3.7 dB was obtained, indicating that the method is effective for reducing polarization dependent loss.     

Theoretical analysis of the impact of Rayleigh noise on the performance of distributed Raman temperature sensors

We present a theoretical model to analyze the impact of Rayleigh noise on Raman distributed temperature sensors (RDTS), which use the anti-Stokes and Stokes light or anti-Stokes component only as the demodulation signals. Based on this model, the effects of Rayleigh noise on temperature accuracy, sensitivity, and resolution are investigated both at only one point and in a section of the fiber. The analysis indicates that for RDTS demodulated by anti-Stokes light only, the temperature accuracy, sensitivity, and resolution decrease by about 1°C, 10%, and 0.25°C on the assumption that the Rayleigh noise accounts for 10% of the anti-Stokes intensity. Moreover, for RDTS demodulated by Stokes and anti-Stokes light, the temperature accuracy, sensitivity, and resolution decrease by about 1°C, 10%, and 0.2°C assuming that the Rayleigh noise in two paths is equal to 10% of the intensity of anti-Stokes and Stokes light. The analysis demonstrates that the impact of Rayleigh noise on sensing capacities of RDTS is non-negligible, thus providing a major contribution to the elimination of Rayleigh noise in RDTS.     

Desktop 3-axis parallel kinematic milling machine

Parallel kinematic machines (PKM) are still a research-and-development topic in many laboratories although many of them, unfortunately, have no PKM at all. Therefore, the use of a desktop educational 3-axis parallel kinematic milling machine is suggested as a help in the process of acquiring basic experiences in the field of PKM. The developed desktop educational 3-axis parallel kinematic milling machine is based on a newly developed 3-DOF spatial parallel mechanism. This paper describes the structure of the machine, modeling approach, and control and programming system based on PC Linux platform with real-time extension and EMC2 (the Enhanced Machine Controller) software system.