Al2O3 coated single-crystalline hexagonal nanosheets of LiNi0.6Co0.2Mn0.2O2 cathode materials for the high-performance lithium-ion batteries

Journal of Materials Science - The LiNi0.6Co0.2Mn0.2O2 (NCM) cathode material is highly potential for the wide application in lithium-ion batteries due to its moderate cost and high specific...     

Effect of pre-deposition annealing on physical properties of CZTSSe thin films deposed by RF-sputtering based on nanoparticles synthesized by solvothermal technique

This work aims to highlight the beneficial effect of annealing of Cu₂ZnSn(S,Se)₄ (CZTSSe) nanoparticles (NPs) on the properties of the obtained films by RF-magnetron sputtering at room temperature (RT) and at 200 °C. The CZTSSe targets used for the deposition are obtained using nanoparticles synthesized by solvothermal technique. It is denoted that the elemental composition of thin films becomes independent of the growth temperature in the case of annealed CZTSSe NPs. The optical investigation gives that the gap energy is ranging between 1.26 and 1.40 eV with an Urbach’s energy between 100 and 200 meV. By using the Wemple and Didominico model to analyze the refractive index spectra, we have identified common oscillator energy for all CZTSSe thin films and dispersion energy ranging from 2.63 to 5.81 eV. CZTSSe thin films obtained by means of annealed NPs exhibit higher dielectric constant and refractive index. The dispersion of different parameters with experimental conditions is analyzed via a common relationship that illustrates the linear dependence of n₀, E_d, ε_s, and ε_L on the square of the valence difference (ΔZ). The conductivity spectra are deduced, and a theoretical model was identified to fit the permittivity spectra. The obtained results are promising for solar cell applications.

     

Modelling of axis feed consumed energy for sustainable manufacturing

The accurate evaluation of electrical energy demanded by a CNC toolpath during a machining process is essential to determine its efficiency. Actually, the dynamic behavior of cutting forces seems to be neglected by investigators despite its influence on the consumed cutting energy during a face milling operation. This paper aims to investigate the effect of dynamic behavior of the machining system in order to take into account the dynamic response of the cutting forces on the axis feed power prediction. A dynamic cutting power model is developed in order to predict the consumed cutting energy. A parametric study is performed in order to show the impact of cutting conditions on the consumed energy values. The numerical results are compared to experimental ones.     

Aggregation‐Induced Nonlinear Optical Effects of AIEgen Nanocrystals for Ultradeep In Vivo Bioimaging

Nonlinear optical microscopy has become a powerful tool in bioimaging research due to its unique capabilities of deep optical sectioning, high‐spatial‐resolution imaging, and 3D reconstruction of biological specimens. Developing organic fluorescent probes with strong nonlinear optical effects, in particular third‐harmonic generation (THG), is promising for exploiting nonlinear microscopic imaging for biomedical applications. Herein, a simple method for preparing organic nanocrystals based on an aggregation‐induced emission (AIE) luminogen (DCCN) with bright near‐infrared emission is successfully demonstrated. Aggregation‐induced nonlinear optical effects, including two‐photon fluorescence (2PF), three‐photon fluorescence (3PF), and THG, of DCCN are observed in nanoparticles, especially for crystalline nanoparticles. The nanocrystals of DCCN are successfully applied for 2PF microscopy at 1040 nm NIR‐II excitation and THG microscopy at 1560 nm NIR‐II excitation, respectively, to reconstruct the 3D vasculature of the mouse cerebral vasculature. Impressively, the THG microscopy provides much higher spatial resolution and brightness than the 2PF microscopy and can visualize small vessels with diameters of ≈2.7 µm at the deepest depth of 800 µm in a mouse brain. Thus, this is expected to inspire new insights into the development of advanced AIE materials with multiple nonlinearity, in particular THG, for multimodal nonlinear optical microscopy.     

直流电车杂散电流对城市燃气管道电腐蚀的影响规律研究

为得到轨道与埋地管道并行情况下杂散电流对管道电腐蚀的影响规律,建立了基于电路原理和电力系统接地极理论的双边供电直流电车杂散电流对管地电位干扰模型,并求得了轨道电位和管地电位的分布变化函数以及杂散电流泄漏量分布函数。采用MATLAB进行了数值模拟,得到了杂散电流泄露规律及其对管地电位干扰规律,并对管道防腐蚀层单破损点、双破损点情况下管道的电腐蚀规律进行了分析。结果表明:轨道杂散电流泄露量与轨道电位大小成正比,降低轨道电阻可减小杂散电流泄露量。防腐蚀层单破损点不易产生腐蚀,双破损点导致局部腐蚀较严重,且变电站附近的点腐蚀严重。因此,应重点监测保护变电站处下方管道以减少产生多破损点的概率。     

Fast and low complexity frequency domain analysis of nonuniform substrate integrated waveguide‐based structures

A novel, low complexity approach for the analysis of nonuniform lossy substrate‐integrated waveguide transmission lines based on the method of moments is proposed. The approach uses frequency‐dependent basis functions derived from the structure's propagation characteristics. Two tapered structures are analyzed, fabricated, and measured to validate the proposed approach. The analytical results of the proposed approach for both structures are compared to those obtained by measurement and by three‐dimensional field simulation. Excellent agreement is observed between the three sets of results with simulation time savings on more than 98% and memory requirement reduction of more than 97%.     

Elderly fall detection based on multi-stream deep convolutional networks

Multimedia Tools and Applications - Fall is the biggest threat to seniors, with significant emotional, physical and financial implications. It is the major cause of serious injuries, disabilities,...     

Adaptive Neural Tracking Control for Uncertain Switched Nonlinear Non-lower Triangular System with Disturbances and Dead-zone Input

International Journal of Control, Automation and Systems - This work investigates the adaptive neural tracking control problem for a class of uncertain switched nonlinear non-lower triangular...     

A robust video watermarking based on feature regions and crowdsourcing

Multimedia Tools and Applications - Video watermarking technique aims at resolving insecurity problems. Recently, many approaches have been proposed in order to satisfy the new constraints of video...     

Detection of unanticipated faults for autonomous underwater vehicles using online topic models

For robots to succeed in complex missions, they must be reliable in the face of subsystem failures and environmental challenges. In this paper, we focus on autonomous underwater vehicle (AUV) autonomy as it pertains to self‐perception and health monitoring, and we argue that automatic classification of state‐sensor data represents an important enabling capability. We apply an online Bayesian nonparametric topic modeling technique to AUV sensor data in order to automatically characterize its performance patterns, then demonstrate how in combination with operator‐supplied semantic labels these patterns can be used for fault detection and diagnosis by means of a nearest‐neighbor classifier. The method is evaluated using data collected by the Monterey Bay Aquarium Research Institute's Tethys long‐range AUV in three separate field deployments. Our results show that the proposed method is able to accurately identify and characterize patterns that correspond to various states of the AUV, and classify faults at a high rate of correct detection with a very low false detection rate.